new publication: Mapping Bushmeat Hunting Pressure in Central Africa

new publication: Mapping Bushmeat Hunting Pressure in Central Africa

Biotropica_Ziegler_Fa_Wegmann_bushmeat_hunting_pressure_2016

Hunting pressure modelled for Central Africa (Biotropica link)

Our analysis on mapping bushmeat hunting pressure in Africa based on various co-variates, such as land cover, is now available online. Is is related to our article in NATURE Scientific Reports.

Hunting and trade of wild animals for their meat (bushmeat), especially mammals, is commonplace in tropical forests worldwide. In West and Central Africa, bushmeat extraction has increased substantially during recent decades. Currently, such levels of hunting pose a major threat to native wildlife. In this paper, we compiled published data on hunting offtake of mammals, from a number of studies conducted between 1990 and 2007 in Cameroon, Central African Republic, Democratic Republic of Congo, Equatorial Guinea, Gabon, and Republic of Congo. From these data sources, we estimated annual extraction rates of all hunted species and analyzed the relationship between environmental and anthropogenic variables surrounding each hunting rate and levels of bushmeat extraction. We defined hunting pressure as a function of bushmeat offtake and number of hunted species and confirm that hunting pressure is significantly correlated with road density, distance to protected areas and population density. These correlations are then used to map hunting pressure across the Congo Basin. We show that predicted risk areas show a patchy distribution throughout the study region and that many protected areas are located in high-risk areas. We suggest that such a map can be used to identify areas of greatest impact of hunting to guide large-scale conservation planning initiatives for central Africa.

 

Stefan Ziegler, John E. Fa, Christian Wohlfart, Bruno Streit,Stefanie Jacob and Martin Wegmann (2016) Mapping Bushmeat Hunting Pressure in Central Africa. Biotropica. http://onlinelibrary.wiley.com/doi/10.1111/btp.12286/abstract

MSc by Asja Bernd: “Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data”

MSc by Asja Bernd: “Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data”

AsjaBernd_MSc_GlobalChangeEcology_org_2015_resizedeast_africa_af_areaThe MSc thesis by Asja Bernd titled “Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data” is handed in. Very interesting results on global grassland fragmentation. Read the abstract:

Around the world, grassland and savannah ecosystems are under intense anthropogenic use, yet research has not given them much attention. One significant threat is fragmentation, reducing habitat connectivity and hindering species dispersal. Using MODIS land cover data from 2012, combined with infrastructure data derived from VMAP0 and OpenStreetMap, I assessed the fragmentation of grasslands on a global scale. The metrics applied were patch size, distance to the euclidean nearest neighbour and number of neighbours per patch. To quantify the contribution of human pressure to fragmentation, the results were correlated with the Human Influence Index and human population density. For subsets, selected from the Global 200 Ecoregions, I analysed land cover data from 2001 and 2012 to determine
trends over time. Globally, grasslands are highly fragmented by infrastructure, which reduced patch size by more than 50 %, and significantly increased isolation. Human pressure seems to act as a driver of fragmentation, diminishing patch size and the number of neighbours, while increasing the distance to neighbours. For the subsets, results varied, but two of three metrics indicated an increase in fragmentation between 2001 and 2012. In the face of declining migrations of terrestrial mammals and increasing human pressure, a better understanding of the effects of fragmentation is needed to develop adequate management and protection strategies.

Supervisor: Prof. Neil Burgess and Dr. Martin Wegmann

new article: forest mapping in South-East Asia

new article: forest mapping in South-East Asia

our new article “Mapping threatened dry deciduousdipterocarpforest in South-east Asia for conservation management” by Christian Wohlfart, Martin Wegmann and Peter Leimgruber got just published. This article was a result of Christians MSc thesis which was conducted in cooperation with the Smithsonian Conservation Biology Institute (SCBI) within the Global Change Ecology MSc. study program. This study is highly valuable for ongoing research projects in the region and Peter is using it for explaining animal distributions.Wohlfart_Wegmann_Leimgruber_2014_dry_tropical_forest

Habitat loss is the primary reason for species extinction, making habitat conservation a critical strategy for maintaining global biodiversity. Major habitat types , such as lowland tropical evergreen forests or mangrove forests, are already wellrepresented in many conservation priorities, while others are underrepresented. This is particularly true for dry deciduous dipterocarp forests (DDF), a key forest type in Asia that extends from the tropical to the subtropical regions in South-eastAsia (SE Asia), where high temperatures and pronounced seasonal precipitation patterns are predominant. DDF are a unique forest ecosystem type harboring a wide range of important and endemic species and need to be adequately represented in global biodiversity conservation strategies. One of the greatest challenges in DDF conservation is the lack of detailed and accurate maps of their distribution due to inaccurate open-canopy seasonal forest mapping methods. Conventional land cover maps therefore tend to perform inadequately with DDF. Our study accurately delineates DDF on a continental scale based on remote sensing approaches by integrating the strong, characteristic seasonality of DDF. We also determine the current conservation status of DDF throughout SE Asia. We chose SE Asia for our researchbecause its remaining DDF are extensive in some areas but are currently degrading and under increasing pressure from significant socio-economic changes throughout the region. Phenological indices, derived from MODIS vegetation index time series, served as input variables for a Random Forest classifier and were used to predict the spatial distribution of DDF. The resulting continuous fields maps of DDF had accuracies ranging from R² = 0.56 to 0.78. We identified three hotspots in SE Asia with a total area of 156,000 km2, and found Myanmar to have more remaining DDF than the countries in SE Asia. Our approach proved to be a reliable method for mapping DDF and other seasonally influenced ecosystems on continental and regional scales, and is very valuable for conservation management in this region.

link to the OpenAccess article: Tropical Conservation Science Vol.7 (4):597-613, 2014