Human demography and reserve size predict wildlife extinction in West Africa.

Species-area models have become the primary tool used to predict baseline extinction rates for species in isolated habitats, and have influenced conservation and land-use planning worldwide. In particular, these models have been used to predict extinction rates following the loss or fragmentation of natural habitats in the absence of direct human influence on species persistence. Thus, where direct human influences, such as hunting, put added pressure on species in remnant habitat patches, we should expect to observe extinction rates higher than those predicted by simple species-area models. Here, we show that extinction rates for 41 species of large mammals in six nature reserves in West Africa are 14-307 times higher than those predicted by models based on reserve size alone. Human population and reserve size accounted for 98% of the observed variation in extinction rates between reserves. Extinction occurred at higher rates than predicted by species-area models for carnivores, primates and ungulates, and at the highest rates overall near reserve borders. Our results indicate that, where the harvest of wildlife is common, conservation plans should focus on increasing the size of reserves and reducing the rate of hunting.     

Quantifying past and present connectivity illuminates a rapidly changing landscape for the African elephant

There is widespread concern about impacts of land‐use change on connectivity among animal and plant populations, but those impacts are difficult to quantify. Moreover, lack of knowledge regarding ecosystems before fragmentation may obscure appropriate conservation targets. We use occurrence and population genetic data to contrast connectivity for a long‐lived mega‐herbivore over historical and contemporary time frames. We test whether (i) historical gene flow is predicted by persistent landscape features rather than human settlement, (ii) contemporary connectivity is most affected by human settlement and (iii) recent gene flow estimates show the effects of both factors. We used 16 microsatellite loci to estimate historical and recent gene flow among African elephant (Loxodonta africana) populations in seven protected areas in Tanzania, East Africa. We used historical gene flow (F_ST and G'_ST) to test and optimize models of historical landscape resistance to movement. We inferred contemporary landscape resistance from elephant resource selection, assessed via walking surveys across ~15 400 km² of protected and unprotected lands. We used assignment‐based recent gene flow estimates to optimize and test the contemporary resistance model, and to test a combined historical and contemporary model. We detected striking changes in connectivity. Historical connectivity among elephant populations was strongly influenced by slope but not human settlement, whereas contemporary connectivity was influenced most by human settlement. Recent gene flow was strongly influenced by slope but was also correlated with contemporary resistance. Inferences across multiple timescales can better inform conservation efforts on large and complex landscapes, while mitigating the fundamental problem of shifting baselines in conservation.     

Diverse effects of the common hippopotamus on plant communities and soil chemistry

Oecologia - The ecological importance of the common hippopotamus (Hippopotamus amphibius) in aquatic ecosystems is becoming increasingly well known. These unique megaherbivores are also likely to...     

Scent marking in a territorial African antelope: I. The maintenance of borders between male oribi

Scent marking is ubiquitous among the dwarf antelope and gazelles of Africa, but its function has been the subject of debate. This study examined preorbital gland scent marking in the oribi, Ourebia ourebi, a territorial African antelope. Several hypotheses for the function of scent marking by territorial antelope were tested with observational data. Of these, the hypotheses that scent marking is driven by intrasexual competition between neighbouring males, and that marks serve as an honest advertisement of a male's ability to defend his territory from rivals, were supported best. Thirty-three territorial male oribi on 23 territories marked most at borders shared with other territorial males, and territorial males marked more often at borders shared with multimale groups than at borders shared with a single male. This suggests that males perceived neighbouring male groups as a greater threat to territory ownership than neighbouring males that defended their territories without the aid of adult subordinates. Marking rate was unrelated to territory size or the number of females on adjacent territories, but males with many male neighbours marked at higher rates than those with fewer male neighbours. These results suggest that the presence of male neighbours has a greater effect on the scent marking behaviour of territorial antelope than has been considered previously. Copyright 1999 The Association for the Study of Animal Behaviour.     

A Multi-Scale Distribution Model for Non-Equilibrium Populations Suggests Resource Limitation in an Endangered Rodent

Species distributions are known to be limited by biotic and abiotic factors at multiple temporal and spatial scales. Species distribution models, however, frequently assume a population at equilibrium in both time and space. Studies of habitat selection have repeatedly shown the difficulty of estimating resource selection if the scale or extent of analysis is incorrect. Here, we present a multi-step approach to estimate the realized and potential distribution of the endangered giant kangaroo rat. First, we estimate the potential distribution by modeling suitability at a range-wide scale using static bioclimatic variables. We then examine annual changes in extent at a population-level. We define “available” habitat based on the total suitable potential distribution at the range-wide scale. Then, within the available habitat, model changes in population extent driven by multiple measures of resource availability. By modeling distributions for a population with robust estimates of population extent through time, and ecologically relevant predictor variables, we improved the predictive ability of SDMs, as well as revealed an unanticipated relationship between population extent and precipitation at multiple scales. At a range-wide scale, the best model indicated the giant kangaroo rat was limited to areas that received little to no precipitation in the summer months. In contrast, the best model for shorter time scales showed a positive relation with resource abundance, driven by precipitation, in the current and previous year. These results suggest that the distribution of the giant kangaroo rat was limited to the wettest parts of the drier areas within the study region. This multi-step approach reinforces the differing relationship species may have with environmental variables at different scales, provides a novel method for defining “available” habitat in habitat selection studies, and suggests a way to create distribution models at spatial and temporal scales relevant to theoretical and applied ecologists.     

