As the biodiversity crisis continues there is a need to measure the loss of habitat and species. So far, investments in protected area (PA) or community based conservation initiatives have had limited success. In Kenya, protected areas constitute an impressive 12.3% of its designated land, yet the majority of these PAs are too small to maintain viable populations of threatened wildlife with large home ranges. The Greater Mara Ecosystem (GME) in southern Kenya covers 6,000km2, consisting of the Masai Mara National Reserve (MMNR) and 10 surrounding group ranches. In response to the need to simultaneously improve both wildlife conservation and local livelihood prospects alike, DICE, Friends of Conservation and the Massai developed, implemented and ran a community driven scout programme that was supported by the Darwin Initiative. From 2004-2006, some 74 Maasai scouts monitored the abundance and population trends of 26 wildlife species across the GME. This M.Sc. dissertation focused on four species, wild dog (Lycaon pictus), lion (Panthera leo), elephant (Loxondata africana) and zebra (Equus burchelli), that vary in their vulnerability to the different threat types across the GME. Fixed transect surveys were conducted to record focal species encounter rates thereby determining the population trends over two years. Non-fixed transects were also conducted to record encounter rates of threat types. Binary logistic regression analyses were performed to investigate the spatio-temporal physical variables and threat variables influencing focal species population trends and presence. The final models identified population trend and abundance patterns for elephant and lion populations, and abundance patterns only for wild dogs. Declines in elephant abundance were located in areas with lower retribution killings of crop pests and medium levels of bushmeat poaching. Declines in lion abundance were located in areas with medium threat levels in retribution of livestock predators and in areas closer to the MMNR border. Finally, wild dogs, which have suffered large scales declines over the past 30 years, were present in the wet and dry season in areas with high elevation and only the wet season in areas closer to rivers. This study aims to understand the variables affecting vulnerable species to enable future conservation programmes to the target key areas and reduce the decline of wildlife across the GME. The study also aims contribute to a wider understanding of patterns and causes of species decline across similar bioregions.
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... Elephants play an important ecological role in savannahs and forest ecosystems in maintaining suitable habitats for numerous animal species (Stephenson, 2007). Their habit of stripping bark from trees and pulling down trees to access fodder modifies vegetation dynamics and plays a fundamental role in the creation of savannah-woodland mosaics (Richmond, 2006). As pointed out by Osborne (2012), the loss of elephant habitat and subsequent home range in priority areas is a cause for concern and is caused by agricultural expansion into elephant habitat. ...
The Maasai Mara Landscape (MML) supports one of the richest wildlife populations remaining on earth but over the last century, has experienced transformation notably through conversion of former rangelands into croplands. Elephants have both temporal and spatial requirements, which if not provided, render them vulnerable to the land-use practices. The study assessed land use and vegetation cover changes that have occurred and their effects on the elephant movements and distribution within the MML using an integrated methodological approach. The analysis revealed changes in land use and land cover classes over a period of 20 years for the three epochs, from 1997, 2007 and 2017. Elephant’s distribution has been restricted to areas of high vegetation densities within specific habitats hence accelerating the rate of habitat destruction and degradation due to their high densities. These changes have drastically reduced forage for elephants necessitating them to travel longer distances out of their home range in search for food. Human beings have caused land use and cover changes which have detrimental impacts on the ecosystem and ecosystem services.
Keywords: land use change, land cover changes, Maasai Mara Landscape, elephant distribution, home range.
Most attempts to identify important areas for biodiversity have sought to represent valued features from what is known of their current distribution, and have treated all included records as equivalent. We develop the idea that a more direct way of planning for conservation success is to consider the probability of persistence for the valued features. Probabilities also provide a consistent basis for integrating the many pattern and process factors affecting conservation success. To apply the approach, we describe a method for seeking networks of conservation areas that maximize probabilities of persistence across species. With data for European trees, this method requires less than half as many areas as an earlier method to represent all species with a probability of at least 0.95 (where possible). Alternatively, for trials choosing any number of areas between one and 50, the method increases the mean probability among species by more than 10%. This improvement benefits the least-widespread species the most and results in greater connectivity among selected areas. The proposed method can accommodate local differences in viability, vulnerability threats, costs, or other social and political constraints, and is applicable in principle to any surrogate measure for biodiversity value.
