To Celebrate the 50th Earth Day – Biodiversity Crisis, Anthropogenic Causes and 6th Mass Extinction Event
Mohammed Ashraf
Gaylord Nelson who pioneered the Earth Day in April 22, 1970
April 22 is Earth Day. It was the brainchild of senator Gaylord Nelson from Wisconsin who was inspired by Rachel’s Carson’s pioneering and most influential work ‘The Silent Spring’ first published in 1962. Nelson in early 1970s was disheartened by the ongoing ecological and social destructions that were brought upon my multi trillion corporations across the United States. He witnessed and ravages the massive oil spilled in Santa Barbra, California in January 1969. Nelson pursued congressmen and other high level political leaders and recruited Dennis Hayes and came up with an idea of picking April 22 as weekday which falls between Spring break and final exam for college students in the United States. The notion behind is to infuse and ignite large scale student driven environmental movement across the United States and in April 22, 1970, twenty million Americans (10% of the total population back then) rolled up their sleeves and hit the road to demonstrate large scale protests against 150 years of industrial revolution that become the social and ecological curse across the globe. Earth Day is monumental achievement, not only for the United States but for all other countries of the world : Thanks to Senator Nelson.
Rachel Carson who pioneered the environmental thinking among public by writing influential book ‘The Silent Spring’ in 1962
The entire gamut of ecological, social and environmental movements and academic disciplines that now came to exist because of these two groundbreaking and most influential American individuals : 1. Ms. Rachel Carson 2. Senator Gaylord Nelson. Fifty years has gone past, significant social and economic developments have taken place and earth is now at the crossroad between human centric destructive development and ecological and biosphere crisis that now leading the earth to 6th Mass Extinction Event. Today we celebrate 50th Anniversary of Earth Day and take a look at some of the key ecological and biological facets and conservation implications across tropical ecoregions.
Image Courtesy : Gurudeep Ramakrishna
Earth is roughly five billions years. A very deep time in cosmic time frame. Generally human existence on earth is fraction of few seconds considering the universe, our galaxy and the birth of our solar system. Earth is the only planet in our solar system that came to bring life due to its exact location relative to sun, our moon and its 23 degree tilt from its orbital axis. It’s unique and humans are fortunate to find a place in this planet. There is no planet in our solar system where life exists; certainly not multi cellular organism like ourselves. Out of millions of other solar systems in our Milky Way galaxy, earth-like planet certainly exist and may be there is distinct possibility that advance species (probably more advance than humans) inhabit these exoplanets but they are too far for human to travel and to live there. The distance we are talking about is light years which simply means the distance the light travel in one year. Even one light year is too far and often takes up all the digits of your calculator. Numerically it looks like this : = (186282 Miles X 60 Seconds X 60 Minutes X 24 Hours X 365 Days). If you multiply all these you will get the 1 light-year. It’s a large number certainly in distance in miles. Exoplants are located hundreds and thousands of light years from earth. Humans’ only living planet is Earth because with current technology there is no future or long term possibility certainly not within the next 1000 years or so for humans to even reach to half light year let alone landing in our nearest solar system Proxima Centuary located little over four light-years from earth. Why I am telling all these and how these relate to 50th Anniversary of Earth Day? The rationale behind this is simple. Humans must come to realize this is the only planet they have for their survival and if they wish to stay here for another 1 billion years when sun will die and its flares will disintegrate the earth and other planets (in fact you can see some of the other stars are dying when you gaze night sky) like a small crystal jar. It is important for human species to understand that short term pleasure, profit and existing human centric life style (some folks call it death style) governed by greed, shaky moral and ethical dilemma, competitions and running a race where the track is nothing but destination to hell will only lead humans to extinction and that extinction is actually very much right at our front door. This is we call 6th extinction event, the last one was of course 65 millions years ago when Dinosaurs died out and created evolutionary niche for humans to evolve. If humans fail to see earth as part of cosmic system and grasp the broader picture of embracing earth from astronomical time dimensions chances are very likely humans will face extinction within the next 1000 years which again is nothing but fraction of seconds given the earth’s potential to stay in its orbit for one billion years from now. Humans have lot to loose, Earth, well, that is different kettle of fish!
Civet facing human persecution across tropics
Let’s take a brief look how many species are there and how humans are driving species to extinction. Globally there are little over 2.13 million species that have so far been cataloged. This number does not mean this is the total number of species that exist in our planet. Probability estimation suggests between 4 to 50 million species exist on earth and more tangible estimate ballpark it to 16 million species. Nevertheless, out of two million or so species, only 3% are in fact vertebrates (Fishes, Mammals, Amphibians, Reptiles and Birds) including humans of course. The remaining 97% notably comprises insects and plants. The striking chord here is extinction will ensure vertebrates disappear in the face of human assaults to earth.
If you look back cosmic cataclysm even back in the Dinosaurs era, insects survived and so do many other invertebrates. They will continue to stay well beyond mass 6th extinction event that looms over the face of the earth due to anthropogenic interferences. That makes insects more better survivor than humans in cosmic time scale. The ecological fabric on the other hand deeply maintained by large keystone vertebrates that often sits at the top of the food chain. The concept of keystone species underlies that other species survival often determines by maintaining healthy crop of keystone mega vertebrates or species that play as an indicator for the ecosystems. Tigers, wolves, falcons, whales, frogs, pythons and other charismatic and enigmatic species are often the heartbeat of ecosystems. Their numbers are in steep decline and among all of the vertebrates, amphibians (mainly frogs and toads) are most endangered. Almost one third (33%) of all amphibians that are discovered so far, are facing extinction crisis as in endangered or critically endangered (IUCN Data), comparing to less than 20% all all mammals, across the tropical and neotropical belt. Amphibians play massive role both as keystone vertebrate and indicator species and healthy population of frogs simply translates to healthy ecosystems. Agricultural conversion, industrial pesticides, human population encroachments, mono culture cash crop plantations (rubber, palm, teak, coffee etc), aquaculture (shrimp farms decimating almost all the mangrove ecosystems across the hemisphere), wildlife trade, greenhouse gas emissions and many other factors are attributed to earth’s biodiversity loss and species extinction which are driving the planet one step close to 6th mass extinction event as we speak.
Help Save Tiger in the Wild. Image Courtesy: World Wildlife Fund, USA
I conclude this essay with few positive notes. 50 years of environmental and ecological movements since the first inception of Earth Day in the United State in 1970, policies and governance to bring about social and ecological justice are being taking place. In fact majority of the nations adopted conservation measures and action programs following the US Endangered Species Act 1973, three years after the birth of Earth Day! The process is slow and cumbersome although some good work has been done with mixed result. For example, over the last 50 years, iconic tiger numbers from hundred thousands tiger across South and South East Asia plummeted to less than few thousand tigers. With historical population so high to now merely 4000 species left in the wild led significant conservation action programs to revive wild tiger population across the tropical belt. Science driven cutting edge technologies like radio telemetry study, scat sampling, mitochondrial DNA analysis, remote sensing and geographic information science based spatial mapping, camera trapping to estimate tiger population under conceptual statistical framework have led tigers and other wild cats recovery across the globe. Some part of India and Nepal, the good news of tiger numbers are slowly recovering is sense of joy and pride for many of the tireless and often unpaid research ecologists and wildlife biologists who almost dedicated their entire life to help safeguard keystone vertebrates hence to ensure protecting earth’s remaining fragile but precious ecosystems. The latest footage from Panthera, one of the most prestigious and influential wild cat research organization is looking back how it has been for the past 50 years for wild cats conservation by coinciding the 5th anniversary of Earth Day! I leave you to watch that little video clip.
Image Courtesy : World Wide Fund for Nature, Switzerland
Like all its felid cousins, tiger is graceful and awesome creature. It is in fact the largest carnivore in felid guild with its historical population range all the way from Turkey to Russia, Indonesia to Japan, and Iran to Thailand. Sadly, current population size is shrunk to mere 3% and tigers now live in handful of nations in South and South East Asia and Russian Far East. It is classed as endangered species with global population possibly range from 3500 to 3800 tigers that are now facing range of human persecution across tropical and semi tropical biomes. Historically, there were hundred thousands tiger but due to unbridled human population and economic growth and other associated causes, tiger numbers quickly plummeted to less than 4000 by the end of 20th century. Tigers now live in an isolated and fragmented patch mosaics surrounded by expanding human encroachments in the form of agricultural and cash crop mono culture expansions across Asia. In spite of the large scale global consensus to help safeguard the remaining wild tiger population over the past half a century and considerable investments on tiger conservation, wild tigers in their native ecosystems are far from secure footing. To help conserve the dwindling and remaining isolated population of tigers across its range nations, science bound conservation initiatives is more than an ecological imperative, it is an absolute priority.
Image Courtesy: Panthera Tiger Forever Program, New York
In the year 2010, ambitious Global Tiger Recovery Program (GTRP) was initiated by bringing together governments of all tiger range nations and international conservation organizations in St. Petersburg, Russia. This was the most exciting, monumental and largest gathering of international ministerial in conservation conference that ever took place to help recover single endangered species in Asia. The core objective of the GTRP is to double the tiger numbers by year 2022 coinciding with the Chinese New Year referring to Chinese Year of the Tiger. Surely, the GTRP gained enormous momentum both politically and socially and garnered significant recognitions from international conservation groups and forums. Even high profile Hollywood celebrities like Harrison Ford got involve and gave powerful speech at St. Petersburg. The declaration was made and signed by all tiger states which became St. Petersburg Declaration to help safeguard and double the remaining tiger population in the wild. Nine years has gone past since the inception of GTRP and St. Petersburg declaration, yet tigers long term future security is far from reality. One can make an argument that it is all elite and posh to held high profile international conference followed by submission of glossy and chick posters and publications focusing the plight of tigers, but in reality, the tiger numbers continue to decline in dramatic fashion with little over 100 tigers get killed per year across tiger range nations. Therefore, ‘Paper Tiger’ hardly managed to escape from the conference room and Ivory towers thereby failed to became healthy live tiger with secure future in the wild.
Image Courtesy: World Wide Fund for Nature, Gland, Switzerland
Lack of science bound study of tigers and under implementation of ecological science in national conservation policy framework may one of many reasons, tiger range nations are facing serious challenges to stabilize or increase tiger population size. Despite the fact, doubling the tiger numbers is a collective goal and does not translate to individual national goal, all tiger states have agreed to stabilize and make an endeavor to increase tiger population size via St. Petersburg Declaration. This unfortunately has not been achieved in most of the tiger nations except India and Nepal where dedicated and ecologically valid conservation action plans have been undertaken with marked positive outcome. Even in India, which holds over half of the tiger population and which still has millions of square kilometers of suitable tiger habitats, most of the forest are in fact empty forests. It is therefore not surprising that despite over 1.5 million square kilometers of tiger ecosystems exist in South and South East Asia, over 75% of the tigers are in fact living in less than 5% of the areas and under increasing anthropogenic pressures in the form of habitat fragmentation, agricultural expansion, tigers’ essential prey depletion and human encroachment. Doubling the tiger numbers by year 2022 is surely an ambitious goal but to make this goal a reality, standalone political will or emotional plea to save tigers is not good enough. Identifying key conservation areas within the broad heterogeneous patch mosaics of tiger conservation landscape (also known as TCL) is one of many objectives that require dedicated science bound conservation action plan. Considering to the fact that tigers now live in highly insularized and patchy habitat and facing human induced perturbations of all forms, identifying ecologically suitable habitats for tigers where breeding population size stands better chance for long term survival can help reach the target towards doubling tiger population size. In the contrary, where tiger numbers become too small or breeding females are absent, conservation actions and investment in those habitats may pose little significance to increase population size. Other important focus should be interconnecting those breeding areas with nearby forested ecosystems for young tigers to disperse and populate from its source population. This comes under creating source-sink structure and to manage the isolated and fragmented population size within meta-population form within the broad tiger conservation landscape.
Image Courtesy: World Wide Fund for Nature, Beyond the Stripes, Gland, Switzerland
In spite of the fact, scientific study of tigers actually begun in early 1960s by brilliant American wildlife biologist George Schaller and his pioneering work on tigers in Kanha National Park in India was first published in the form of seminal book called ‘The Deer and the Tiger’ in 1967, most of the scientific works on tigers still remain unnoticed by government officials working or in charge of conservation planning and implementation in tiger range nations. Major ecological advances were made by another American carnivore ecologist Melvil Sunquist in the early and mid 70s through radio-telemetry study in Chitwan National Park in Nepal to understand tiger population distribution, its hunting and feeding habit, its reproductive behavior and home range size and other ecological vital information. In the early 90s, Indian wildlife biologist Ullas Karanth and James Nichols (American Wildlife Scientist) pioneered the scientific study of tigers under modern ecological and statistical framework to accurately estimate tiger population size and density by utilizing the power of camera trap capture-recapture modeling method in Southern states of India. Following Karanth’s footsteps wildlife biologists Kae Kawanishi and Monirul Khan reliably estimate the tiger density for the first time in Malaysia and Bangladesh in early this century. We now have wealth of ecologically valid data on tigers: thanks to these pioneering biologists and their associates but ironically it did not help prevent chronic and dramatic decline of tiger numbers across tropical belts. Forty years or more have gone past and tiger conservation certainly entered into the realm of cutting edge statistically valid and ecologically sound modern research framework, yet reaching the target to double the tiger population remain far from reality.
Image Courtesy: World Wide Fund for Nature, Gland, Switzerland.
