The use of habitat suitability models and species-area relationships to predict extinction debts in coastal forests, South Africa

Adaptive variation in the upper limits of avian body temperature

Physiological performance declines precipitously at high body temperature (T_b), but little attention has been paid to adaptive variation in upper T_b limits among endotherms. We hypothesized that avian maximum tolerable T_b (T_bmax) has evolved in response to climate, with higher T_bmax in species exposed to high environmental heat loads or humidity-related constraints on evaporative heat dissipation. To test this hypothesis, we compared T_bmax and related variables among 53 bird species at multiple sites in South Africa with differing maximum air temperature (T_air) and humidity using a phylogenetically informed comparative framework. Birds in humid, lowland habitats had comparatively high T_bmax (mean ± SD = 45.60 ± 0.58 °C) and low normothermic T_b (T_bnorm), with a significantly greater capacity for hyperthermia (T_bmax - T_bnorm gradient = 5.84 ± 0.77 °C) compared with birds occupying cool montane (4.97 ± 0.99 °C) or hot arid (4.11 ± 0.84 °C) climates. Unexpectedly, T_bmax was significantly lower among desert birds (44.65 ± 0.60 °C), a surprising result in light of the functional importance of hyperthermia for water conservation. Our data reveal a macrophysiological pattern and support recent arguments that endotherms have evolved thermal generalization versus specialization analogous to the continuum among ectothermic animals. Specifically, a combination of modest hyperthermia tolerance and efficient evaporative cooling in desert birds is indicative of thermal specialization, whereas greater hyperthermia tolerance and less efficient evaporative cooling among species in humid lowland habitats suggest thermal generalization.

Species-landscape interactions drive divergent population trajectories in four forest-dependent Afromontane forest songbird species within a biodiversity hotspot in South Africa

Species confined to naturally fragmented habitats may exhibit intrinsic population complexity which may challenge interpretations of species response to anthropogenic landscape transformation. In South Africa, where native forests are naturally fragmented, forest-dependent birds have undergone range declines since 1992, most notably among insectivores. These insectivores appear sensitive to the quality of natural matrix habitats, and it is unknown whether transformation of the landscape matrix has disrupted gene flow in these species. We undertook a landscape genetics study of four forest-dependent insectivorous songbirds across southeast South Africa. Microsatellite data were used to conduct a priori optimization of landscape resistance surfaces (land cover, rivers and dams, and elevation) using cost-distances along least-cost pathway (LCP), and resistance distances (IBR). We detected pronounced declines in effective population sizes over the past two centuries for the endemic forest specialist Cossypha dichroa and Batis capensis, alongside recent gene flow disruption in B. capensis, C. dichroa and Pogonocichla stellata. Landscape resistance modelling showed both native forest and dense thicket configuration facilitates gene flow in P. stellata, B. capensis and C. dichroa. Facultative dispersal of P. stellata through dense thicket likely aided resilience against historic landscape transformation, whereas combined forest-thicket degradation adversely affected the forest generalist B. capensis. By contrast, Phylloscopus ruficapilla appears least reliant upon landscape features to maintain gene flow and was least impacted by anthropogenic landscape transformation. Collectively, gene flow in all four species is improved at lower elevations, along river valleys, and riparian corridors- where native forest and dense thicket better persist. Consistent outperformance of LCP over IBR land-cover models for P. stellata, B. capensis and C. dichroa demonstrates the benefits of wildlife corridors for South African forest-dependent bird conservation, to ameliorate the extinction debts from past and present anthropogenic forest exploitation.

Selective extinctions resulting from random habitat destruction lead to under-estimates of local and regional biodiversity loss in a manipulative field experiment

Land-use change is a significant cause of anthropogenic extinctions, which are likely to continue and accelerate as habitat conversion proceeds in most biomes. One way to understand the effects of habitat loss on biodiversity is through improved tools for predicting the number and identity of species losses in response to habitat loss. There are relatively few methods for predicting extinctions and even fewer opportunities for rigorously assessing the quality of these predictions. In this paper, we address these issues by applying a new method based on rarefaction to predict species losses after random, but aggregated, habitat loss. We compare predictions from three rarefaction models, individual-based, sample-based, and spatially clustered, to those derived from a commonly used extinction estimation method, the species-area relationship (SAR). We apply each method to a mesocosm experiment, in which we aim to predict species richness and extinctions of arthropods immediately following 50% habitat loss. While each model produced strikingly accurate predictions of species richness immediately after the habitat loss disturbance, each model significantly underestimated the number of extinctions occurring at both the local (within-mesocosm) and regional (treatment-wide) scales. Despite the stochastic nature of our small-scale, short-term, and randomly applied habitat loss experiment, we found surprisingly clear evidence for extinction selectivity, for example, when abundant species with low extinction probabilities were extirpated following habitat loss. The important role played by selective extinction even in this contrived experimental system suggests that ecologically driven, trait-based extinctions play an equally important role to stochastic extinction, even when the disturbance itself has no clear selectivity. As a result, neutrally stochastic null models such as the SAR and rarefaction are likely to underestimate extinctions caused by habitat loss. Nevertheless, given the difficulty of predicting extinctions, null models provide useful benchmarks for conservation planning by providing minimum estimates and probabilities of species extinctions.