GIS-based measurements that combine native raster and native vector data are commonly used in environmental assessments. Most of these measurements can be calculated using either raster or vector data formats and processing methods. Raster processes are more commonly used because
they can be significantly faster computationally than vector, but error is introduced in converting vector data to raster. This conversion error has been widely studied and quantified, but the impact on environmental assessment results has not been investigated. We examined four GIS-based
measurements commonly used in environmental assessments for approximately 1000 watersheds in the state of Maryland and Washington, D.C. Each metric was calculated using vector and raster methods, and estimated values were compared using a paired t-test, Spearman rank correlation, and cluster
analyses. Paired t-tests were used to determine the statistical significance of quantitative differences between methods, and Spearman rank correlation and cluster analyses were used to evaluate the impact of the differences on environmental assessments. Paired t-test results indicated significant
quantitative differences between methods for three of the four metrics. However, Spearman ranks and cluster analyses indicated that the quantitative differences would not affect environmental assessment results. Spearman rank correlations between vector and raster values were greater than
0.98 for all comparisons. Cluster analyses resulted in identical assignment for 88 percent to over 98 percent of watersheds analyzed among vector and various raster methods.
The aim of this text is to provide an up-to-date understanding of the Serengeti-Mara ecosystem in East Africa, home to one of the largest and most diverse populations of animals in the world. Building on the groundwork laid by "Serengeti: Dynamics of an Ecosystem", published in 1979 by the University of Chicago Press, this work integrates studies of the ecosystem at every level, from the plants at the bottom of the visible food chain to the many species of herbivores and predators, as well as the system as a whole. Drawing on data from long-term studies, the contributors examine the processes that have produced the Serengeti's biological diversity, with its species-species and species-environment interactions. The book also discusses computer modelling as a tool for exploring these interactions, employing it to test and anticipate the effects of social, political and economic changes on the entire ecosystem and on particular species, with the aim of assisting the development of future conservation and management strategies.
Ecological variables often fluctuate synchronously over wide geographical areas, a phenomenon known as spatial autocorrelation or spatial synchrony. Development of statistical approaches designed to test for spatial autocorrelation combined with the increasing accessibility of long-term, large-scale ecological datasets are now making it possible to document the patterns and understand the causes of spatial synchrony at scales that were previously intractable. These developments promise to foster significant future advances in understanding population regulation, metapopulation dynamics and other areas of population ecology.
Turkey has three major bio-geographical regions namely Euro-Siberian, Mediterranean and Irano-Turanian. There are very different types of ecosystems such as agricultural, mountain, forests, steppes and wetlands, as well as coastal and marine. The country has rich floral and faunal diversity, high endemism and wide genetic diversity. A good progress has been made in protecting nature and biodiversity rich areas. Since 1990, the extent of protected areas has almost doubled to reach 7.2% of the territory. There are 40 national parks, 31 nature conservation areas, 107 natural monuments, 184 nature parks, 81 wildlife reserve areas, 58 conservation forests, 239 genetic conservation areas, 373 seed stands, 15 specially protected areas, 1273 natural sites, 14 Ramsar sites and 1 biosphere reserve. In this paper information on different ecosystems of the country is presented.
Natural Connections is the first systematic analysis of community based conservation, a people driven, bottom up approach to conservation which makes local communities the beneficiaries and custodians of conservation efforts. It includes a comprehensive examination of detailed cases from around the world and provides an overview of CBC in the context of the debate over sustainable development, poverty and environmental decline. It also reviews issues arising from CBC programs and an agenda for future action.
Wildlife resources under the protective custodianship of skilled managers can thrive and sustain important revenues. Such custodianship is generally lacking among communal rural societies in Africa because of land use policies that overlook the capacity and the practical importance of actively engaging these societies in wildlife management. In Zambia participation by local village communities in this management is recognized as a prerequisite for wildlife development and conservation. This participation is permitted through the administrative management design (called ADMADE) for game management areas. To help improve the capacity of rural communities to become more knowledgeable and effective in managing their wildlife resources, a geographical information system (GIS), based on ARC/INFO software, was applied and tested as an appropriate technology. It was hypothesized that maps composed of easily recognizable information about land use issues affecting the welfare of local residents and their natural resources would facilitate communal societies to make technically improved land use decisions with broad-based support within the community. Results offered a growing set of achievements in land use planning by local community leaders in support of this hypothesis. Custom designed maps produced by this technology were used by these leaders to explain and build consensus at the community level on ways to resolve resource use conflicts. Results also demonstrated the pragmatic and cost-effective value of training local residents to participate in the collection of GIS data as a way of making maps more locally acceptable and better focused on relevant issues and needs.