Armed with forty-years of scientific study of tigers, modern wildlife biologists and conservation ecologists alike from tiger range and non tiger range countries mainly from North America and Western Europe, are jointly collaborating whenever and wherever the opportunity exist to strengthen and build science based ecological conservation of tigers in Asia. Advancements in India and Nepal over the last forty years to help save tigers enabled surrounding nations like Bhutan, Bangladesh and Myanmar to embrace scientific study to understand tiger population and ecology . These nations have made attempt to understand tigers’ demographic parameters within ecologically and statistically valid norm for the past ten years or so. For example, for quarter of century or more, Bangladesh conducted ad hoc study to estimate tiger population by using non scientific methods of several kinds. However, this has now all changed and recent studies were all driven by solid science of ecology, statistics and mathematical modeling. Reliable estimation of tigers in Bangladesh now reveals that tiger population size is in fact four times lower than what was estimated through ad hoc studies over many decades.
Image Courtesy : Panthera, Tiger Forever Program, New York
These latest studies provided us not only with good sets of quality data on demographic parameters and distribution patterns of tiger over spatial and temporal scales covering hundred and thousands of tiger conservation landscape but also revealed great deal of ecological information about tigers that in the past were simply absent. For example, Sunquist and Karanth’s work revealed tigers’ hunting efficiency is by and large 10%. In the surface it may mean little but when put into ecological and conservation perspectives, the percentage can enable wildlife biologists to answer critical ecological questions. Adult individual male tiger require between 2500 kg to 3000 kg of meat per year. Breeding female raising litter of 4-5 cubs needs considerably more meat on the hoof and works out roughly 3500 kg per year. Majority of the tiger habitats are increasingly becoming empty forest where tigers’ prey base remain scarce. On the other hand millions of years of evolution have made tiger as one of the most top-notch landscape species on earth in which it is designed to hunt down large ungulates (hoofed mammals) weigh between 50kg to 1000kg depending on the landscape where these preys and tiger inhabit. To take tigers hunting efficiency into account, if an ecosystem is blessed with 500 healthy deers weighing on average 50kg per individual, an individual adult tiger would then able to hunt down 50 of them per year hence barely meeting the annual energy nutrition budget. Conservation implication of tiger’s hunting efficiency then simply translates to effective management of prey population. In fact, prey population is the critical determinant of long term tiger population viability. Classic landscape predator sitting at the top of the food chain and governing the ecosystem as if prime minister of the nation, cannot be survived, reproduced and repopulated without adequate, regular and healthy supply of nutrients and proteins. Just like lions in Africa cannot live by consuming millions of tons of insects, tigers cannot live by eating smaller prey weighing less than 50 kilograms in tropical Asia. Its all rooted into hunting efficiency and how many prey animals weighing over 50 kg that tiger can kill per year.
Image Courtesy : Gurudeep Ramakrishna
In order for GTRP to become a successful longterm tiger ecology and conservation project with functional objective to double the tiger numbers, ecological study of tiger focusing several key sets of elements are at fundamental and paramount importance. Identifying key conservation areas where at least 10 – 25 breeding population size is present, followed by joining these population by creating effective wildlife corridors (aka dispersal corridors) to increase tiger population dispersal and gene flow will help increase reproductivity, survival chance and population status in the long run. Several wild tiger populations pivoted around with breeding tigers are necessary in this remit. Equally, protecting prey population base at level that meets tigers annual nutrition budget is at critical importance. Annual tiger and its prey survey that embrace science would enable tiger ecologists to effectively monitor demographic patterns over spatial and temporal scales : essentially vital to understand whether conservation actions are in fact helping to increase tiger and its prey base or simply not working. Doubling the tiger numbers largely depends on whether a tiger nation has laid out a tiger conservation action program based on solid science of ecology, wildlife biology, statistical modeling and other interdisciplinary subjects in the field survey to data processing and analysis. Results can then be translated in laymen terms to educate policymakers, local conservation leaders, general public and law makers across tiger nations where probability of long term survival for tiger is relatively high. These in turn will help create sufficient political synergy and power to safeguard this awesome and magnificent animal that is now very near to extinction. George Schaller, who pioneered the scientific study of wild tigers over five decades ago in India, warns us that: “Future generations will be truly saddened, if this century has so little wisdom, compassion, such lack of generosity of spirit, that it eliminates one of the most dramatic animals that has ever lived on this planet.”
Wild tigers (Panthera tigris) are charismatic mega-carnivore in felid guild that serve as flagship keystone species in tropical and semi tropical ecosystems across South and South East Asia. Historically tiger populations range many countries covering as far as Turkey, Uzbekistan and Iran in western Asia to Singapore, Korea, Philippines and most of Southern China in East Asia (see figure 1). Empirical and anecdotal evidence suggest there were over hundred thousands tigers that roam free across broad geographic landscape in the Palearctic and Indo Malaya biogeographic realms over the past hundred years. Sadly, tiger numbers shrank dramatically and 96% of the tigers disappear due to various anthropogenic negative impacts across their once contiguous and broad ecological landscape of Asia. There are probably less than 3800 tigers left in the wild and recent estimate suggests that approximately hundred tigers get killed by poachers every year. Tigers now live in an increasingly human- dominated insularized and fragmented landscape in handful of nations in South and South East Asia and Russian Far East. Habitat encroachment by humans, habitat degradation or agricultural conversion/expansion and habitat fragmentation are some of the leading drivers that pushed tigers into brink of extinction. To reverse these negative trends and to halt tiger population decline, ecoregional based preservation, restoration and habitat connectivity in conjunction with identifying key conservation areas where breeding tiger populations pose high probability of long term survival in heavily fragmented Tiger Conservation Landscapes (TCL) across Indo Malayan ecoregion should be placed at top conservation priority for tiger range nations across tropical and semi tropical belt.
Figure 1 : Historical tiger range across Palearctic ecoregion. GIS Data : World Wildlife Fund, USA
Keystone mega vertebrates for example Mountain Lion (Puma concolor) in North America, Jaguar (Panthera onca) in South America, Lion (Panthera leo) in Africa and Tiger (Panthera tigris) in subcontinent Asia and Russian Far East are classic landscape predator which helps maintaining the overall biodiversity and ecological structure, composition and functions of the ecosystems and biomes in which they inhabit. Recent study on Mountain Lion (aka Cougar, Puma ) population by Mark Elbroch in Greater Yellowstone National Park in United States revealed astonishingly high species diversity in entolomogical, ornithological and mammalogical fronts. Elbroch’s study points out where keystone apex carnivore lives and hunt, their kills alone attract large numbers and high diversity of invertebrates and other vertebrates including birds and mammals in kill sites. Large carnivores often hunt large herbivores often weigh ten time more than their own body weight. Elbroch and his research team found out that Mountain Lion that kills 700 pounds Elk (aka Wapiti) leaves large proportion of the carrion (dead meat) which then become home to significantly high diversity of invertebrates notably beetles, slugs, insects and other entomologically important species. Rotting carcasses attract other carnivores including bears, foxes and wolves at the kill sites. The way Mountain Lion shapes up the ecosystem in North America, it is by some carnivore ecologists, refer to as true ecosystem engineer that help promotes high diversity of species thereby contributing to maintenance and sustainability of the ecological services, functions and significant diversity. Elbroch’s finding is valid for other obligate carnivores in Felid guild for example Jaguars and Tigers. Tigers in tropical and semi tropical Asia often hunts large ungulate (hoofed mammal). For example, in India, tiger prefers to hunt down the largest bovine : The wild Gaur (Bos gaurus). Weigh over 1000 kg, more than three times the weight of Bengal tiger, it is the largest extant (not extinct yet) ungulate in Indo Malayan ecosystems. Although, data on tiger kills focusing large to medium sized ungulates are sporadic and often scarce, it is nonetheless inferred that large kills like Gaur will attracts significantly higher number of other subordinate carnivores, other mammals and birds at the tiger’s kill sites. Therefore, healthy tiger population actively hunting down large ungulates in tropical ecosystems in Asia is true indication of the healthy ecosystems as they shape up the overall structure, diversity, compositions and functions of the ecosystems. It is not surprising that tiger serves as flagship umbrella species in India and other South Asian nations to bring about overall biodiversity conservation. On the other hand, declining population of tigers and the sorry-state-of-this-affairs apparent in tiger range nations are true indication of incremental damage and loss of intact and pristine ecosystems. Elbroch’s study on Mountain Lion kills is by no means limit only to Cougar, in fact this landmark studyand its findings now enable us to give a true name to apex carnivores like Puma and Tigers as classic landscape ecosystem engineer.
In spite of significant ecological (and economic and societal) contributions by tigers, tiger numbers are declining exponentially with severe consequences leading to ecosystem malfunctioning and total breakdown of food-chain where tigers act as top predator. Recognizing the steep and dramatic decline of tiger population across Indo Malayan ecoregion, Global Tiger Recovery Program (GTRP) – the most ambitious and high-level international conservation initiative ever undertaken for single-species recovery in Asia – was launched in year 2010. GTRP was strongly supported and multilaterally embraced by some of the most prestigious international conservation organizations for example IUCN, WWF, Wildlife Conservation Society (WCS) and Smithsonian Institution. The fundamental goal of the GTRP is rooted into doubling the tiger numbers for the next 12 years from year 2010 right till year 2022 by coinciding with the Chinese New Year of the Tiger. The project was fashionably named as Tx2 or TX2 which arithmetically translates to Tiger times 2 hence doubling the tiger population size. In year 2010 when GTRP was launched in the form of St. Petersburg Declaration which then agreed by all 13 tiger range nations along with international conservation groups, tiger numbers were estimated to 3200 across Indo Malayan and Russian Far East ecoregions. Six years later in year 2016, tiger numbers were estimated to 3890 – a 21% increase since GTRP was launched. Doubling the tiger numbers from 3200 to 6400 by year 2022 is surely challenging and ambitious goal considering to the fact that nine years have gone past since the St. Petersburg Declaration and current estimation of tiger population across its range nations is far from reaching Tx2 target. The grim reality is tiger numbers are face with serious anthropogenic threats of various fronts and majority of the tiger nations are in fact loosing their tigers. For example Myanmar (former Burma), Cambodia and Vietnam have not witnessed any breeding population size since 2008. Hence, it can be inferred that these nations have already lost the species or tigers are simply functionally extinct due to the fact that no breeding tigers have been detected for the past 11 years. Countries like China, Thailand, Laos and part of India are facing similar problem where either breeding population has not been detected or population size become too insularized and small that tigers’ chances for long term survival in that particular ecosystem is none therefore the species may be functionally extinct.
Figure 2 : Fragmented Tiger Conservation Landscapes in Indo Malayan Ecoregion as reflected in Green overlay against the historic range of tigers in Asia. GIS Data : World Wildlife Fund (WWF) USA
Politically motivated high level inter-ministerial gathering to help rescue dwindling wild tigers of Asia certainly captured large scale international media coverage focusing GTRP in St. Petersburg in 2010. Tx2 was launched to double the tiger numbers by year 2022, millions of dollars were committed by international conservation groups and donor organizations from across the hemisphere and significantly remarkable numbers of groundbreaking ecological studies have been carried out to understand the demographic parameters and distribution patterns of tigers. Wild tigers entered into the realm of glossy publications and became ‘Paper Tiger’ whilst ‘Wild Tigers’ continue to disappear with a rate of 100 tigers a year due to anthropogenic insults across its range nations. ‘Paper Tigers’ were presented in international symposiums, workshops and conferences over and over to captivate the political, social and scientific momentums prior to and after St. Petersburg Declaration with little or no actual implementations of conservation action plans on the ground to increase tiger population. In spite of all these, large bodies of academic research papers focusing tigers already exist and the booming numbers of conservation organizations (mainly in the west) along with international campaign and media coverage investing on bringing the iconic tigers from near extinction crises are simply an ironic flip side of the same coin against the backdrop of habitat destruction, conversion of virgin tropical tiger ecosystems to monoculture cash crop to meet high demand for oil palm, aquaculture shrimp farms, rubber and teak plantation for the high market demands for western culture.
Figure 2 : GIS based image of heavily fragmented tiger conservation landscapes (TCL) against the background of historical tiger range. GIS Data: Global Forest Watch, World Wildlife Fund and IUCN
Despite the fact 70 million hectares of land that is earmarked as potential Tiger Conservation Landscape (TCL) still exist and three years left to reach Tx2 target by 2022, global tiger population size has not markedly increased. Chances are high that Tx2 target will not be achieved given the timeline therefore question arises with regards to Tx2 in terms of its planning, efficacy, statistical rigor and pragmatic implementation. 70 million hectares of TCL translates to total of 76 tiger conservation landscapes (see figure 2).
Figure 3 : GIS image : Red areas represent tiger presence and yellow areas comprise tiger’s functionally extinct status over the last 10 year. GIS Data : WWF USA, IUCN
These fragmented ecosystems are the last remaining habitats for tigers and other endangered faunas and floras. St. Petersburg Declaration on doubling the tiger numbers hence Tx2 was based on these TCL on figure 2 and out of 76 TCL, 29 of them or 38% of them were further earmarked as high priority TCL for meeting Tx2 target. GIS data on where tigers inhabit in terms of breeding population size and where tigers are functionally extinct that is no tigers were detected since 2008 already exist. Figure 3 delineates the TCLs where tigers are present (red in the map) and where tigers are functionally extinct (yellow in the map) in Indo Malayan ecoregion.
