Reconsidering priorities for forest conservation when considering the threats of mining and armed conflict.

Many threats to biodiversity can be predicted and are well mapped but others are uncertain in their extent, impact on biodiversity, and ability for conservation efforts to address, making them more difficult to account for in spatial conservation planning efforts, and as a result, they are often ignored. Here, we use a spatial prioritisation analysis to evaluate the consequences of considering only relatively well-mapped threats to biodiversity and compare this with planning scenarios that also account for more uncertain threats (in this case mining and armed conflict) under different management strategies. We evaluate three management strategies to address these more uncertain threats: 1.

A climate adaptation strategy for Mai Po Inner Deep Bay Ramsar site: Steppingstone to climate proofing the East Asian-Australasian Flyway.

The ecological functionality of the East Asian-Australasian Flyway is threatened by the loss of wetlands which provide staging and wintering sites for migrating waterbirds. The disappearance of wetland ecosystems due to coastal development prevents birds from completing their migrations, resulting in population declines, and even an eventual collapse of the migration phenomenon. Coastal wetlands are also under threat from global climate change and its consequences, notably sea level rise (SLR), extreme storm events, and accompanying wave and tidal surges.

Mapping and assessing the impact of small-scale ephemeral water sources on wildlife in an African seasonal savannah.

In many savannah regions of Africa, pronounced seasonal variability in rainfall results in wildlife being restricted to floodplains and other habitats adjacent to permanent surface water in the dry season. During the wet season, rainfall fills small-scale, ephemeral water sources that allow wildlife to exploit forage and other resources far from permanent surface water. These water sources remain difficult to quantify, however, due to their small and ephemeral nature, and as a result are rarely included in quantitative studies of wildlife distribution, abundance, and movement.

Spatial Distribution of Carbon Stored in Forests of the Democratic Republic of Congo.

National forest inventories in tropical regions are sparse and have large uncertainty in capturing the physiographical variations of forest carbon across landscapes. Here, we produce for the first time the spatial patterns of carbon stored in forests of Democratic Republic of Congo (DRC) by using airborne LiDAR inventory of more than 432,000 ha of forests based on a designed probability sampling methodology. The LiDAR mean top canopy height measurements were trained to develop an unbiased carbon estimator by using 92 1-ha ground plots distributed across key forest types in DRC.

Using fragmentation to assess degradation of forest edges in Democratic Republic of Congo.

Background: Recent studies have shown that fragmentation is an increasing threat to global forests, which has major impacts on biodiversity and the important ecosystem services provided by forested landscapes. Several tools have been developed to evaluate global patterns of fragmentation, which have potential applications for REDD+. We study how canopy height and above ground biomass (AGB) change across several categories of forest edges determined by fragmentation analysis.

Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals.

Modelling the species distribution of flat-headed cats (Prionailurus planiceps), an endangered South-East Asian small felid.

Background: The flat-headed cat (Prionailurus planiceps) is one of the world's least known, highly threatened felids with a distribution restricted to tropical lowland rainforests in Peninsular Thailand/Malaysia, Borneo and Sumatra. Throughout its geographic range large-scale anthropogenic transformation processes, including the pollution of fresh-water river systems and landscape fragmentation, raise concerns regarding its conservation status. Despite an increasing number of camera-trapping field surveys for carnivores in South-East Asia during the past two decades, few of these studies recorded the flat-headed cat.