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There is an urgent need for reliable data on the impacts of deforestation on tropical biodiversity. The city-state of Singapore has one of the most detailed biodiversity records in the tropics, dating back to the turn of the 19th century. In 1819, Singapore was almost entirely covered in primary forest, but this has since been largely cleared. We compiled more than 200 y of records for 10 major taxonomic groups in Singapore (>50,000 individual records; >3,000 species), and we estimated extinction rates using recently developed and novel statistical models that account for “dark extinctions,” i.e., extinctions of undiscovered species. The estimated overall extinction rate was 37% (95% CI [31 to 42%]). Extrapolating our Singapore observations to a future business-as- usual deforestation scenario for Southeast Asia suggests that 18% (95% CI [16 to 22%]) of species will be lost regionally by 2100. Our extinction estimates for Singapore and Southeast Asia are a factor of two lower than previous estimates that also attempted to account for dark extinctions. However, we caution that particular groups such as large mammals, forest-dependent birds, orchids, and butterflies are disproportionately vulnerable. [ABSTRACT FROM AUTHOR]

Bayesian methods have been developed for inferring the true year of extinction of a species from sighting records that have both certain and uncertain sightings. These methods typically make the restrictive assumption that all sighting types (i.e. certain, valid uncertain, invalid uncertain) derive from constant rate Poisson processes.In this study, the constant rate assumption in the homogeneous Poisson process is relaxed by allowing certain and uncertain sightings to follow independent non‐homogeneous Poisson processes. The model can thus identify whether any of the sighting rates were increasing, decreasing or constant. In addition, a change‐point is introduced to model the uncertain sightings, where the sighting rates before and after the change‐point vary.We have used Markov Chain Monte Carlo (MCMC) sampling to generate the posterior distributions for model parameters including species extinction time. The proposed method was applied to the sighting records of the black‐footed ferret Mustela nigripes and the ivory‐billed woodpecker Campephilus principalis (IBW) species.Based on a hypothesis test, the results of the model indicate that the species both went extinct in the years 1988 and 1956 respectively. Moreover, a decline in the certain sighting rate was also inferred for both these species, possibly indicating the decrease in the species abundance as it converges to extinction. Thus, earlier models that assume a constant sighting rate may well be biased. Uncertain sighting rates for the IBW were found to increase before extinction (indicating possibly some additional ecological attention received near extinction) and remained constant after extinction. [ABSTRACT FROM AUTHOR]

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The coexistence of many species within ecological communities poses a long‐standing theoretical puzzle. Modern coexistence theory (MCT) and related techniques explore this phenomenon by examining the chance of a species population growing from rarity in the presence of all other species. The mean growth rate when rare, E[r], is used in MCT as a metric that measures persistence properties (like invasibility or time to extinction) of a population. Here we critique this reliance on E[r] and show that it fails to capture the effect of temporal random abundance variations on persistence properties. The problem becomes particularly severe when an increase in the amplitude of stochastic temporal environmental variations leads to an increase in E[r], since at the same time it enhances random abundance fluctuations and the two effects are inherently intertwined. In this case, the chance of invasion and the mean extinction time of a population may even go down as E[r] increases. [ABSTRACT FROM AUTHOR]

Among the local processes that determine species diversity in ecological communities, fluctuation‐dependent mechanisms that are mediated by temporal variability in the abundances of species populations have received significant attention. Higher temporal variability in the abundances of species populations can increase the strength of temporal niche partitioning but can also increase the risk of species extinctions, such that the net effect on species coexistence is not clear. We quantified this temporal population variability for tree species in 21 large forest plots and found much greater variability for higher latitude plots with fewer tree species. A fitted mechanistic model showed that among the forest plots, the net effect of temporal population variability on tree species coexistence was usually negative, but sometimes positive or negligible. Therefore, our results suggest that temporal variability in the abundances of species populations has no clear negative or positive contribution to the latitudinal gradient in tree species richness. [ABSTRACT FROM AUTHOR]

Habitat loss leads to species extinctions, both immediately and over the long term as 'extinction debt' is repaid. The same quantity of habitat can be lost in different spatial patterns with varying habitat fragmentation. How this translates to species loss remains an open problem requiring an understanding of the interplay between community dynamics and habitat structure across temporal and spatial scales. Here we develop formulas that characterise extinction debt in a spatial neutral model after habitat loss and fragmentation. Central to our formulas are two new metrics, which depend on properties of the taxa and landscape: 'effective area', measuring the remaining number of individuals and 'effective connectivity', measuring individuals' ability to disperse through fragmented habitat. This formalises the conventional wisdom that habitat area and habitat connectivity are the two critical requirements for long‐term preservation of biodiversity. Our approach suggests that mechanistic fragmentation metrics help resolve debates about fragmentation and species loss. [ABSTRACT FROM AUTHOR]