Figure 4 : GIS overlay delineates large swaths of Tx2 areas (blue in the map) where tigers have already functionally extinct hence impossible to double the tiger numbers in these TCLs reflected as blue by year 2022. GIS Data Courtesy : WWF USA and IUCN
Further analysis of GIS data (see figure 4 : All the blue areas are TCLs selected for meeting Tx2 target) on TCL earmarked as Tx2 under GTRP – St. Petersburg Declaration reveals majority of the TCLs to meet the Tx2 target to double the tiger numbers are in fact empty forest when it comes to tiger presence. For example, large swath of ecoregional TCLs straddling the border between Myanmar, Thailand, Cambodia, Vietnam and Laos were selected for doubling the tiger numbers when data reveals that these areas have already lost tigers or tigers are functionally extinct (refer to figure 3) due to small and insularized population size with no presence of breeding females. Therefore it is not surprising that Tx2 target will not be met by year 2022 and the wild tiger will remain as paper tiger in the Chinese Year of the Tiger. After all how can tiger numbers be increased let alone doubling it when no tigers have been detected in majority of the tiger conservation landscape (TCL) that are chosen as Tx2 landscape. One can marshal an argument that so called ambitious Tx2 project initiated with weak foundation where prioritizing key tiger conservation landscapes were left out. On the contrary, pockets of fragmented ecosystems under TCLs with tiger presence still exist (see figure 3 : Red in the map) in southern and central India and in Indonesian island Sumatra. Tx2 failed to select these areas as priority TCLs to increase tiger numbers. Had these areas been earmarked as Tx2 landscape, paper tigers could have stood the chance to escape from conference rooms to become true wild tigers to roam free in Asia. Tiger are true landscape carnivore and it requires large areas (often as large as 100 sq km) for hunting, roaming, breeding and establishing its home range. It poses good reproductive capacity and given adequate prey base and quality habitat, its population can bounce back relatively quick. GIS data reveals large tract of fragmented tiger ecosystems exist in India and Sumatra where tiger presence is confirmed. Connecting these isolated and fragmented ecosystems by creating ecological corridors (aka wildlife corridors) to connect disjunct population for gene flow and confirmed breeding purpose hence managing the source-sink meta population structure of tiger conservation landscape against the backdrop of human-induced negative impacts should be at the top conservation priority for Tx2 to reasonably achieve part of its goal to double the tiger numbers by year 2022.
To raise a cub, mother tiger requires 3500 kg of meat per year. It translates to roughly hundred deer a year for one adult female tiger with cubs.
Tigers are breathtaking high profile landscape carnivore that provokes sheer sense of joy and excitement whenever and wherever one can see them. From historical hundred thousand population to mere 3800 within the last 100 years is true testimony to the fact that species long term survival rate is slim unless ecologically valid science bound conservation action plans are at place in an effective timeline. St. Petersburg Declaration to revive tigers from brink of extinction was popularized and spot-lighted over the last nine years yet tiger numbers continue to decline with limited positive impact of to reach Tx2 target to double the tiger numbers by year 2022. In the face of current anthropogenic impacts that looms over almost all tiger conservation landscapes (TCL), prioritizing the conservation action plans that incorporate GIS based ecological data on tiger presence and absence and to focus on creating ecological corridors to connects fragmented tiger landscapes across Indo Malayan ecoregion are top priorities to meet at least the partial target of Tx2 to double the tiger numbers by year 2022. Conservation focus should be on small isolated pockets of tiger conservation landscapes where tigers’ presence is fully confirmed as oppose to large swath of areas where tiger have not been detected for the past five years. Tx2 goal can only be achieved if it shifts its priority from focusing on areas where tigers have not been sighted for over the past 5 years to areas where tiger presence is 100% confirmed for example southern and central Indian fragmented tiger conservation landscape and Sumatran rainforest.
Connecting Ecological Corridors to Conserve Outstanding Biological Diversity in Indo Malayan Ecoregion : Tiger as Touchstone Umbrella Species!
Mohammed Ashraf
Bengal Tiger as Umbrella Species
In spite of the large scale investment on tiger conservation over the last quarter of a century, tiger numbers continue to decline at dramatic rate. Considerable conservation efforts, initiatives and campaigns both nationally and internationally have been spearheaded with mixed results. In some nations, tiger numbers dropped to near zero with little or no hope for long term survival in the wild. In other nations, population seem to be stabilized and only few nations managed to increase tiger numbers so far. India and Nepal have made good advancement to increase tiger numbers over the last decade or so and governments, civil societies and NGOs of these nations alongside international donor organizations are collaborating to help secure tiger population and its habitats for long term persistence of wild tigers. Since the 2010 Tiger Summit in St. Petersburg in Russia, the first most high-level government meeting for conserving single species in Asia, states of all thirteen nations where tiger population is arguably present, made commitment to help protect tigers in their respective nations through ambitious project called Tx2 which aim to double the tiger numbers from current population of 3900 to 7800 by year 2022 – coinciding with next Chinese Year of the Tiger. It certainly is an ambitious project that came under St. Petersburg Declaration agreed by all the thirteen tiger range states. Three quarter of the time has elapsed since St. Petersburg Declaration with only three years left to double the global wild tiger population, countries have lost tigers, large numbers of tiger habitats across Asia has been converted to mono culture cash crop cultivation, tigers essential prey population has been decimated, forests and grasslands are encroaches and decimated and direct killing of tigers for its body parts, retaliation continued unchecked and unabated. The future of tigers’ survival in the wild looks bleak and pessimistic. In the face of current population status of tigers and considering to the fact that time is ticking to meet St. Petersburg Declaration for Tx2 deadline by year 2022, it is critically important to revitalize our tiger projects that can reflect more holistic approach of tiger conservation where significant potential to approach tiger conservation as key proponent of overall biodiversity conservation should sits right at the heart of all tiger ecology and conservation action plans across Indo-Malayan tiger landscape.
This young transient Bengal tiger was captured in came trap in restored wildlife corridor in Bhutan. Wildlfie corridors play essential role for improving dwindling population size by aiding tigers to disperse from its source pool that are often small protected areas in many parts of Asia. Image courtesy : World Wide Fund for Nature, 2017 Report – Beyond the Stripes
Tigers are truly a high profile landscape predator which require relatively large landscape for hunting, breeding, foraging and for home range establishment. It is a flagship carnivore that has catalyzed significant social and political momentum in the past and often served to raise ecological and conservation education across the hemispheres. Since, its ecological and behavioral attributes are deeply rooted into harnessing the opportunities of large landscape, it is critically important that tiger conservation initiatives focus on safeguarding landscapes that are beyond protected areas where majority of
Tiger Conservation Landscape : These are the only areas where tigers now live against the ongoing anthropogenic disturbances in heavily fragmented ecosystems as indicated in green. GIS Data Source : World Wildlife Fund, Washington D.C. USA.
the tigers now inhabit. In spit of the fact that there are still seventy million hectares of landscape available for tigers across Indo-Malayan biographic ecoregion, over eighty percent of the current tiger population is restricted within protected areas of various sizes. Protected areas lone cannot help secure long term survival of breeding tiger population. For tigers to live this century and beyond, it is essential that landscape corridors that link source population currently residing in protected areas are created and maintained for healthy breeding tigers to disperse and establish their own home range. Sadly, it is often outside of the protected areas where land degradation, agricultural expansion, mining, energy and other anthropogenic disturbances that take place. Creating ecological corridors to connect protected areas will ensure that the entire tiger landscape has been protected. It will significantly enhance ecological diversity and gene flow not only for tigers but also for large suits of species of flora and fauna that share lands with tiger.
Panthera tigris
Tigers are classic keystone umbrella species that help protect multitude of endangered mega fauna including Orangutan and Rhinoceros in tropical and semi tropical ecosystems across South and South East Asia. For example, where critically endangered primate Orangutan (Pongo abelii) and Sumatran Rhino (Dicerorhinus sumatrensis) live, hundred percent of their land overlap with tiger habitats. Over thirty percent of endangered Asian Elephant (Elephas maximus) population falls under tiger landscapes in countries like Bangladesh, India, Nepal, Thailand, Indonesia and Malaysia. Since these species are also endangered and often served as flagship species, conserving tigers simply means, these species receive automatic protection. Hence the word ‘umbrella species’ for tiger conservation has special meaning in terms of bringing about high profile vertebrate conservation management and education across Indo Malayan landscape. Some of the most outstanding and most richest biological assemblages are found in tiger landscapes in Asia. Four Biodiversity Hotspots – the worlds most richest part in terms of biodiversity – lie in Indo Malayan ecoregions and three of these Biodiversity Hotspots are in India and Nepal alone. They cover majority of the tiger landscapes hence conserving tigers not only help protect these critically important global biodiversity hotspots but also help safeguarding astonishingly high numbers of species from all taxa notably mammals, reptiles, amphibians, birds and fishes – the essential components of tropical diversity. The diversity of ecosystems from tall grasslands in Eastern India to Himalayan foothills, the temperate high altitude forests where critically endangered Snow Leopard (Panthera uncia) roams in Nepal to the largest mangrove swamp of Bangladesh where only remaining Bengal tigers live, conserving tiger habitats beyond protected areas through creation, restoration and maintenance of wildlife and ecological corridors for dispersal, gene flow, ecosystem functions is not just for tigers itself but more importantly for multitude of charismatic and enigmatic species that are facing global extinction assaults stemming from human induced disturbances across tropical and semi tropical Asia.
Current tiger range (green) and Tx2 range (red) to double the tiger numbers by year 2022 against the background of historical range of tigers (Panthera tigris). GIS Data Source : World Wildlife Fund (WWF), Washington D.C. USA.
Landscape based tiger ecology and conservation management has been well integrated in many parts of South Asia and its effectiveness to improve tiger population size is well documented in Nepal, Bhutan and India. Fragmented tiger ecosystems in the form of protected areas in India for example simply are not enough, if tigers to survive well beyond this century. Considering to the fact, over 70 million hectares of forests are still available for tigers to disperse through establishment of ecological dispersal corridors, restoration and establishment of landscape corridors will not only help benefits to increase tiger numbers, given adequate protection of course, but will immensely benefits large suits of biologically diverse flora and fauna along with multiple numbers of critically endangered flagship vertebrates like Snow Leopards, Great Indian Hornbills, Indian Rhinoceroses, Asian Elephants, Burmese Pythons, Orangutans, and Sumatran Rhinos to name few. Long term survival of these species in the wild depends on securing long term future for tigers in Asia.
Saving tigers, you get more for your health, livelihood and money!
Mohammed Ashraf
Wild tigers (Panthera tigris) are breathtaking, charismatic and elusive mega vertebrate that now facing anthropogenic assaults across South and South East Asia. This secretive and graceful species once roam all over Asia from Mediterranean ecosystem by the Caspian sea in the west to relatively high latitude far east nations like Korea and Japan. Sadly, three subspecies have gone extinct from the wild over the past hundred years and current extant subspecies number is rounded to five. More so, there were over hundred thousands tiger freely roamed across this vast Asian ecological landscape as early as 1900, but sadly 95% of the tiger habitats is disappeared by the
Historic and Current Range (Green) of Tigers. GIS Data Source : World Wildlife Fund, Washington D.C. USA
turn of the 20th century. The remaining five subspecies of tigers now live in a complex human induced fragmented ecosystems across South and South East Asia and Russian Far East. Tigers are in grave threat and in serous trouble. There are less than 4000 tigers left in the wild and their numbers are declining astronomically purely due to human persecution in various forms for example, habitat encroachment, prey depletion and hunting, agricultural expansion to name few. In spite of the fact tigers provoke sense of pure awe and excitement for millions of people across the world, it is ironic that their population size is pushed to near extinction. The importance of preserving tigers in the wild not just for the sake of doubling tiger population size but more importantly how conserving tiger habitats across tiger range nations can significantly benefits humans and nations’ economy are at the heart of devising in-situ conservation initiatives and public outreach campaign across the hemisphere.
Wild Tiger
96% of the tiger population has gone extinct from the wild over the last century and current estimates indicate there are 3900 wild tigers left across 13 tiger range nations. Recognizing the fact that tigers are in deep trouble and about to go extinct, if concerted efforts to reverse the trend of population decline were not in force, governments of 13 tiger states gathered in St. Petersburg in Russia in year 2010. The most ambitious and challenging project called Tx2 which simply refers to doubling the tiger population size (Tiger times 2 or Tx2) by year 2022 coinciding with the next Chinese year of the tiger, were launched via St. Petersburg Declaration. Governments of these 13 states agreed to the declaration and made commitments to increase tiger population in their respective nations. Nine years have gone past since Tx2 was initiated and the current status and demographic vital signs of tigers across tiger range countries are still long way from secured footing. The negative trend of population decline continues and local population is either gone extinct or become too small to maintain demographically viable breeding population. Habitat destruction coupled with rampant poaching for tiger body parts and skin continue unchecked despite endangered species act and international ban on trade for endangered species under Convention on International Trade in Endangered Species (CITES). The goal to achieve Tx2 hence doubling the tiger numbers from 3900 to 7800 by year 2022 is still not out of our hand but time is ticking. Doubling the tiger number is a collective goal and not directly translates to doubling the tiger number for each individual state . For example, countries like Nepal and Bhutan where Bengal tiger (Panthera tigris tigris) subspecies roam, concerted and dedicated efforts since St. Petersburg declaration in 2010 have been made and tiger population has in fact increased in these nations. India for example harbors over half of the tiger population (over 2000 tigers in India) and Indian government and dedicated wildlife scientists are working hard to stabilize tiger population and restore degraded tiger habitats. Therefore, progress has been made but not all up to the speed and expectation. Countries like Malaysia where subspecies Malayan tiger (Panthera tigris jacksoni) roam, are in grave threat due to large scale agricultural and industrial expansion to boost short term economic benefits. Same applies to Thailand where Indo-Chinese subspecies (Panthera tigris corbetti) are in great danger. Situation on tiger population status is more severe and dire in countries like Laos, Vietnam, Cambodia, China and Myanmar (formerly Burma) where population size of tigers is so low that it is functionally extinct. Indonesian islands of Bali and Java already lost tiger subspecies over the last 50 years or so and only subspecies that is Sumatran tiger (Panthera tigris sumatrae) now roams in the tropical forest ecosystem of Indonesian island called Sumatra. Their numbers are also declining fast due to habitat transformation for mono cultural cash crop notably oil palm, teak, rubber and coffee plantations. Bangladesh boasts the largest mangrove ecosystem called Sundarbans in the world. It is also the only mangrove wetland that harbors tiger population. Despite the vast size of mangrove delta and potentially the largest single-tract contiguous tiger ecosystem in South Asia, it is a paradox that there are less than 200 tigers left in the Bangladesh part of the Sundarbans. Amur tiger (Panthera tigris altaica) population in Russian far east are facing similar anthropogenic disturbances but population seem to be stabilize : thanks to dedicated conservation initiatives and actions that are on place.
