High variability in patterns of population decline: the importance of local processes in species extinctions

Abstract

A fundamental goal of conservation science is to improve conservation practice. Understanding species extinction patterns has been a central approach towards this objective. However, uncertainty remains about the extent to which species-level patterns reliably indicate population phenomena at the scale of local sites, where conservation ultimately takes place. Here, we explore the importance of both species- and site-specific components of variation in local population declines following habitat disturbance, and test a suite of hypotheses about their intrinsic and extrinsic drivers. To achieve these goals, we analyse an unusually detailed global dataset for species responses to habitat disturbance, namely primates in timber extraction systems, using cross-classified generalized linear mixed models. We show that while there are consistent differences in the severity of local population decline between species, an equal amount of variation also occurs between sites. The tests of our hypotheses further indicate that a combination of biological traits at the species level, and environmental factors at the site level, can help to explain these patterns. Specifically, primate populations show a more marked decline when the species is characterized by slow reproduction, high ecological requirements, low ecological flexibility and small body size; and when the local environment has had less time for recovery following disturbance. Our results demonstrate that individual species show a highly heterogeneous, yet explicable, pattern of decline. The increased recognition and elucidation of local-scale processes in species declines will improve our ability to conserve biodiversity in the future.

Figure 1

Variation in response ratios (r) across (a) sites and (b) species. The response ratio is the population change in response to logging (calculated as the abundance in logged forest divided by the abundance in matching unlogged forest), where r=1 is no change, r>1 is an increase and r<1 a decrease, and r=0 is extinction. Median r values are shown by the black horizontal bars, interquartile ranges are shown by the grey vertical bars, and minimum and maximum values are indicated by the vertical lines. The y-axis is square-root transformed (sqrt, for ease of presentation). All sites and species where sample size n>2 are plotted. The sites are grouped by country and then by continent, from the Americas eastward to Africa and Asia: BR, Brazil; CR, Costa Rica; GB, Gabon; GH, Ghana; MA, Madagascar; UG, Uganda; ID, Indonesia; MY, Malaysia. The species are listed alphabetically.

Figure 2

The effects of selective logging on primate populations. The response ratio is the population change in response to logging (calculated as the abundance in logged forest divided by the abundance in matching unlogged forest), where r=1 is no change, r>1 is an increase and r<1 a decrease, and r=0 is extinction. The figure shows how the response to logging is a function of both (a) extrinsic and (b) intrinsic variables. (a) The extrinsic variable is the recovery time (years since logging). (b) The four intrinsic variables are (i) body size, (ii) ecological flexibility (indexed by the annual temperature range at the centre of the species geographical range), (iii) gestation period and (iv) home range size. Data are predicted values obtained from the overall best-fitting model, back-transformed from the log_e-transformed data, holding other variables constant at their median value.