Monitoring Mining Disturbance and Restoration over RBM Site in South Africa Using LandTrendr Algorithm and Landsat Data

Considering the negative impact of mining on ecosystems in mining areas, the South African government legislated the Mineral and Petroleum Resources Development Act (No. 28 of 2002), to compel mining companies to restore the land affected by mining. Several studies have used remotely sensed data to observe the status and dynamics of surface mines. Advances in remote sensing along the cloud-based Google Earth Engine (GEE) now promise an enhanced observation strategy for improved monitoring of mine environments. Despite these advances, land rehabilitation at Richards Bay Minerals (RBM) is mainly restricted to field-based approaches which are unable to reveal seamless patterns of disturbance and restoration. Here, we illustrate the value of the trajectory-based LandTrendr algorithm in conjunction with GEE for mine rehabilitation studies. Our automated method produced disturbance and recovery patterns (1984–2018) over the RBM site. The study revealed that RBM has progressively been mining different portions of the mineral-rich coastal area after which restoration was undertaken. The duration of mining over each site ranged from 2 to 6 years. The LandTrendr outputs correspond with independent reference datasets that were classified with an overall accuracy of 99%; it captures mine-induced disturbance efficiently and offers a practical tool for mine restoration management.

Forest floor temperature and greenness link significantly to canopy attributes in South Africa's fragmented coastal forests

Tropical landscapes are changing rapidly due to changes in land use and land management. Being able to predict and monitor land use change impacts on species for conservation or food security concerns requires the use of habitat quality metrics, that are consistent, can be mapped using above-ground sensor data and are relevant for species performance. Here, we focus on ground surface temperature (Thermal_ground) and ground vegetation greenness (NDVI_down) as potentially suitable metrics of habitat quality. Both have been linked to species demography and community structure in the literature. We test whether they can be measured consistently from the ground and whether they can be up-scaled indirectly using canopy structure maps (Leaf Area Index, LAI, and Fractional vegetation cover, FCover) developed from Landsat remote sensing data. We measured Thermal_ground and NDVI_down across habitats differing in tree cover (natural grassland to forest edges to forests and tree plantations) in the human-modified coastal forested landscapes of Kwa-Zulua Natal, South Africa. We show that both metrics decline significantly with increasing canopy closure and leaf area, implying a potential pathway for upscaling both metrics using canopy structure maps derived using earth observation. Specifically, our findings suggest that opening forest canopies by 20% or decreasing forest canopy LAI by one unit would result in increases of Thermal_ground by 1.2 °C across the range of observations studied. NDVI_down appears to decline by 0.1 in response to an increase in canopy LAI by 1 unit and declines nonlinearly with canopy closure. Accounting for micro-scale variation in temperature and resources is seen as essential to improve biodiversity impact predictions. Our study suggests that mapping ground surface temperature and ground vegetation greenness utilising remotely sensed canopy cover maps could provide a useful tool for mapping habitat quality metrics that matter to species. However, this approach will be constrained by the predictive capacity of models used to map field-derived forest canopy attributes. Furthermore, sampling efforts are needed to capture spatial and temporal variation in Thermal_ground within and across days and seasons to validate the transferability of our findings. Finally, whilst our approach shows that surface temperature and ground vegetation greenness might be suitable habitat quality metric used in biodiversity monitoring, the next step requires that we map demographic traits of species of different threat status onto maps of these metrics in landscapes differing in disturbance and management histories. The derived understanding could then be exploited for targeted landscape restoration that benefits biodiversity conservation at the landscape scale.