Image Courtesy: World Wide Fund for Nature (WWF) – 2017 Report -Beyond the stripes : save tiger, save so much more!
Tigers are an umbrella species meaning saving tigers benefits suits of heterogeneous ecosystems that host exceptionally high biodiversity. Biological diversity aka biodiversity comprises genes, species, population, community, ecosystem, landscape and biosphere which in fact is our planet. Each of this element of biodiversity poses significant benefits to humans. Everything as a human we require comes from ecosystems be it fresh air, clean water, nutrients, medicine to name few. Ecosystem is made up of plants and animals comprising genes, species, population and community. Large landscape hosts several ecosystems and hosts multitude ecological and biological diversity across the tiger landscape. These ecosystems are the heartbeat of human survival. Tigers in South and South East Asia live in these large ecological landscapes comprising tropical and semi tropical forests and tall grasslands, rainforests and mangrove swamps. These are exceptionally rich landscapes due to high diversity of flora (plants) and fauna (animals). The earth’s most richest places in terms of animals and plants are in fact fall into tiger landscapes and these are ecologically termed as Biodiversity Hotspot. Out of 13 tiger range countries, 12 of these nations harbor four biodiversity hotspots where tigers roam. There are 332 Key Biodiversity Areas (KBA) that were identified within tiger landscapes. KBAs are ecosystems with high floral, faunal and ecological diversity and significantly contribute towards global biodiversity persistence in tropical belt. 30% of the tiger landscapes also fall under UNESCO (United Nations Education, Science and Cultural Organization) declared World Heritage Site. These are exceptionally outstanding ecosystem but these ecosystems are unique both in terms of their biodiversity and socio-cultural potential incorporating indigenous community and their ecological wisdom. Preserving tigers that lives in large tiger landscapes in South and South East Asia encompassing Biodiversity Hotspot, KBAs and World Heritage Site not only benefits tigers, but it significantly benefits humans that are intricately connected and depends on these ecosystems for livelihood and survival. For example nine globally important watersheds fall under tiger landscapes in South Asia. These watershed provide clean water to as many as 830 million people. Forests where tiger lives store more carbons than any other forests in Asia hence contributing to mitigate global climate change. 100% of the Orangutan’s and Rhino’s habitats overlaps with tiger landscape in Sumatra therefore preserving tigers simply bring benefits and protection for these endangered vertebrates. Tigers are truly a landscape species and keystone mega vertebrate that brings enormous benefits and opportunity for humans and large number of other species.
Bengal Tigers
Conserving tigers that are now living in dwindling population in large fragmented heterogeneous biodiversity hotspots in Indo Malayan ecoregion translates to astronomical benefits to large suits of biologically diverse species, humans and economy. Between 1997 – 2011 ecosystem loss counted to $20.2 trillion dollars. Investing in tiger conservation in tiger landscapes prevent ecosystem loss because when you conserve tigers, you not only saving tiger as single species, you are in fact preserving part of earth that poses remarkably high biodiversity and ecosystems that people need for their survival in the long run.
“I would stop using the label ‘Project Tiger’ and call it ‘Project Eco-System’. We need to communicate effectively that saving the tiger is not some middle class obsession. It is an ecological imperative — by saving the tiger, you are saving the forests. The tiger is merely the symbol. By saving it, we ensure our water security.”
Jairam Ramesh, former Minister of State for Environment and Forests, India
Global Tiger Day : July 29, 2019 : Hope and Inspiration to Bring Back Tigers from Extinction Crisis!
Mohammed Ashraf
Bengal Tiger in Tall Grassland Ecosystem in South Asian Tiger Landscape, image Courtesy: World Wildlife Fund, USA
29th of July is Global Tiger Day also known as International Tiger Day. We see tigers in various commercial and business facets, from fashion motif to our cereal box. I even remember, Exxon the multinational oil giant once televised ad with a slogan ‘Tiger on your tank”! The sheer power and magnificence of tigers captured corporate attention for decades if not century and tiger symbols or brands got embedded into our modern social and cultural fabric.
Help Save Tiger in the Wild. Image Courtesy: World Wildlife Fund, USA
Despite so much admiration and affection, tigers in the wild are facing global extinction crisis in sheer magnitude. To put this into perspective, as early as 1900, there were over 100,000 tigers used to roam all over Asia, by the turn of century, 95% of the tiger population has disappeared from the wild. Three sub species of tigers (Caspian tiger, Bali tiger, and Javan tiger) have completely gone extinct : Thanks to human persecution across tiger range countries. Shockingly there are only 3900 tigers left in the wild with disproportionate population size across 13 tiger range countries. Among 13 countries, few of the nations like Cambodia, Vietnam and China has population size small enough to class as almost extinct. This is because, once the population size become too small then genetically it is not possible to reverse the declining trend to bring back the species from extinction crisis. This small population size is often known as effective population size which is always smaller than real population size. In other words effective population size means genetically, species are not viable to interbreed hence extinct in the wild.
Tiger Cub : A Hope and Inspiration for Future Generation. Image Courtesy : World Wildlife Fund, USA, Tx2 means Doubling Tiger Number by year 2022.
At the moment, India has the largest tiger population over 2000 tigers in the wild, but that is not surprising because India is the largest landmass among all tiger range countries. Nepal, Bangladesh, Bhutan has small population but governments of these nations are trying to stabilize if not increase the tiger numbers. Russian far east, in an area near Amur river, has roughly 400 tigers. There are tigers in Sumatra and population is declining as we speak.
Tiger numbers at a glance. Image Courtesy: World Wildlife Fund, USA
Hence, the situation for tiger is bleak and saddening. The way, tiger numbers are declining, the species may not survive in the wild next century. I do not like to see that happens and I am sure many of us who grew up with sheer respect and admiration for wild cats, would feel the same. Global tiger day provide us an opportunity to revitalize our spirit to do something, anything to help save tigers in the wild. Individually, we may not have much power, but collectively and globally, we have the power to help conserve tigers in the wild, to restore their forest ecosystem, through education outreach, cultural and social festivals, posters and banners, web pages and blogs and many other ways. To mark the 9th Global Tiger Day, Species Ecology will make an endeavor to do what it can do to help raise awareness and public outreach and conservation education surrounding tigers. I personally plan on writing up essays focusing general information about tigers to scientific studies that have been conducted to help protect this charismatic mega vertebrate that evoke so much of excitement and enlightenment among us. In spite of the fact, tigers are essentially Asian species, I personally feel it is a species we can class it as Global Mega Fauna due to its popularity that does not limit any geo-political boundary. For example, Yosemite National Park in California (first national park in the world), Amazon basin in Brazil and other South America States, Himalaya and its surrounding tiger habitats in Nepal and other South Asian States, Tazmahal in India and Sundarbans mangrove ecosystem (the largest contiguous single tract mangrove forest that harbor wild Bengal tigers in the world) in Bangladesh and Indian part pose no social and or geo political boundaries. These are global ecological assets just like tigers, mountain lion, jaguars and snow leopard as an example. To conclude, I am going to provide you with few basic statistics on how helping to save tigers benefits humans across the globe. This statistics equally apply to any other keystone umbrella species as indicated above.
Bengal Tigers, Image Courtesy: World Wildlife Fund, USA
Tiger landscapes encompass 9 major water sheds in Asia that provide fresh water supply and potable clean drinking water for over 8 million people in Asia.
103 million dollars a year directly generated from tiger tourism in one national park in India. Makes you wonder why live tigers are valuable to society and economy than dead one.
Bengal Tiger in Indian National Park. Image Courtesy : World Wildlife Fund, USA
Large tract of forest protected for tigers host immense biodiversity, birds, mammals, reptiles, fishes, mollusks, invertebrates and trees. Tigers are apex carnivore that sit at the top of the food chain in forest ecosystem. It is a keystone umbrella species meaning helping to conserve tigers not only help tigers and humans but also safeguard suits of biological and ecological diversity that depends on tigers survival. You save tigers, you saving the forest ecosystem in which we humans are intricately related for our own survival.
Finally, forest protected for tigers in Amur region in Russian Far East, can absorb 130,000 tonnes of carbon a year. It works out carbon emission from 25,0000 cars a year. Helping to save tigers and its ecosystems will significantly help curb human induced carbon emission : the main culprit for global warming hence climate change.
Today, April 22, 2019, is Earth Day! To mark the 49th anniversary of this most historically groundbreaking and monumental day, Species Ecology pulled together twelve most influential figures that helped us to shape and hone our ecological and conservation skills against the backdrop of anthropocentric persecution and capitalistic exploitation of our earth and all its natural resources (both renewable and non renewable). In the face of current ecological and social degradation leading the earth into 6th Mass Extinction Event, commemorating these brilliant minds as part of celebrating Earth Day cannot be overemphasized. Without these people, we wouldn’t have achieved biodiversity conservation, national and internal conservation mandates, environmental laws and treaty! These are their stories!
Happy Earth Day
Mohammed Ashraf (Founder)
49th Earth Day : Commemorating Twelve Most Influential Figures
Gaylord Nelson
Gaylord Nelson, Politician and Environmentalist
No other name is more associated with Earth Day than that of Gaylord Nelson (1916-2005). After returning from World War II, Nelson began a career as a politician and environmental activist that was to last the rest of his life. As governor of Wisconsin, he created an Outdoor Recreation Acquisition Program that saved about one million acres of parkland. He was instrumental in the development of a national trails system (including the Appalachian Trail) and help pass the Wilderness Act, the Clean Air Act, and other landmark environmental legislation. He is perhaps best known as the founder of Earth Day, which has become an international celebration of all things environmental.
Theodore Roosevelt
Theodore Roosevelt, Politician and Conservationist
It might surprise some that a famed big-game hunter would make it onto a list of environmentalists, but Theodore Roosevelt (1858-1919) was one of the most active champions of wilderness preservation in history. As governor of New York, he outlawed the use of feathers as clothing adornment in order to prevent the slaughter of some birds. While president of the United States (1901-1909), Roosevelt set aside hundreds of millions of wilderness acres, actively pursued soil and water conservation, and created over 200 national forests, national monuments, national parks, and wildlife refuges.
Henry-David-Thoreau
Henry David Thoreau, Author and Activist
Henry David Thoreau (1817-1862) was one of America’s first philosopher-writer-activists, and he is still one of the most influential. In 1845, Thoreau — disillusioned with much of contemporary life — set out to live alone in a small house he built near the shore of Walden Pond in Massachusetts. The two years he spent living a life of utter simplicity was the inspiration for Walden, or A Life in the Woods, a meditation on life and nature that is considered a must-read for all environmentalists. Thoreau also wrote an influential political piece called Resistance to Civil Government (Civil Disobedience) that outlined the moral bankruptcy of overbearing governments.
Aldo Leopold
Aldo Leopold, Ecologist and Author
Aldo Leopold (1887-1948) is considered by some to be the godfather of wilderness conservation and of modern ecologists. After studying forestry at Yale University, he worked for the U.S. Forest Service. Though he was originally asked to kill bears, cougars and other predators on federal land because of protests from local ranchers, he later adopted a more holistic approach to wilderness management. His best-known book, A Sand County Almanac, remains one of the most eloquent pleas for the preservation of wilderness ever composed.
Edward Abbey
Edward Abbey, Author and Monkey-Wrencher
Edward Abbey (1927-1989) was one of America’s most dedicated — and most outrageous — environmentalists. Born in Pennsylvania, he is best known for his passionate defense of the deserts of America’s Southwest. After working for the National Park Service in what is now Arches National Park in Utah, Abbey wrote Desert Solitaire, one of the seminal works of the environmental movement. His later book, The Monkey Wrench Gang, gained notoriety as an inspiration for the radical environmental group Earth First!which has been accused of eco-sabotage by some, including many mainstream environmentalists.
Rachel Carson
Rachel Carson, Scientist and Author
Rachel Carson (1907-1964) is regarded by many as the founder of the modern environmental movement. Born in rural Pennsylvania, she went on to study biology at Johns Hopkins University and Woods Hole Marine Biological Laboratory. After working for the U.S. Fish and Wildlife Service, Carson published The Sea Around Us and other books. Her most famous work, however, was 1962’s controversial Silent Spring, in which she described the devastating effect that pesticides were having on the environment. Though pilloried by chemical companies and others, Carson’s observations were proven correct, and pesticides like DDT were eventually banned.
