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. Our goal was to map ephemeral water in Bwabwata National Park in Namibia using two different approaches and to relate measures of ephemeral water to the abundance, distribution, and movement of two large wildlife species. We used high-resolution Google Earth and Esri World imagery to visually identify waterholes. Additionally, we used Sentinel-2 satellite imagery to map ephemeral water across the study area using the Normalized Difference Water Index. With these mapped waterhole layers and data from GPS-collared individuals of African elephant (Loxodonta africana) and African buffalo (Syncerus caffer), we evaluated the importance of ephemeral water in conditioning abundance and movement of these two species. The two approaches to mapping ephemeral water resulted in the visual identification of nearly 10,000 waterholes, and a predicted ephemeral water layer of ~76% accuracy. The inclusion of ephemeral water into models of abundance and movement resulted in improved goodness of fit relative to those without water, and water impacts on abundance and movement were among the strongest of all variables considered. The potential importance of ephemeral water in conditioning the movements and distributions of large herbivores in African savannahs has been difficult to quantify relative to vegetation drivers. Our results suggest research into ephemeral water impacts deserves more attention.

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. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun­scene­sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun­scene­sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P < 0.001) across a wide range of AGB levels from 26 Mg/ha to 460 Mg/ha, and was confirmed by cross validation. A high-resolution biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies.

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. to ignore them; 2. avoid them; or 3. specifically target actions towards them, first individually and then simultaneously to assess the impact of their inclusion in spatial prioritisations. We apply our approach to the eastern Democratic Republic of the Congo (DRC) and identify priority areas for conserving biodiversity and carbon sequestration services. We found that a strategy that avoids addressing threats of mining and armed conflict more often misses important opportunities for biodiversity conservation, compared to a strategy that targets action towards areas under threat (assuming a biodiversity benefit is possible). We found that considering mining and armed conflict threats to biodiversity independently rather than simultaneously results in 13 800-14 800 km2 and 15 700-25 100 km2 of potential missed conservation opportunities when undertaking threat-avoiding and threat-targeting management strategies, respectively. Our analysis emphasises the importance of considering all threats that can be mapped in spatial conservation prioritisation.

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. The impacts of SLR are compounded by coastal subsidence and decreasing sedimentation, which can result from coastal development. Thus, important wetlands along the flyway should be assessed for the impacts of climate change and coastal subsidence to plan and implement proactive climate adaptation strategies that include habitat migration and possibility of coastal squeeze. We modelled the impacts of climate change and decreasing sedimentation rates on important bird habitats in the Mai Po Inner Deep Bay Ramsar site to support a climate adaptation strategy that will continue to host migratory birds. Located in the Inner Deep Bay of the Pearl River estuary, Mai Po's tidal flats, coastal mangroves, marshes, and fishponds provide habitat for over 80,000 wintering and passage waterbirds. We applied the Sea Level Affecting Marshes Model (SLAMM) to simulate habitat conversion under two SLR scenarios (1.5m and 2.0m) for 2050, 2075, and 2100 for four accretion rates (2mm/yr, 4 mm/yr, 8 mm/yr, 15 mm/yr). The results showed no discernible impact to habitats until after 2075, but projections for 2100 show that the mangroves, marshes and tidal flats could be impacted in almost all scenarios of SLR and accretion. Under a 1.5m SLR scenario, even at low tide, if accretion levels decrease to 4 mm/yr, the tidal flats will be inundated and with a 2 mm/yr accretion the mangroves will also be inundated. Thus, important shorebird habitats will be lost. During high tide the ponds inside the nature reserve, which are intensively managed to provide high tide roosting sites and other habitats for waterbirds, will also be inundated. Thus, with a 1.5m SLR and declining sedimentation the migratory shorebirds will lose habitat, including the high tide roosting habitats inside the nature reserve. The model also indicates that the fishponds further inland in the Ramsar site will be less impacted. Most fishponds are privately owned and could be developed in the future, including into high rise apartments; thus, securing them for conservation should be an important climate change adaptation strategy for Mai Po, since they provide essential habitats for birds under future climate change scenarios. But Mai Po is only one steppingstone along the EAAF, and hundreds of other wetlands are also threatened by encroaching infrastructure and climate change. Thus, similar analyses for the other wetlands are recommended to develop a flyway-wide climate-adaptation conservation strategy before available options become lost to wetland conversion.

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. LiDAR samples provided estimates of mean and uncertainty of aboveground carbon density at provincial scales and were combined with optical and radar satellite imagery in a machine learning algorithm to map forest height and carbon density over the entire country. By using the forest definition of DRC, we found a total of 23.3 ± 1.6 GtC carbon with a mean carbon density of 140 ± 9 MgC ha-1 in the aboveground and belowground live trees. The probability based LiDAR samples capture variations of structure and carbon across edaphic and climate conditions, and provide an alternative approach to national ground inventory for efficient and precise assessment of forest carbon resources for emission reduction (ER) programs.

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. We use Democratic Republic of Congo (DRC) as an example. RESULTS: An analysis of variance of different edge widths and airborne estimated canopy height found that canopy heights were significantly different in forest edges at a distance of 100 m from the nonforest edge. Biomass was significantly different between fragmentation classes at an edge distance of 300 m. Core forest types were found to have significantly higher canopy height and greater AGB than forest edges and patches, where height and biomass decrease significantly as the level of fragmentation increases. A change analysis shows that deforestation and degradation are increasing over time and biomass loss associated with degradation account for at least one quarter of total loss. We estimate that about 80 % of primary forests are intact, which decreases 3.5 % over the 15 year study period, as primary forest is either deforested or transitioned to forest edge. While the carbon loss per hectare is lower than that of deforestation, degradation potentially affects up to three times more area than deforestation alone. CONCLUSIONS: When defining forest degradation by decreased biomass without any loss in forest area, assessing transitions of core forest to edges over time can contribute an important element to REDD+MRV systems. The estimation of changes between different forest fragmentation types and their associated biomass loss can provide an estimate of degradation carbon emission factors. Forest degradation and emissions due to fragmentation are often underestimated and should comprise an essential component of MRV systems.

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. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we designed a predictive species distribution model using the Maximum Entropy (MaxEnt) algorithm to reassess the potential current distribution and conservation status of the flat-headed cat. Eighty-eight independent species occurrence records were gathered from field surveys, literature records, and museum collections. These current and historical records were analysed in relation to bioclimatic variables (WorldClim), altitude (SRTM) and minimum distance to larger water resources (Digital Chart of the World). Distance to water was identified as the key predictor for the occurrence of flat-headed cats (>50% explanation). In addition, we used different land cover maps (GLC2000, GlobCover and SarVision LLC for Borneo), information on protected areas and regional human population density data to extract suitable habitats from the potential distribution predicted by the MaxEnt model. Between 54% and 68% of suitable habitat has already been converted to unsuitable land cover types (e.g. croplands, plantations), and only between 10% and 20% of suitable land cover is categorised as fully protected according to the IUCN criteria. The remaining habitats are highly fragmented and only a few larger forest patches remain. CONCLUSION/SIGNIFICANCE: Based on our findings, we recommend that future conservation efforts for the flat-headed cat should focus on the identified remaining key localities and be implemented through a continuous dialogue between local stakeholders, conservationists and scientists to ensure its long-term survival. The flat-headed cat can serve as a flagship species for the protection of several other endangered species associated with the threatened tropical lowland forests and surface fresh-water sources in this region.