Novel predators and anthropogenic disturbance influence spatio-temporal distribution of forest antelope species

Understanding the effects of anthropogenic disturbance on species' behaviour is crucial for conservation planning, considering the extent of habitat loss. We investigated the influence of anthropogenic disturbances including agriculture, urbanisation, protected areas, and the presence of novel predators, on the temporal and spatial behaviour of sympatric forest antelope (Tragelaphus scriptus, Philantomba monticola, Sylvicapra grimmia, and Cephalophus natalensis) in an anthropogenic matrix containing forest fragments in the Indian Ocean Coastal Belt of South Africa. We integrated land-use types with camera-trap data and compared activity patterns using circular statistics and occupancy modelling. Antelope species overlapped in temporal and spatial distribution and exhibited diurnal activity for 50% of the time. All species exhibited nocturnal activity for ∼25-33% of all observations, except for C. natalensis. Nocturnal activity varied between species and land-use types. The predators Canis familiaris, C. mesomelas and Caracal caracal negatively influenced occupancy of P. monticola, S. grimmia and C. natalensis. Humans negatively influenced temporal activity of P. monticola, and spatial distribution of T. scriptus and S. grimmia. C. familiaris had an overall negative influence on S. grimmia. We found spatial, and to a lesser extent temporal, segregation between species. However, plasticity in activity patterns existed, which varied in response to anthropogenic effects and novel predators.

Creation of forest edges has a global impact on forest vertebrates

Forest edges influence more than half of the world's forests and contribute to worldwide declines in biodiversity and ecosystem functions. However, predicting these declines is challenging in heterogeneous fragmented landscapes. Here we assembled a global dataset on species responses to fragmentation and developed a statistical approach for quantifying edge impacts in heterogeneous landscapes to quantify edge-determined changes in abundance of 1,673 vertebrate species. We show that the abundances of 85% of species are affected, either positively or negatively, by forest edges. Species that live in the centre of the forest (forest core), that were more likely to be listed as threatened by the International Union for Conservation of Nature (IUCN), reached peak abundances only at sites farther than 200-400 m from sharp high-contrast forest edges. Smaller-bodied amphibians, larger reptiles and medium-sized non-volant mammals experienced a larger reduction in suitable habitat than other forest-core species. Our results highlight the pervasive ability of forest edges to restructure ecological communities on a global scale.

Pattern or process? Evaluating the peninsula effect as a determinant of species richness in coastal dune forests

The peninsula effect predicts that the number of species should decline from the base of a peninsula to the tip. However, evidence for the peninsula effect is ambiguous, as different analytical methods, study taxa, and variations in local habitat or regional climatic conditions influence conclusions on its presence. We address this uncertainty by using two analytical methods to investigate the peninsula effect in three taxa that occupy different trophic levels: trees, millipedes, and birds. We surveyed 81 tree quadrants, 102 millipede transects, and 152 bird points within 150 km of coastal dune forest that resemble a habitat peninsula along the northeast coast of South Africa. We then used spatial (trend surface analyses) and non-spatial regressions (generalized linear mixed models) to test for the presence of the peninsula effect in each of the three taxa. We also used linear mixed models to test if climate (temperature and precipitation) and/or local habitat conditions (water availability associated with topography and landscape structural variables) could explain gradients in species richness. Non-spatial models suggest that the peninsula effect was present in all three taxa. However, spatial models indicated that only bird species richness declined from the peninsula base to the peninsula tip. Millipede species richness increased near the centre of the peninsula, while tree species richness increased near the tip. Local habitat conditions explained species richness patterns of birds and trees, but not of millipedes, regardless of model type. Our study highlights the idiosyncrasies associated with the peninsula effect-conclusions on the presence of the peninsula effect depend on the analytical methods used and the taxon studied. The peninsula effect might therefore be better suited to describe a species richness pattern where the number of species decline from a broader habitat base to a narrow tip, rather than a process that drives species richness.

Evidence and mapping of extinction debts for global forest-dwelling reptiles, amphibians and mammals

Evidence of extinction debts for the global distributions of forest-dwelling reptiles, mammals and amphibians was tested and the debt magnitude was estimated and mapped. By using different correlation tests and variable importance analysis, the results showed that spatial richness patterns for the three forest-dwelling terrestrial vertebrate groups had significant and stronger correlations with past forest cover area and other variables in the 1500 s, implying the evidence for extinction debts. Moreover, it was likely that the extinction debts have been partially paid, given that their global richness patterns were also significantly correlated with contemporary forest variables in the 2000 s (but the absolute magnitudes of the correlation coefficients were usually smaller than those calculated for historical forest variables). By utilizing species-area relationships, spatial extinction-debt magnitudes for the three vertebrate groups at the global scale were estimated and the hotspots of extinction debts were identified. These high-debt hotspots were generally situated in areas that did not spatially overlap with hotspots of species richness or high extinction-risk areas based on IUCN threatened status to a large extent. This spatial mismatch pattern suggested that necessary conservation efforts should be directed toward high-debt areas that are still overlooked.