John Muir
John Muir, Naturalist and Writer
John Muir (1838-1914) was moved to Wisconsin as a young boy. His lifelong passion for hiking began as a young man when he hiked to the Gulf of Mexico. Muir spent much of his adult life wandering in — and fighting to preserve — the wilderness of the western United States, especially California. His tireless efforts led to the creation of Yosemite National Park, Sequoia National Park and millions of other conservation areas. Muir was a profound influence on many leaders of his day, including Theodore Roosevelt. In 1892, Muir and others founded the Sierra Club “to make the mountains glad.”
Carl Segan
Carl Segan, Astronomer, Astrobiologist, Astrophysicist and Author
Carl Edward Sagan (November 9, 1934 – December 20, 1996) was an American astronomer, cosmologist, astrophysicist, astrobiologist, author, science popularizer, and science communicator in astronomy and other natural sciences. He is best known for his work as a science popularizer and communicator. Sagan published more than 600 scientific papers and articles and was author, co-author or editor of more than 20 books.[3] He wrote many popular science books, such as The Dragons of Eden, Broca’s Brain and Pale Blue Dot, and narrated and co-wrote the award-winning 1980 television series Cosmos: A Personal Voyage. Sagan advocated scientific skeptical inquiry and the scientific method, pioneered exobiology and promoted the Search for Extra-Terrestrial Intelligence (SETI). He spent most of his career as a professor of astronomy at Cornell University, where he directed the Laboratory for Planetary Studies.
E O Wilson
Edward Wilson, Father of Biodiversity
Edward Osborne Wilson (born June 10, 1929), usually cited as E. O. Wilson, is an American biologist, theorist, naturalist and author. His biological specialty is myrmecology, the study of ants, on which he has been called the world’s leading expert. Wilson has been called “the father of sociobiology” and “the father of biodiversity”,for his environmental advocacy, and his secular-humanist and deist ideas pertaining to religious and ethical matters. Among his greatest contributions to ecological theory is the theory of island biogeography, which he developed in collaboration with the mathematical ecologist Robert MacArthur, which was the foundation of the development of conservation area design, as well as the unified neutral theory of biodiversity of Stephen Hubbell.Wilson is the Pellegrino University Research Professor, Emeritus in Entomology for the Department of Organismic and Evolutionary Biology at Harvard University, a lecturer at Duke University and a Fellow of the Committee for Skeptical Inquiry.
Robert MacArthur
Robert MacArthur, Father of Ecology and Ecological Mathematics
Robert Helmer MacArthur (April 7, 1930 – November 1, 1972) was American ecologist who made a major impact on many areas of community and population ecology. MacArthur received his Master’s degree in mathematics from Brown University in 1953.A student of G. Evelyn Hutchinson, MacArthur earned his Ph.D. from Yale University in 1957; his thesis was on the division of ecological niches among five warbler species in the conifer forests of Maine and Vermont. MacArthur was a professor at the University of Pennsylvania, 1958–65, and professor of biology at Princeton University, 1965-72. He played an important role in the development of niche partitioning, and with E.O. Wilson he co-authored The Theory of Island Biogeography (1967), a work which changed the field of biogeography, drove community ecology and led to the development of modern landscape ecology. His emphasis on hypothesis testing helped change ecology from a primarily descriptive field into an experimental field,and drove the development of theoretical ecology. At Princeton, MacArthur served as the general editor of the series Monographs in Population Biology, and helped to found the journal Theoretical Population Biology. He also wrote Geographical Ecology: Patterns in the Distribution of Species (1972). He was elected to the National Academy of Sciences in 1969. Robert MacArthur died of renal cancer in 1972 at age of 42.
George Schaller
George Schaller, Conservation Biologist and Author
George Beals Schaller (born 1933) is a American mammalogist, biologist, conservationist and author. Schaller is recognized by many as the world’s preeminent field biologist, studying wildlife throughout Africa, Asia and South America. He is vice president of Panthera Corporation and serves as chairman of their Cat Advisory Council. Schaller is also a senior conservationist at the Bronx Zoo-based Wildlife Conservation Society. Schaller received his Bachelor of Science degree from the University of Alaska in 1955, and went on to the University of Wisconsin–Madison to obtain his PhD in 1962. In 1959, when Schaller was only 26, he traveled to Central Africa to study and live with the mountain gorillas (Gorilla beringei beringei) of the Virunga Volcanoes. Little was known about the life of gorillas in the wild until the publication of The Mountain Gorilla: Ecology and Behavior in 1963, that first conveyed to the general public just how profoundly intelligent and gentle gorillas really are, contrary to then-common beliefs. Schaller also, in 1964, recounted this epic two-year study in The Year of the Gorilla, which also provides a broader historical perspective on the efforts to save one of humankind’s nearest relatives from the brink of extinction. The American zoologist Dian Fossey, with assistance from the National Geographic society followed Schaller’s ground-breaking field research on mountain gorillas in the Virungas. Schaller and Fossey were instrumental in dispelling the public perception of gorillas as brutes, by demonstrably establishing the deep compassion and social intelligence evident among gorillas, and how very closely their behavior parallels that of humans.
David Brower
David Brower, Environmental Activist
David Brower (1912-2000) has been associated with wilderness preservation since he began mountain climbing as a young man. Brower was appointed the Sierra Club’s first executive director in 1952; over the next 17 years, membership grew from 2,000 to 77,000, and they won many environmental victories. His confrontational style, however, got Brower fired from the Sierra Club — he nonetheless went on to found the groups Friends of the Earth, the Earth Island Institute and the League of Conservation Voters.
You can download the portable document format of this essay by clicking PDF here
Wild Goose
Wildlife ecologists are often interested to find out the parameters that influence the species distribution and population size. These parameters can range from intrinsic ecological factors (for example density dependent population regulation) to extrinsic anthropogenic disturbances (man made caused of greenhouse gas emission). Within this broad spectrum, wildlife ecologists often need to find out the possible underlying trend or mechanism that influence the population parameter of species that are at concern. Lot of wildlife biologists who recently graduated are in a situation where they feel the necessary statistical tools they require to successfully carry out ecological data analyses are absent due to various economic and social factors that are hindering them to access the cutting edge scientific tools and resources. This problem is more intense in developing nations where technical and academic supports are often few and far between due to weak economic and social structure and conditions. For example, both in developed and developing nations, students are often trained to carry out necessary statistical tests under conceptually unified mathematical rigor within the broad spectrum of ecology in general and mathematics in particular. Students are trained to use handful of statistical and mathematical software that they are often introduced in their undergraduate university level education. These software usually range from Minitab, SPSS, JMP, for statistical analyses and MATLAB, Maplin and Maple for mathematical programming. These are commercially lucrative easy-to-use, graphical user interphase (GUI) based high-priced software that students once graduate, struggle to get hold of due to various economic and social factors beyond their control. One of the main factors is these are expensive software which are also closed-sourced meaning one cannot really access the source code (programming codes) to redevelop or reproduce the software or to work with the software in an ultimate freedom. Hence, students, once finish their undergraduate study in wildlife science or ecology, often find it hard to keep up their academic and research study in ecology in general and wildlife science in particular. These in turn affect the overall balance of delivering healthy pool of scientific scholars from biodiversity conservation arena. On the other hand, human existence deeply rooted into sustaining and conservation the remaining biodiversity of our planet. Simply put, if concerted and active (pro active as oppose to retrospective) measures to help conserve (if not preserve) the remaining ecological diversity within the next 25-50 years at top, our planet will simply face doomsday scenario which will eliminate human species in the very blink of our eyes. Considering to the fact, out planet is very old (over 5 billion years old), extinction of human species although pretty apparent in evolutionary time scale, will happen within the next 100 years or so if we fail to curve the species extinction in the face of capitalistic free-market resource consumption and exploitation across the hemispheres.
Geese
Despite the fact that many students from conservation biology related disciplines pose necessary scientific skills, it is unfortunate they they lack necessary technical tools to master and utilize their newly developed analytical skills in ecology due to capitalistic profit-driven market enterprise that only allow the wealthy section of the society to access their products in this case the scientific software that we are about to reveal. However, things have changed and lot of folks now started to boycotting these commercial enterprise and started to write their own source codes hence developing open-source scientific software to conduct their necessary ecological research. Therefore, in this article, I introduce R programming language which is open-source totally free (as often jokingly term as free beer) scientific software that is significantly more powerful and streamlined than any commercial enterprise software that are monopolized and controlled by capitalistic profit driven market tycoons. R can be accessed and installed pretty quick and if you are using UNIX variant operation systems for example Linux or BSD, R (the base R) usually comes with it. Here, I will not discuss the necessary steps one require to access and install R as these information are readily available on the net (use your favorite search engine to download and install R). Instead, I will dive down to the implementation and utilization of R programming language to address ecological datasets that are critically important to help conserve ecological units from genetics to population, from community to landscape level and from ecosystem to the entire planet (commonly known as biosphere or ecosphere).
Mommy goose with her gosling
I am always fascinated by ducks and geese and often interested to know more about their population and what influences their population. Hence I am going to provide you with a simple and clean example of how R (the power of R and things it can do for you are simply infinite and astounding) can help you develop your ecological model based on simple data that you can collect right after finishing your undergraduate study in wildlife ecology or any related disciplines (ecology, conservation biology, landscape ecology and so on). Remember, lack of technical resources due to capitalism is not your problem hence do not let capitalist to stop doing the good things for yourself and more importantly for our planet which needs more conservation scientists than MBA. Recently, I went to mangrove ecosystem of particular tropical estuarine landscape where I was interested to find out how geese population (greylag goose in particular) is influenced by the presence of crow and eagle nests around its vicinity. As we may know, although geese is relatively big bird, it has its fare share of enemy and often eagle and crows are the birds of prey that either kill gosling or severely disturb roosting and grazing habits of geese population. This problem is more phenomenon in tropical mangrove where geese often visit by following their long-haul winter migratory route from temperate and tundra ecosystems as far as Himalaya and Siberia. Here I am interested to see whether their is any possible relationship between number of geese and number of eagle or crow nests. I am also interested to count both male and female geese and how male and female population size are influenced by crow nest within their roosting points.
I collected sample of 49 observation of geese population size over two weeks of ecological survey in mangrove ecosystem. My sampling sites are randomly selected and no sites are repeated to collect data. The total survey area was 100 sq km estuarine mangrove. I first carried out necessary feasibility study to find out how much of an area I can cover to count geese in one fell swoop. Based on my energy and logistic resources, I worked out if I can cover 2 sq km a day, I can then generate fifty, 2-sq-km blocks (50 times 2 equates 100 sq km) to carry out my sampling survey. The block design is critically important. It is pre-requisite for random sampling design in which I must need to ensure each 2-sq-km block posses equal chance of being selected for my survey so that I do not end up choosing any block based on favoritism (as if I do what I want or like, as if ad-hoc study which has no ecological and scientific bearing). Hence each of my 2-sq-km block has probability of (1/20) or 0.05 percent chance of being selected hence will form valid representative of the entire area of 100 sq. km. Its notable to point out that the power of random sampling is very robust therefore it does not really matter how many sample blocks you going to choose to carry out your survey (although one rule of thumb is no less than 10 percent of the total sampling size). However, what does matter is whether you have randomly selected your blocks or not. Therefore, even if I choose to carry out my graylag geese survey on 10 sq km (10 percent of my total 100 sq km sampling area) which works out five 2-sq-km blocks out of total twenty blocks comprising my potential survey unit of 100 sq km, I can still come up with ecologically valid data set with regards to geese population and eagle nests to infer or generalize how the geese numbers are influenced by the eagle nests (you could class this as my working ecological question at this point of time).
Sampling Blocks
Lets do some work on R to start with. I need to choose five random blocks of 2 sq km each from total of 20 blocks that comprise my 100 sq km survey area. Please note, I created a cell block (see the matrix diagram) with each blocked are assigned with serial number starting from 1 and ending with 50.
Sample of randomly selected blocks
I will now ask R to randomly select 5 blocks out of 50 and present me with the set of random five numbers which will be my sampling blocks. I can write a simple code that R will use to generate random five blocks out of 50 from my five by ten (5 rows and 10 columns) matrix dimension and the R code is provided below.
sample ( x= 1 : 50, size = 5, replace = FALSE)
{40 7 5 9 2}
I have written this simple code above hence asked R to generate five random numbers out of 50 hence I can write my sampling block by using set builders notation as such (Pronounced as the set of all between 1 to 50 such that is ). Hence these set of five numbers () are my ecological survey unit comprising total of 10 sq km out of 100 sq km potential survey unit. I have further generated the matrix dimension but this time I have highlighted my random blocks in which I will investigate the grey-leg goose population size and how it relates with eagle and crow nests in or around their roosting/grazing/resting site.
Before we go further, just a quick note on my simple R coding. As you can see, I have asked R to randomly select 5 numbers between 1 to 50 by assigning it as as variable hence . I then assigned R with my sample size which is 5 meaning R will randomly select five blocks out of 50 from my sample matrix. Finally I asked R not to replace the block by writing FALSE. What it means is, by default, R will pick any number between 1 to 50 randomly and then put it back into the system (often known as recycling) but we do not want to select the same number twice hence I asked R not to replace the selected number which in coding term simply works out as replace = FALSE.
