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Tiger occupancy in Ratapani landscape: What is the reason behind tiger presence in proximity of capital Bhopal, Madhya Pradesh, India?

XV World Forestry Congress, 2-6 May 2022









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    Bovine trypanosomosis in the Upper West Region of Ghana: Entomological,parasitological and serological cross-sectional surveys 2011
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    Baseline surveys were conducted in the Upper West Region of Ghana to assess the distribution and densities of tsetse species, as well as the prevalence of bovine trypanosomosis. The entomological survey was designed to cover the suitable tsetse habitats along the three main rivers in the study area (i.e. Black Volta, Kulpawn and Sissili). Results indicated the presence of Glossina tachinoides in all three river basins, whilst Glossina palpalis gambiensis was only found close to the south ern limit of the study area. A random sampling of 1800 cattle of the West African Short Horn, Sanga and Zebu breeds from 36 randomly selected grid cells covering the study area showed substantial differences between parasitological and serological prevalences. The average parasitological prevalence was estimated at 2.5% (95% CI: 1.06– 5.77) with the majority of the infections due to Trypanosoma vivax. Most of the infected cattle were found close to the major river systems. The serologi cal prevalence, measured using Enzyme Linked Immunosorbent Assay (ELISA), test was 19% (95% CI: 14.03–25.35). Cattle with anti-trypanosomal antibodies were also found throughout the study area.
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    A strategic reassessment of fish farming potential in Africa 1998
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    The present study is an update of an earlier assessment of warm-water fish farming potential in Africa, by Kapetsky (1994). The objective of this study was to assess locations and areal expanses that have potential for warm-water and temperate-water fish farming in continental Africa. The study was based on previous estimates for Africa by the above author, and on estimates of potential for warm-water and temperate-water fish farming in Latin America by Kapetsky and Nath (1997). However, a nu mber of refinements have been made. The most important refinement was that new data allowed a sevenfold increase in resolution over that used in the previous Africa study, and a twofold increase over that of Latin America (i.e. to 3 arc minutes, equivalent to 5 km x 5 km grids at the equator), making the present results more usable in order to assess fish farming potential at the national level. A geographical information system (GIS) was used to evaluate each grid cell on the basis of severa l land-quality factors important for fish-farm development and operation regardless of the fish species used. Protected areas, large inland water bodies and major cities were identified as constraint areas, and were excluded from any fish farming development altogether. Small-scale fish farming potential was assessed on the basis of four factors: water requirement from ponds due to evaporation and seepage, soil and terrain suitability for pond construction based on a variety of soil attributes a nd slopes, availability of livestock wastes and agricultural by-products as feed inputs based on manure and crop potential, and farm-gate sales as a function of population density. For commercial farming, an urban market potential criterion was added based on population size of urban centres and travel time proximity. Both small-scale and commercial models were developed by weighting the above factors using a multi-criteria decision-making procedure. A bioenergetics model was incorporated int o the GIS to predict, for the first time, fish yields across Africa. A gridded water temperature data set was used as input to a bioenergetics model to predict number of crops per year for the following three species: Nile tilapia (Oreochromis niloticus), African catfish (Clarias gariepinus) and Common carp (Cyprinus carpio). Similar analytical approaches to those by Kapetsky and Nath (1997) were followed in the yield estimation. However, different specifications were used for small-scale and co mmercial farming scenarios in order to reflect the types of culture practices found in Africa. Moreover, the fish growth simulation model, documented in Kapetsky and Nath (1997), was refined to enable consideration of feed quality and high fish biomass in ponds. The small-scale and commercial models derived from the land-quality evaluation were combined with the yield potential of each grid cell for each of the three fish species to show the coincidence of each land-quality suitability class with a range of yield potentials. Finally, the land quality-fish yield potential combinations were put together to show where the fish farming potential coincided for the three fish species. The results are generally positive. Estimates of the quality of land show that about 23% of continental Africa scored very suitable for both small-scale and commercial fish farming. For the three fish species, 50-76% of Africa's land has the highest yield range potential, and the spatial distribution of th is yield is quite similar among the species and farming systems. However, the spatial distribution of carp culture potential was greater than for Nile tilapia and African catfish. Combining the two farming system models with the favourable yields of the three fish species suggest that over 15% of the continent has land areas with high suitability for pond aquaculture.
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    The number of forest- and tree-proximate people
    A new methodology and global estimates
    2022
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    Mapping the spatial relationship between forests, trees and the people that live in and around them is key to understanding human-environment interactions. First, quantifying spatial relationships between humans and forests and trees outside forests can help decision-makers develop spatially explicit conservation and sustainable development indicators and policies to target priority areas. This study combined tree cover and human population density data to map the spatial relationship between forests, trees and people on a global scale providing estimates of the number of forest-proximate people and tree-proximate people for 2019. The methodology relies on spatial overlays that combine global-scale remotely sensed data on tree cover (as a proxy for forest cover) and gridded human population data to identify people that live in or close to forests and trees. Evidence on the number and spatial distribution of people living within or near forests and trees outside forests may, therefore, support decision-makers to 1) target projects in priority areas; 2) prioritize among alternative sites; 3) reduce the cost of achieving environmental or socio-economic objectives; 4) improve the effectiveness of monitoring, including by estimating the numbers of people who will be affected or have been affected as a result of an intervention, or affected by biophysical changes to forests (e.g. deforestation, fire or floods); and/or 5) more effectively and assuredly reaching target populations.

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