Environmental gradients determine the potential for ecosystem engineering effects

Understanding processes that determine biodiversity is a fundamental challenge in ecology. At the landscape scale, physical alteration of ecosystems by organisms, called ecosystem engineering, enhances biodiversity worldwide by increasing heterogeneity in resource conditions and enhancing species coexistence across engineered and non‐engineered habitats. Engineering–diversity relationships can vary along environmental gradients due to changes in the amount of physical structuring created by ecosystem engineering, but it is unclear how this variation is influenced by the responsiveness of non‐structural abiotic properties to engineering. Here we show that environmental gradients determine the capacity for engineering to alter resource availability and species diversity, independent of the magnitude of structural change produced by engineering. We created an experimental rainfall gradient in an arid grassland where rodents restructure soils by constructing large, long‐lasting burrows. We found that greater rainfall increased water availability and productivity in both burrow and inter‐burrow habitats, causing a decline in local (alpha) plant diversity within both of these habitats. However, increased rainfall also resulted in greater differences in soil resources between burrow and inter‐burrow habitats, which increased species turnover (beta diversity) across habitats and stabilized landscape‐level (gamma) diversity. These responses occurred regardless of rodent presence and without changes in the extent of physical alteration of soils by rodents. Our results suggest that environmental gradients can influence the effects of ecosystem engineering in maintaining biodiversity via resource heterogeneity and species turnover. In an era of rapid environmental change, accounting for this interaction may be critical to conservation and management.     

The effects of small sample size and sample bias on threshold selection and accuracy assessment of species distribution models

Species distribution models are used for a range of ecological and evolutionary questions, but often are constructed from few and/or biased species occurrence records. Recent work has shown that the presence‐only model Maxent performs well with small sample sizes. While the apparent accuracy of such models with small samples has been studied, less emphasis has been placed on the effect of small or biased species records on the secondary modeling steps, specifically accuracy assessment and threshold selection, particularly with profile (presence‐only) modeling techniques. When testing the effects of small sample sizes on distribution models, accuracy assessment has generally been conducted with complete species occurrence data, rather than similarly limited (e.g. few or biased) test data. Likewise, selection of a probability threshold – a selection of probability that classifies a model into discrete areas of presences and absences – has also generally been conducted with complete data. In this study we subsampled distribution data for an endangered rodent across multiple years to assess the effects of different sample sizes and types of bias on threshold selection, and examine the differences between apparent and actual accuracy of the models. Although some previously recommended threshold selection techniques showed little difference in threshold selection, the most commonly used methods performed poorly. Apparent model accuracy calculated from limited data was much higher than true model accuracy, but the true model accuracy was lower than it could have been with a more optimal threshold. That is, models with thresholds and accuracy calculated from biased and limited data had inflated reported accuracy, but were less accurate than they could have been if better data on species distribution were available and an optimal threshold were used.     

Is the Climate Right for Pleistocene Rewilding? Using Species Distribution Models to Extrapolate Climatic Suitability for Mammals across Continents

Species distribution models (SDMs) are increasingly used for extrapolation, or predicting suitable regions for species under new geographic or temporal scenarios. However, SDM predictions may be prone to errors if species are not at equilibrium with climatic conditions in the current range and if training samples are not representative. Here the controversial “Pleistocene rewilding” proposal was used as a novel example to address some of the challenges of extrapolating modeled species-climate relationships outside of current ranges. Climatic suitability for three proposed proxy species (Asian elephant, African cheetah and African lion) was extrapolated to the American southwest and Great Plains using Maxent, a machine-learning species distribution model. Similar models were fit for Oryx gazella, a species native to Africa that has naturalized in North America, to test model predictions. To overcome biases introduced by contracted modern ranges and limited occurrence data, random pseudo-presence points generated from modern and historical ranges were used for model training. For all species except the oryx, models of climatic suitability fit to training data from historical ranges produced larger areas of predicted suitability in North America than models fit to training data from modern ranges. Four naturalized oryx populations in the American southwest were correctly predicted with a generous model threshold, but none of these locations were predicted with a more stringent threshold. In general, the northern Great Plains had low climatic suitability for all focal species and scenarios considered, while portions of the southern Great Plains and American southwest had low to intermediate suitability for some species in some scenarios. The results suggest that the use of historical, in addition to modern, range information and randomly sampled pseudo-presence points may improve model accuracy. This has implications for modeling range shifts of organisms in response to climate change.