Now that I have my blocks randomly selected I can begin my survey work (the fun part). I have visited the blocks every morning and every evening for the past two weeks and collected the data on greylag goose population size. I also collected the data in terms of distribution of greylag goose by gender (male and female goose). I then carried out line transect survey in the same blocks every morning and evening to count eagle and or crow nests in or around the vicinity of grazing/roosting and resting sites of the goose population. My line transects were roughly half a km long although some line transects were a km long due to high density of crow nests in relation to the vicinity of greylag goose population. My dataset is presented below. Can we make anything out of this data? Can we answer few statistically valid ecological questions from this dataset? Possibly not, because dataset is often useless on its own unless we make it meaningful. How we going to gain high level understanding from this freshly collected ecological data on grey-leg goose population in relation to crow/eagle nests? Answer lies in solid command in statistics and harnessing the power of statistical tools and modeling. We will harness the power of statistical tools by utilizing the power of R programming. Hence the remaining part of the essay will focus on R coding to gain high level understanding of out dataset.
When we are presented with dataset of two numerical variables as in the case in my data, we are often interested to find out whether these numerical variables are anyhow relate with each other. Here I am interested to find out whether there is any relationship between number of goose and number of eagle nests. I am also interested to find out whether there is any relationship between male and female goose distribution in relation to eagle/crow nests. Furthermore, I am ecologically motivated to develop a model that will provide statistically valid summery which we can utilize to generalize and make predictions in terms of goose population and eagle nests. Does any of these make sense so far and if so, how we go about it? It’s simple, we let R to answer all these interesting questions. All we gotta do is ask R by writing codes (language) that R can understand. It’s as simple as that.
As I was saying before, when we have two numerical variables (fashionably known as bivariate data), first thing we want to do is create a scatter plot to see at a glance what our data looks like graphically. This would be our first step towards gaining high level understanding of ecological data. I am going to write fairly simple code hence ask R to generate a scatter plot for me. But before we do anything, let me provide you with brief fundamental information with regards to how exactly R plots graphs. Firstly, R is highly powerful and sophisticated mathematical programming language that hosts over 5000 packages. These packages are developed by scientists from various backgrounds ranging from mathematicians to wildlife ecologists, academic scholars to computer programmers. Packages are like a restaurant where you can go and order meal and order various types of meal and enjoy! In R packages are like different restaurant. For example, you can choose to go to Pakistani restaurant to enjoy Pakistani cuisines or Bangladeshi restaurant to enjoy Bangladeshi cuisines. In R, you have packages very similar to your choice of restaurants. You can download and install package that will generate highly sophisticated data rich and powerful graphs for your analytical modeling. You can also install package that will do all the algebraic calculations or solve advance problem focusing calculus and so on. You can also install package that will do cladisitic and principle component analysis and more advance work. You can also install package that will carry out geographic analysis GIS for you. Hence its like going to different restaurant right and there are over 5000 different restaurants (packages) in R town. Making any sense so far? Now, I have also mentioned about going to restaurant ordering your favorite menu. Surely there are many menu to choose from. In R, we call them function hence each package will come with lots of functions that we need to use to write our programs or to instruct R to carry out set of specific numerical and statistical tasks. Hence, package is like restaurant and functions are like menu. Just like if you choose to go to Pakistani restaurant, you are not expecting to order Vietnamese menu right? So if you are working on ggplot2 package of R, you are not expecting to conduct matrix or principle component analysis (PCA) right? What it entails is, set of R functions are grouped together to work for specific package. Although there may be situation where you come across functions (that is menu in a restaurant) are overlapping between one package (package is your restaurant) to another, but generally packages host set of functions to carry out specific mathematical and statistical tasks. I have already indicated one of the package that we going to use to analyze our geese data. This package is called ggplot2 and it will host set of functions that we will utilize to derive high level understanding of our data through insightful graphs. Now that you have some basic background understanding how R packages work alongside with set of functions that come within the package, we can start the analytical part of our ecological study. It’s really a fun part when you learn to harness the power of R coding to gain high level understanding of you hard-earned ecological field data.
As mentioned earlier the first thing I would like do to is, generate a scatter plot to see how two of my variables are laid out. Hence I am interested to see how number of geese are influenced by eagle/crow nest. Scatter plot is really a point graph where we have our eagle/crow nest at x-axes and geese numbers in y-axes. ggplot will do all the job to generate a point corresponding to both and axis for my geese variables. First I load the ggplot2 package and then develop a framework in which I will simply add necessary layers to enrich the plot as we go along. It’s pretty simple. It’s like baking a cake. You make a plain cake and then add necessary toppings from strawberry cream to different flavor of vanilla or chocolate, may be even put ice cream in it too…so the options are unlimited. It’s the same with ggplot. We first ask R to develop the framework and then simply add layers to enrich our graph to gain high level statistical insight.
Now, this is our very basic scatter plot. At quick glance, as we can see, almost all our geese numbers fall between the crow nests that range from . In other words, simply by glancing our scatter plot, we have already gained a valuable information about how our geese numbers are influenced by crow/eagle nests. We can also visualize the fact that there is considerable variation in geese numbers ranging from to within the nesting range of eagle/crow from to . But have you spotted one or two things yet? Have you noticed that our scatter plot actually does not reveal information in terms of gender? Remember I collected data of geese numbers of both male and female geese. So the question I am not curious to know is how male and female geese population is distributed within the crow/eagle nesting range of to . All I am going to do now is, write a simple code in my original framework to instruct R to provide me with gender wise population distribution and the codes are as follows:
geese_plot <- ggplot (geese, aes(eagleCrowNest, numberOfGeese, color = Gender))
geese_plot + geom_point()
Scatter plot color coded
I just typed color equal to gender and ggplot has done the rest. It has pulled together my data variables, matched the variables together to generate points based on gender. It then color coded the gender so that I can visualize the difference of geese numbers based on their gender. How nice and powerful is that? Now, my data is making more sense. Not only I now know that geese numbers do well when eagle nests or less than 2.5 but I also now pin point how female numbers are more sensitive to crow nests as oppose to the male geese. More particularly most of our female geese population do well when there is no crow nest at all. Take a good look at the first column of our scatter plot where you will find more pink dots (female geese) vertically lined up where crow nest in our x-axes is . Interestingly we found only one male geese when crow nest is and rest of them are all females. In our second column we see considerable variation in geese population ranging from as low as to as high as . We do now really know why there is such a high variation in terms of geese numbers but we do know that there are more male geese than female within this population variation. Now, have you spotted something else so far? Have you counted my total observation. I have collected total of 49 sample of geese population from my two-weeks field survey. But, if you count the points, it does not match up. Can you answer why not? It’s cause we may have points that are overlapping with other points meaning they possibly have similar or same number in terms of their population size. Therefore, we need to ask R to disentangle the overlapping of our data point to reveal all our data points in the graph. This hopefully would provide us with more clearer perspective how the population is actually influenced by the eagle nests. Because the position of our data points may have been overlapped, all I will do is write position equal to jitter. What jitter does is it disentangle any observation that overlaps with other. The mathematical procedure that R follows is also pretty simple. R simply assign a random number as reference point for each observation and then based on that reference number it can geometrically disentangle any closest numbers surrounding it. The codes and the output are provided below:
Now this provide all our data points. If you now go ahead and count the points, it should match up to my observation. This also revealed that almost half of our observation was overlapped hence we did not see it from our previous graph. This non overlapping jitter plot now actually revealed full picture of our geese population distribution. We can almost confidently say that female geese population is very sensitive to even small increment of eagle or crow nest. As you can see from the graph that there exist distinctive separation of female population size in terms of eagle/crow nest numbers. Lot of females are almost absent (see the base of the x – axes) even when the crow nest is less than $4$. I still think data are clumped together. Although it has revealed all our data points, by a quick glance we see, some points are still relatively attached to one another and that is due to the size of the point (the circle). What I would like to do now is change the size of the circle so that it provide us with slightly more improve version of our jitter plot. The code and the output are provided below:
geese_plot <- ggplot (geese, aes(eagleCrowNest, numberOfGeese, color = Gender))
geese_plot + geom_point(size = 1.5 , position = “jitter”)
Scatter plot with point size change
Now this looks lot better. Hence this would be our standard scatter plot for further data exploration and analysis. By now you probably started to realize the power of R coding and more precisely the flexibility, freedom and options of writing your own codes to explore, analyze and manipulate data under conceptually unified mathematical and statistical rigor. ggplot is extremely flexible and powerful and if you planning on becoming full blown scientist or academic, regardless of which discipline your study and research focused on, you would be million times better off harnessing the power of R programming language as oppose to commercial profit-driven capitalistic products that you have probably used when you did statistical course at your undergraduate or graduate school.
Before we go ahead carrying out further data analysis based on the scatter plot that ggplot has enabled us to create, did you notice something that we could change at this point. If we look at the labels of the graph in and axis, we could improve it by adding a layer. As mentioned earlier, once you developed your skeleton of the plot by using ggplot command, all we have to do afterwards is continue adding layers to improve our plot. Hence lets improve the label of our plot by simply adding a layer called labs. The command and the improved output of the plot are provided below:
geese_plot <- ggplot (geese, aes(eagleCrowNest, numberOfGeese, color = Gender))
geese_plot + geom_point(size = 1.5 , position = “jitter”) + labs (x = “Number of Eagle/Crow Nests”, y = “Number of Geese”)
Scatter plot with streamlined labels
Now this improved version is obviously reveal more clearer understanding in terms of what our axis and axis represents in terms of our bivariate data variables. Although you may have noticed that I keep typing the backbone code which developed our skeleton:
geese_plot <- ggplot (geese, aes(eagleCrowNest, numberOfGeese, color = Gender)).
However when you you actually working in writing R code, you only have to do it once. After that, you just work on adding layers just like the the way I added labels as one of the layers in our original skeleton which R saved as R object as geese_plot.
Now that we have covered quite a bit in terms of collecting data to data pre-processing and beyond by organizing our data hence to generate scatter plot to make some meaning of our data set by harnessing the power of ggplot in R coding, we will step back a bit and focus on statistical method underpinning our data variables. In this remit, its notable to emphasis the fact that when we work on bivariate datasets, as in our geese datasets, we are often interested in three aspects of our data variables: 1. Scatter plot to get a first hand glance hour our data are behaving hence to make first hand impression of our ecological variables. 2. We then very much interested to determine whether our data is linearly distributed. That is whether our scatter plot looks like it can be fitted with a straight line. This is statistical technique and it is known as regression method. Hence, in our scatter plot, our next job would be to conduct regression analysis. At first glance, it is pretty evident that our dataset is actually not forming a straight line as most of our data points are clustered between 0 to 4 in our axis. Nevertheless, it does open up a question then, what proportion of our data points can be answered through fitted line or as it known as regression line. Regression line is simple a straight line that help us to predict data points within specific range of our original data values. Hence regression line is pretty helpful for making predictions. For example, firstly, I am interested to find out what proportion of our data points can fall into regression line that is if I would have to predict geese number based on crow nest variations across axis, I am then interested to find out what percentage of our data can be explained or predict from the regression line. Do all these making sense? I am not going to go into critical details of statistical mechanism as I intend to provide you with separate treatments of regression analysis by my other articles. But for now, we will simply R to fit a regression line in our scatter plot. Again, the procedure is pretty simple. We will simply add another layer. In R programming, regression line is known as smooth. The rationale behind the name is, it makes our data variables smooth by finding the best fitted line based on all the data points we have in our scatter diagram. Of course, R does not pull this off in thin air…the mathematical procedure R use is rooted into conceptually unified statistical rigor. In other words, R will find the best fitted line based on least squared criterion which is an statistical and algebraic procedure to find the best line that can fit among our data. For now, you do not really need to focus on how this line is derived mathematically as this article is more about appreciating the R programming and it implications on ecological study. Hence, I am going to write a code for adding another layer as smooth and the code and the output are as follows:
geese_plot <- ggplot (geese, aes(eagleCrowNest, numberOfGeese, color = Gender))
geese_plot + geom_point(size = 1.5 , position = “jitter”) + labs (x = “Number of Eagle/Crow Nests”, y = “Number of Geese”)+ geom_smooth(method = “lm”)
Scatter plot with regression line modeled into it
Here we have our linear model and as you can see R has found the best fitted lines both for our male and female geese. Although, as suspected, our lines are not about the data points as most of the data are not really about any of these lines hence it intuitively answers my question that is very small proportion or percentage of our data points can be answered or predict through our best fitted linear model or regression line. Nevertheless, it still provide lot of solid insight. For example, as I was telling you before that our female geese are really super sensitive to eagle or crow nest and a quick glance at our regression lines (red line for the female data points) confirm that. As you may know from elementary geometry, more precisely from your coordinate geometry class that slope of any straight line is defined as ratio of rise and run where rise is the difference between two coordinate points in axis and run is the difference between two points in axis. If you look into our female geese regression line (the red line) we see, its slope is higher (because the red line is lot more steeper) than the blue line representing our male geese. In other words, even though our regression line does not really provide a robust linear model for making ecological predictions, it does however tell us the steepness of the female data points which in turns mean our female geese are extremely sensitive to eagle nests in or around their vicinity. Of course it is expected as females exhibit brooding attributes and strong motherly instinct to protect their eggs and subsequent gosling. Therefore ecological and conservation management implication is to ensure crow nests are removed if our conservation management goal is to help safeguard migratory female geese population in any specific estuarine mangrove ecosystem or freshwater wetlands as an example.
Now, lets ask R to do further improvement of our regression lines. As you may notice, that our regression lines also have shaded area. Firstly what are these shaded areas. Shaded area are actually 95% confidence interval. 95% confidence interval is a statistical measure that enable us to answer in terms of our probability to make predictions from our data points. And not surprisingly, as mentioned earlier, our regression models are pretty weak (small proportion of our data points are about the lines, meaning close to the lines) hence as you can see from the shaded area, we are 95% confident that only a small proportion of our data points can be utilized for making predictions. In other words, most of our data points are actually outside of our shaded area. However, there are overlapping between male and female confidence intervals. The middle portion (slightly more darker) is actually our overlapping proportion of male and female geese data points and this has serious conservation and ecological significance. However, before we do any further analysis, what we like to do is disentangle our common color coding of gray shaded area. Hence we would like to ask R to assign separate color for our female and male confidence intervals. This would then enable us to appreciate the overlapping part better hence would help us to gain high level understanding of overlapped confidence intervals to make robust predictions.