• Extinction risk of a species population with negative growth rate analyzed. • Extinction risk partitioned according to key deterministic and stochastic processes. • Deterministic processes drive extinction risk when growth rate is large. • Stochastic processes often drive extinction risk when growth rate is small. • Demographic and environmental variance often have sub-additive extinction effects. Species populations are subjected to deterministic and stochastic processes, both of which contribute to their risk of extinction. However, current understanding of the relative contributions of these processes to species extinction risk is far from complete. Here, we address this knowledge gap by analyzing a suite of models representing species populations with negative intrinsic growth rates, to partition extinction risk according to deterministic processes and two broad classes of stochastic processes – demographic and environmental variance. Demographic variance refers to random variations in population abundance arising from random sampling of events given a particular set of intrinsic demographic rates, whereas environmental variance refers to random abundance variations arising from random changes in intrinsic demographic rates over time. When the intrinsic growth rate was not close to zero, we found that deterministic growth was the main driver of mean time to extinction, even when population size was small. This contradicts the intuition that demographic variance is always an important determinant of extinction risk for small populations. In contrast, when the intrinsic growth rate was close to zero, stochastic processes exerted substantial negative effects on the mean time to extinction. Demographic variance had a greater effect than environmental variance at low abundances, with the reverse occurring at higher abundances. In addition, we found that the combined effects of demographic and environmental variance were often substantially lower than the sum of their effects in isolation from each other. This sub-additivity indicates redundancy in the way the two stochastic processes increase extinction risk, and probably arises because both processes ultimately increase extinction risk by boosting variation in abundance over time. [ABSTRACT FROM AUTHOR]

Species populations are subjected to fluctuations in their surrounding environment, and the strength of these fluctuations has been hypothesized to be a major determinant of the extinction risk of these populations. Therefore, a key question is: How does temporal environmental variance affect the extinction risk of species populations? Previous theory based on the dynamics of single populations typically predicts an increased risk of extinction from the effects of environmental variance. However, previous studies have focused mainly on the case where environmental effects are temporally uncorrelated (white environmental noise), whereas such effects are typically correlated (colored environmental noise) in nature. Thus, further work on the case of colored environmental noise is required, but this has been hindered by the analytical intractability of corresponding stochastic models. In our study, we address this limitation by developing a new discrete-time Markov chain model of a species population fluctuating under colored environmental noise, with the simplification that the effects of demographic variance are manifested indirectly as an extinction threshold. This simplifying assumption allows us to derive analytical solutions, which show that the expected extinction time of model species declines with the strength of environmental variance under a variety of different scenarios, reflecting greater extinction risk. Our study thus clarifies the situations under which environmental variance tends to increase extinction risk, and provides a novel analytically tractable framework for modeling temporal environmental variance. We also discuss the possible implications of our results for species richness in ecological communities. [ABSTRACT FROM AUTHOR]

How many species have gone extinct in modern times before being described by science? To answer this question, and thereby get a full assessment of humanity's impact on biodiversity, statistical methods that quantify undetected extinctions are required. Such methods have been developed recently, but they are limited by their reliance on parametric assumptions; specifically, they assume the pools of extant and undetected species decay exponentially, whereas real detection rates vary temporally with survey effort and real extinction rates vary with the waxing and waning of threatening processes. We devised a new, nonparametric method for estimating undetected extinctions. As inputs, the method requires only the first and last date at which each species in an ensemble was recorded. As outputs, the method provides estimates of the proportion of species that have gone extinct, detected, or undetected and, in the special case where the number of undetected extant species in the present day is assumed close to zero, of the absolute number of undetected extinct species. The main assumption of the method is that the per-species extinction rate is independent of whether a species has been detected or not. We applied the method to the resident native bird fauna of Singapore. Of 195 recorded species, 58 (29.7%) have gone extinct in the last 200 years. Our method projected that an additional 9.6 species (95% CI 3.4, 19.8) have gone extinct without first being recorded, implying a true extinction rate of 33.0% (95% CI 31.0%, 36.2%). We provide R code for implementing our method. Because our method does not depend on strong assumptions, we expect it to be broadly useful for quantifying undetected extinctions. [ABSTRACT FROM AUTHOR]

The critical weight range (CWR) hypothesis for Australian mammals states that extinctions and declines have been concentrated in species with body mass between 35 g and 5.5 kg. The biological basis for this hypothesis is that species of intermediate size are disproportionately impacted by introduced predators. The CWR hypothesis has received support from several statistical studies over the past decade, although the evidence is weaker or non-existent for certain groups such as mesic-zone mammals and arboreal mammals. In this study, we employ an information-theoretic model selection approach to gain further insights into the relationship between body mass and extinction risk in Australian mammals. We find evidence, consistent with the CWR hypothesis, that extinction risk peaks at intermediate body masses for marsupials, rodents and ground-dwelling species, but not for arboreal species. In contrast to previous studies, we find that the CWR describes extinction patterns in the mesic zone as well as the arid zone. In the mesic zone, there is also a weaker tendency for large species above the CWR to be more vulnerable, consistent with extinction patterns on other continents. We find that a more biological plausible Gaussian distribution consistently fits the data better than the polynomial models that have been used in previous studies. Our results justify conservation programmes targeted at species within the CWR across Australia. [ABSTRACT FROM AUTHOR]

The critical weight range hypothesis for Australian terrestrial mammals states that species in the intermediate size range 35–5500 g are particularly susceptible to extinction. In a 2001 study Cardillo and Bromham found no statistically significant evidence for this hypothesis and suggested that research should instead focus on why small species are resistant to extinction. We used a similar data set of body sizes of Australian mammals grouped by conservation classification, but we used test statistics (mean deviation above and below the median body size) that are more statistically powerful than those of Cardillo and Bromham (quartiles, maxima, and minima of body size distributions). We found strong evidence in favor of the critical weight range hypothesis: the body size distribution of threatened species was more clustered toward the median body size from above and below. This pattern was statistically significant at the continental scale and in the arid zone, but not in the mesic zone. Confusing statistical significance with evidence of no effect, as Cardillo and Bromham did, can have negative implications for conservation biology because it can result in failure to act when action is warranted or provision of incorrect advice that affects policy and planning decisions. [ABSTRACT FROM AUTHOR]