Did you notice this is the first time, I actually brought the option for making prediction based on our weak linear models. Can you tell me why? It is because even though we are only dealing with two variables that is geese numbers and crow nests, we in fact have two groups or levels in our geese data that is male and female geese. Hence we have this overlapped confidence interval with decent proportion of data points comprising male and female within our data range. Therefore as you can see, even a weak regression model can serve us with valuable insights into our data points providing we have grouped (male and female group) scatter plot. Before we gain ecological insight from our grouped overlapped linear model, let’s just write a simple code that will eliminate our gray color and separate our confidence intervals of our male ad female geese population sample. The code and the output are provided below:
geese_plot <- ggplot (geese, aes(eagleCrowNest, numberOfGeese, color = Gender))
geese_plot + geom_point(size = 1.5 , position = “jitter”) + labs (x = “Number of Eagle/Crow Nests”, y = “Number of Geese”)+ geom_smooth(method = “lm”, aes (fill = Gender))
Scatter plot with regression models color coded
Now this is lot better. R has got rid of the gray shaded bits and added distinct colors for both female (pink) and male (light blue) geese reflecting 95% confidence intervals. The middle portion which is overlapped common area is also lot more clearer and it reveals significant data points are in fact overlapped. However, to ensure no data points are hiding under the overlapped color codes, we can actually do better by asking R to lighten the colors so that if any data points that might be hiding behind the colors can be revealed. The code is simple. Under geom_smooth which is our regression line, we will simply incorporate alpha with numeric value to lighten the shaded area in our plot. The magnitude of numeric value in decimal points that alpha can take determines how light or dark you wish your shaded area to be, depending on the modality of your regression analysis of course.I usually stick to decimal range between 0.1 to 0.3 to lighten the shaded area to reveal any data points that me be previously hidden behind dark shadow
geese_plot <- ggplot (geese, aes(eagleCrowNest, numberOfGeese, color = Gender))
geese_plot + geom_point(size = 1.5 , position = “jitter”) + labs (x = “Number of Eagle/Crow Nests”, y = “Number of Geese”)+ geom_smooth(method = “lm”, aes (fill = Gender), alpha = 0.2)
Streamlined and final version of our regression models
Now, surely, this has greatly improved our regression graph and we can clearly see a good deal of our data points can be answered within the overlapped 95% confidence interval. At first glance, we can confidently say that the variation of female geese numbers range from 6 to 9 when there is total absent of crow or eagle nests. Moreover, we are 95% confident to make future prediction that in any particular estuarine mangrove ecosystem, female geese numbers will range between 6 to 9 when predatory bird as such eagle or crow nests are absolute absent. In terms of male geese population, generally speaking, male geese exhibit less sensitivity towards crow nests. Our male geese data points pose considerable variation ranging from 1 to 25 and most importantly within this range, almost all male geese can tolerate predatory birds (crow/eagle) presence that range from 0 to 6. Our data also reveals that we have two extreme observation in which two males show unusual characteristic. In axis we have 25 male geese (extreme observation point) sitting against predatory nests of 5 which although unusual but intuitively it is pretty evident that large numbers of males in a flock are brave enough to tackle predatory presence ranging from 0 to almost 7. On the other hand, although we have witnessed good numbers of our female geese are absent when crow numbers varies from 1 to 12, however, in axis, we see an extreme observation of one male and the only male which is absent when predatory nests range from 0 to 12. In other words, all our male geese were present with variations in numbers of 1 to 25 within the predatory range of 1-12 except one male which is our outlier.
As you may realize that ecological study of any species simply rooted into conceptually unified statistically valid sampling design, followed by sampling bound data collection leading to data analysis by harnessing the power of sophisticated and powerful statistical packages that are at our disposal. In this essay, I demonstrated the power of R programming language by drawing attention from basic ecological study focusing gray leg geese population influence against predatory bird population in estuarine mangrove ecosystem. This study demonstrate the power of R programming by harnessing the statistical tools as such regression model and its implications on ecological and conservation management.
Finally, in this article, I did not attempt on covering the statistical procedures to develop regression line, neither I attempted to provide underlying statistical mechanisms that underpin this study. More precisely, this study is rooted into developing regression equation , followed by estimating coefficient of determination that reflects what proportion of our data can be fitted into regression line and finally calculating the correlation coefficient also known as Pearson coefficient (named in the honor of the developer Karl Person who originally developed the method). These three statistical procedures underlie the study of my geese population and provided the conceptual framework of the essay. In my next essay, I intend to present these statistical methods and the full treatment of its analytic procedures drawing attention from the same datasets of geese population. This essay is primarily intended to serve two purposes: 1. To show the power of R programming language 2. To understand and appreciate ecological study and its close association with statistics and R programming language as powerful and sophisticated mathematical package to answer simple but interesting ecological questions focusing animal population sampling and estimation methods.
This essay is prepared in – the brainchild of Donalnd Knuth, developed by American Mathematical Society (AMS) and created by George Gratzar from University of Manitoba Department of Mathematics. I have also utilized both Python and R Programming Language to develop quadratic population model and for designing random sampling matrix. No commercial software under capitalistic market share is used in preparation of this draft. UNIX variant GNU-Debian Linux is used throughout as core to run all software packages.
The Portable Document Format (PDF) of the article can be downloaded by simply clicking PDF
Cygnus atratus (Black Swans) in wetland
February 02 is World Wetland Day. It may or may not mean much to people who are either too busy focusing on ‘earning money’ hence to use money as their standard yardstick of development when it comes to their personal and career growth or simply not interested on this topic. For many years, wetlands are considered as wastelands and still in many developing nations, wetlands are rapidly transforming into agricultural paddy field or cash farm of shrimp aquaculture in the expense of large scale degradation or complete decimation of this biologically most productive ecosystems on earth. So what is wetlands, how do we distinguish wetlands from other water bodies, what are the benefits of conserving wetlands, what are their international conservation status or designation, who is responsible for maintaining the global database of wetlands, how to access these database, what is the biological and or ecological potential of wetlands comparing to other ecosystems like rain forest or shrub land and what species serve as an ecological indicator and how do we go about measuring these species in order to ensure ecological integrity, functions and the processes of the wetlands are maintained so that we human can continue to receive the vested unconditional ecosystem services e.g. fresh water supply either directly or from ground water, nutrients in the form of fish and other aquatic fauna, shoreline stability, retention of silts hence avoiding coastal erosion and so forth.
In this short essay, I am going to provide some brief background information about wetlands of different types, the importance of wetland conservation to human, and the species that wetland ecologist or limnologist may consider measuring and monitoring as part of implementing the wise use and conservation management of wetland ecosystems.
Mommy goose with her gosling
Let me start by finding out what is not a wetland? A fraction of land that is covered with rain water hence formed a small rainwater pool, is not a wetland. It is not a wetland because the water is not a permanent one and the soil may not be the one that is adapted to water based plant species to grow and thrive on it. Water base species of plants means a selective group of botanically important species that can only grow in soil that are either permanently or seasonally wet but wet, nevertheless, throughout the year. These kind of plants are also know as Hydrophytes or aquatic plants and the soil they grow on is classed as hydric soil. Now that we have some crude idea what is not a wetland, lets just move on finding out what is actually a wetland. Wetland is an ecosystem comprise with hydric soil and hydrophytes. This is possibly the simplest definition to appreciate. Wetlands sometimes are also known as ecotone which refers to a transition inter phase between dry soil and wet soil. For example, mangrove ecosystem is essentially an unique ecotone due to the fact that the wetland within the mangroves is in the transition zone between dry or semi-dry land surface that are regularly and periodically inundated by tidal waves. Dry or semi dry wetland based ecosystems are also known as terrestrial ecosystem although the diversity and the characteristic of floral species may set it apart from other terrestrial ecosystems and the botanical species that would inhabit in this particular kind of wet-terrestrial ecosystem would be predominantly hydrophytes. Strictly speaking, there are four major kinds of wetlands-marsh lands, swamp forest, however not all swamp forests are mangroves, but all mangroves are swamp forest, bog lands and fen lands.
Although, bogs and fens are often collectively known as mires. Below is the list of different types of wetlands that are under various degree of anthropogenic threats.
1.Lakes including oxbow lakes (both man made and natural), 2. Rivers 3. Swamps, 4. Marshes, 5. Peat lands, 6. Bogs 7. Fends 8. tidal flats or also known as mud flats, 9. Estuaries, 10. Oases, 11. Deltas, 12. Wet grasslands, 13. Near shore marine areas, 14. Freshwater Corridors or River Corridors that are often found meandering through path of forest and finally 15. Man made sites such as fish ponds, rice paddies, reservoirs and salt pans.
Geese feeding on wetland
Hence, it is no surprise, that wetlands are one of the most biologically diverse ecosystems on earth. Despite its significant ecological and conservation importance across the globe, wetlands are in peril both in developed and developing nations. This sorry state of affair largely stem from lack of ecological education focusing wetlands of various types as listed above and unscrupulous and eco-ignorant development policy implementation that either overlook integrated ecological based development approach or simply failed to adhere the ‘UN declarations on Sustainable Development’} also known as Rio+ declaration. Generally speaking, ecosystem benefits of wetlands are punishingly downplayed and the integration of both informal and formal ecological education on wetlands and its benefits to human is virtually absent in majority of countries. Here the paradox is wetlands have been received UN ratification in the from of United Nations’ Educational, Social, and Cultural Organization (UNESCO) declared World Heritage Sites, The Convention on Wetlands of International Importance informally known as Ramsar Convention and UN Man and Biosphere Reserve Designation. Despite all these international recognition of the values of wetlands, human seem to remain notoriously indifferent to acknowledge the significance of wetlands. The benefits human receive from healthy wetland ecosystems are enormous. Firstly, wetlands are the heart beat of human survival regime considering our life depends on potable water supply and wetlands’ purify, retain and replenish water table. Without wetlands, there would be no freshwater supply for human and even in 21st century, human has not found a economically feasible way to technologically advance the desalination of marine water for their consumption. Secondly, tropical countries are often most prone to cyclones, tsunami and tidal surges (Cyclone is also known as Hurricane in North America and Typhoon in North East Asia) and considering large number of people both in developing and developed nations are regionally migrating to coastal belts, they are putting themselves in high risk of cyclone induced perturbation. Healthy coastal belts depends on wetlands as it retain soils hence invigorate the coastal lands through soil accretions, silt deposition. Maintaining healthy ecotone for example mangrove ecosystem can shelter millions of people from coastal tidal surges- a re-occurring natural calamity in tropical countries like Bangladesh and India. Thirdly, wetlands help reduce flooding that cost life in tropical developing nations. Wetlands posses an immense biodiversity value and healthy biological diversity is an essential pre-requisite for healthy human welfare and their socio-cultural value-wisdom. Human living in or around large wetlands in tropical belt often are artisan fisher folk communities and their traditional livelihood is intricately entwined with wetlands in terms of harnessing the natural resources from the ecotones and its associated ecosystems. These values have significant anthropological, cultural, religious, economical, ethno-botanical, socio-political and research significance which human will loose if efforts are not made to conserve wetlands across the tropical eco-regions. In other words, the economic justification or the monetary significance of converting the wetlands to urban development or large scale irrigation projects carries very minimal values in the long run than to maintaining a ‘self sustaining’ wetlands and its ecological functions viz-a-viz ecosystem services that human continue to receive from the wetlands and its associated biodiversity.
Wild Goose habitat is pre-dominantly wetlands
So how we go about making sure we are doing the right thing to conserve and manage wetlands. In other words how do we ensure that our current management practice is as such that we can confidently say that our wetlands are healthy, productive ecological unit. One critically important management practice deeply rooted in to the science of ecology-lending mathematically sophisticated tools and integrating them with further powerful tool of geographical information science. Here we will briefly provide the fundamentals of mathematical estimator that if appropriately employed by wetland ecologist for collecting data can serve as baseline index to measure and monitor the health of wetland ecosystems. Wetlands are dominated by hydrophytes. Although there are relatively good number of vascular aquatic plants inhabiting the terrestrial wetlands. However, these woody species need to compete very hard with each other resulting in the local dominance of single or few species through the process of competition. Therefore these species are not necessarily a good indicator of understanding or measuring the health of the wetlands considering their low diversity and richness. Therefore, wetland ecologists often relies on rooted submerged aquatic plants known as macrophytes. Some of these macrophytes are halophytes- a group of submerge aquatic species that grow in high salinity in the water}. Macrophytes in general serve as an ecologically valid indicator species to statistically appraise the health of the wetland ecosystem. In other words, high diversity (number of different species of macrophytes, their proportional abundance, and evenness of the different species) of macrophytes means grater production of algal species, high biomass and lower loss of phosphorus, all signs of a healthy wetlands. The implication from management perspective is, estimating and monitoring the aquatic macrophytes diversity can at least provide us the lower bound of the index measure to detect the overall health of the wetlands. Ecologically speaking, management practice that maintain macrophyte diversity and monitor the diversity index both in spatial and temporal scales, can potentially enhance the ecological functioning and associated services of wetland ecosystems. So how we go about establishing a diversity index focusing macrophyte species. Here I have introduced a diversity estimator and mathematically illustrated it through algebraic simplifications.
Diversity Index
Diversity index is a mathematically valid numeric representation of a value that not only reflects how many different species are there but also simultaneously take into account the evenness that is how equally or (unequally) the types of different species are distributed across the data sample. Here I start with general estimator and algebraically work my way down to come up with suitable diversity estimator that we can employ in our macrophyte diversity estimation in wetlands. Please note this is a very brief mathematical treatment of figuring out the diversity index hence the estimator. For full treatment, please refer to standard ecological literature that are at your disposal.
Here, D is our Diversity Index, q is diversity order, in other words, the value of q can help us to model the estimator in terms of understanding how sensitive our diversity index is that is rare versus abundance species across the species’ proportional abundance in our sample data, is our proportional abundance of th type of species and R is our total number of species. Notice R is actually Species Richness that simply reflects how many total number of different types of species we have found. We now simplify the above equation below:
We continue further algebraic simplification
If we take radical of in both side of the equation, things will start to make more sense:
Now this is simply a raw version of Shannon-Weaver Index, also commonly known as Shannon entropy. Lets trim the equation to make more sense out of it.
We are going to take natural logarithm in both side of our equation in order to bring down our exponents.
We multiply both side of our equation with negative (-) resulting simply a Shannon entropy.
The left hand side of our equation is simply a value of Shannon Diversity Index and can be written as , however, the value of as mentioned earlier can take up any magnitude although, considering to the fact that is our proportional number of species and we are interested to find out the weighted distribution and the richness () in order to enumerate the value of species diversity index that takes both the distribution and evenness into account, therefore, a general rule of thumb in this case would be to consider the value of that would give us a weighted geometric mean across our proportional number of individual type of species in our sample data set. Hence plugging in the value of in our equation results a Shannon Diversity Index Estimator:
Please note the above equation. Shannon index is grounded to the weighted geometric mean of the proportional abundances of the types of species viz-a-viz the species richness , and it equals the logarithm of true diversity as calculated with . We can carry out further simplification of our as shown below:
This can also be written as
Which equals
The final algebraic simplification of the above equation can be written in a succinct form as shown below:
Algebraic simplifications of our original general estimator lead us to workable succinct Shannon-Weaver Diversity Index which if utilized in a conceptually unified and statistically valid sampling framework can produce ecologically correct diversity index of macrophyte species in wetland ecosystems. Therefore conservation management plan, particularly in the developing nations where tropical wetlands are facing grim future, must focus on integrating scientifically valid statistical sampling design- lending necessary mathematical estimator to better appraise the species diversity index. With adequate baseline data on macrophytes both in spatial and temporal scales, conservation managers will be armed with accurate limnological knowledge to detect any changes in the overall functionality of the wetland health hence to adopt sound management prescription that can help maintain macrophyte diversity viz-a-viz enhancing the functioning and associated ecological services of the wetland ecosystems both in tropical and semi tropical belt.
If you look back cosmic cataclysm even back in the Dinosaurs era, insects survived and so do many other invertebrates. They will continue to stay well beyond mass 6th extinction event that looms over the face of the earth due to anthropogenic interferences. That makes insects more better survivor than humans in cosmic time scale. The ecological fabric on the other hand deeply maintained by large keystone vertebrates that often sits at the top of the food chain. The concept of keystone species underlies that other species survival often determines by maintaining healthy crop of keystone mega vertebrates or species that play as an indicator for the ecosystems. Tigers, wolves, falcons, whales, frogs, pythons and other charismatic and enigmatic species are often the heartbeat of ecosystems. Their numbers are in steep decline and among all of the vertebrates, amphibians (mainly frogs and toads) are most endangered. Almost one third (33%) of all amphibians that are discovered so far, are facing extinction crisis as in endangered or critically endangered (IUCN Data), comparing to less than 20% all all mammals, across the tropical and neotropical belt. Amphibians play massive role both as keystone vertebrate and indicator species and healthy population of frogs simply translates to healthy ecosystems. Agricultural conversion, industrial pesticides, human population encroachments, mono culture cash crop plantations (rubber, palm, teak, coffee etc), aquaculture (shrimp farms decimating almost all the mangrove ecosystems across the hemisphere), wildlife trade, greenhouse gas emissions and many other factors are attributed to earth’s biodiversity loss and species extinction which are driving the planet one step close to 6th mass extinction event as we speak. 
![[1 \geq{x} \geq{50} \, x | 40, 7, 5, 9, 2]](https://s0.wp.com/latex.php?latex=%5B1+%5Cgeq%7Bx%7D+%5Cgeq%7B50%7D+%5C%2C+x+%7C+40%2C+7%2C+5%2C+9%2C+2%5D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
(Pronounced as the set of all 
between 1 to 50 such that 
). Hence these set of five numbers (
. I then assigned R with my sample size which is 5 meaning R will randomly select five blocks out of 50 from my sample matrix. Finally I asked R not to replace the block by writing FALSE. What it means is, by default, R will pick any number between 1 to 50 randomly and then put it back into the system (often known as recycling) but we do not want to select the same number twice hence I asked R not to replace the selected number which in coding term simply works out as replace = FALSE. 
axis for my geese variables. First I load the ggplot2 package and then develop a framework in which I will simply add necessary layers to enrich the plot as we go along. It’s pretty simple. It’s like baking a cake. You make a plain cake and then add necessary toppings from strawberry cream to different flavor of vanilla or chocolate, may be even put ice cream in it too…so the options are unlimited. It’s the same with ggplot. We first ask R to develop the framework and then simply add layers to enrich our graph to gain high level statistical insight. 
. In other words, simply by glancing our scatter plot, we have already gained a valuable information about how our geese numbers are influenced by crow/eagle nests. We can also visualize the fact that there is considerable variation in geese numbers ranging from 
to 
within the nesting range of eagle/crow from 
. But have you spotted one or two things yet? Have you noticed that our scatter plot actually does not reveal information in terms of gender? Remember I collected data of geese numbers of both male and female geese. So the question I am not curious to know is how male and female geese population is distributed within the crow/eagle nesting range of 
observation. This also revealed that almost half of our observation was overlapped hence we did not see it from our previous graph. This non overlapping jitter plot now actually revealed full picture of our geese population distribution. We can almost confidently say that female geese population is very sensitive to even small increment of eagle or crow nest. As you can see from the graph that there exist distinctive separation of female population size in terms of eagle/crow nest numbers. Lot of females are almost absent (see the base of the x – axes) even when the crow nest is less than $4$. I still think data are clumped together. Although it has revealed all our data points, by a quick glance we see, some points are still relatively attached to one another and that is due to the size of the point (the circle). What I would like to do now is change the size of the circle so that it provide us with slightly more improve version of our jitter plot. The code and the output are provided below: 
, followed by estimating coefficient of determination that reflects what proportion of our data can be fitted into regression line and finally calculating the correlation coefficient also known as Pearson coefficient (named in the honor of the developer Karl Person who originally developed the method). These three statistical procedures underlie the study of my geese population and provided the conceptual framework of the essay. In my next essay, I intend to present these statistical methods and the full treatment of its analytic procedures drawing attention from the same datasets of geese population. This essay is primarily intended to serve two purposes: 1. To show the power of R programming language 2. To understand and appreciate ecological study and its close association with statistics and R programming language as powerful and sophisticated mathematical package to answer simple but interesting ecological questions focusing animal population sampling and estimation methods. 
– the brainchild of Donalnd Knuth, developed by American Mathematical Society (AMS) and created by George Gratzar from University of Manitoba Department of Mathematics. I have also utilized both Python and R Programming Language to develop quadratic population model and for designing random sampling matrix. No commercial software under capitalistic market share is used in preparation of this draft. UNIX variant GNU-Debian Linux is used throughout as core to run all software packages.
![q_{D}=\frac{1}{\sqrt[q-1]{\sum_{i=1}^{R} p_{i} p_{i}^{q-1}}}](https://s0.wp.com/latex.php?latex=q_%7BD%7D%3D%5Cfrac%7B1%7D%7B%5Csqrt%5Bq-1%5D%7B%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D%7D%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
is our proportional abundance of 
th type of species and R is our total number of species. Notice R is actually Species Richness that simply reflects how many total number of different types of species we have found. We now simplify the above equation below:![q_{\textbf{D}}=\left(\sqrt[q-1]{\sum_{i=1}^{R} p_{i} p_{i}^{q-1}}\right)^{-1}](https://s0.wp.com/latex.php?latex=q_%7B%5Ctextbf%7BD%7D%7D%3D%5Cleft%28%5Csqrt%5Bq-1%5D%7B%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D%7D%5Cright%29%5E%7B-1%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![q_{\textbf{D}}=\left(\left[\sum_{i=1}^{R} p_{i} p_{i}^{q-1}\right]^{\frac{1}{q-1}}\right)^{-1}](https://s0.wp.com/latex.php?latex=q_%7B%5Ctextbf%7BD%7D%7D%3D%5Cleft%28%5Cleft%5B%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D%5Cright%5D%5E%7B%5Cfrac%7B1%7D%7Bq-1%7D%7D%5Cright%29%5E%7B-1%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![q_{\textbf{D}}=\left(\left[\sum_{i=1}^{R} p_{i} p_{i}^{q-1}\right]^{\frac{1}{-(1-q)}}\right)^{-1}](https://s0.wp.com/latex.php?latex=q_%7B%5Ctextbf%7BD%7D%7D%3D%5Cleft%28%5Cleft%5B%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D%5Cright%5D%5E%7B%5Cfrac%7B1%7D%7B-%281-q%29%7D%7D%5Cright%29%5E%7B-1%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
in both side of the equation, things will start to make more sense:![\sqrt[1-q]{q_{D}}=\left(\sqrt[1-q]{\sum_{i=1}^{R} p_{i} p_{i}^{q-1}}\right)^{\frac{1}{1-q}}](https://s0.wp.com/latex.php?latex=%5Csqrt%5B1-q%5D%7Bq_%7BD%7D%7D%3D%5Cleft%28%5Csqrt%5B1-q%5D%7B%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D%7D%5Cright%29%5E%7B%5Cfrac%7B1%7D%7B1-q%7D%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![\sqrt[1-q]{q_{D}}=\sum_{i=1}^{R} p_{i} p_{i}^{q-1}](https://s0.wp.com/latex.php?latex=%5Csqrt%5B1-q%5D%7Bq_%7BD%7D%7D%3D%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![\left[q_{\textbf{D}}\right]^{\frac{1}{-(q-1)}}=\sum_{i=1}^{R} p_{i} p_{i}^{q-1}](https://s0.wp.com/latex.php?latex=%5Cleft%5Bq_%7B%5Ctextbf%7BD%7D%7D%5Cright%5D%5E%7B%5Cfrac%7B1%7D%7B-%28q-1%29%7D%7D%3D%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![\left[q_{D}\right]^{\frac{1}{-(q-1)}}= \sum_{i=1}^{R} p_{i} p_{i}^{q-1}](https://s0.wp.com/latex.php?latex=%5Cleft%5Bq_%7BD%7D%5Cright%5D%5E%7B%5Cfrac%7B1%7D%7B-%28q-1%29%7D%7D%3D+%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![\left(\sqrt[q-1]{q_{\textbf{D}}}\right)^{-1} = \left(\sum_{i=1}^{R} p_{i} p_{i}^{q-1}\right)](https://s0.wp.com/latex.php?latex=%5Cleft%28%5Csqrt%5Bq-1%5D%7Bq_%7B%5Ctextbf%7BD%7D%7D%7D%5Cright%29%5E%7B-1%7D+%3D+%5Cleft%28%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D%5Cright%29&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
in both side of our equation in order to bring down our exponents.![ln \left(\sqrt[q-1]{q_{\textbf{D}}}\right)^{-1} = ln \left(\sum_{i=1}^{R} p_{i} p_{i}^{q-1}\right)](https://s0.wp.com/latex.php?latex=ln+%5Cleft%28%5Csqrt%5Bq-1%5D%7Bq_%7B%5Ctextbf%7BD%7D%7D%7D%5Cright%29%5E%7B-1%7D+%3D+ln+%5Cleft%28%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+p_%7Bi%7D%5E%7Bq-1%7D%5Cright%29&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![-ln \sqrt[q-1]{{q_{\textbf{D}}}} = \sum_{i=1}^{R} p_{i} (q-1) ln p_{i}](https://s0.wp.com/latex.php?latex=-ln+%5Csqrt%5Bq-1%5D%7B%7Bq_%7B%5Ctextbf%7BD%7D%7D%7D%7D+%3D+%5Csum_%7Bi%3D1%7D%5E%7BR%7D+p_%7Bi%7D+%28q-1%29+ln+p_%7Bi%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
![ln \sqrt[q-1]{q_{\textbf{D}}}= -\sum_{i=1}^{R} (q-1) p_{i} ln p_{i}](https://s0.wp.com/latex.php?latex=ln+%5Csqrt%5Bq-1%5D%7Bq_%7B%5Ctextbf%7BD%7D%7D%7D%3D+-%5Csum_%7Bi%3D1%7D%5E%7BR%7D+%28q-1%29+p_%7Bi%7D+ln+p_%7Bi%7D&bg=ffffff&fg=2b2b2b&s=3&c=20201002)
, however, the value of 
as mentioned earlier can take up any magnitude although, considering to the fact that 
) in order to enumerate the value of species diversity index that takes both the distribution and evenness into account, therefore, a general rule of thumb in this case would be to consider the value of 
that would give us a weighted geometric mean across our proportional number of individual type of species in our sample data set. Hence plugging in the value of 
. We can carry out further simplification of our 
Species Ecology 