Multistage density dependence in an amphibian

Density dependence is the major process keeping the sizes of natural populations within bounds. In organisms with complex life cycles, the stage at which density dependence occurs and whether it occurs in one or several life stages have important consequences for the dynamics of their populations. I manipulated density of pool frogs (Rana lessonae) during the aquatic larval and the terrestrial juvenile stages and examined the effect on growth and survival until 1year of age. High larval density, but not high juvenile density, led to smaller size at this age. Both larval and juvenile density led to reduced growth during the early juvenile stage, but the effect of the larval density appeared stronger than the effect of juvenile density. No density dependence in survival could be found. My results suggest that density dependence in both the larval and the terrestrial juvenile stage may play important roles in the regulation and dynamics of amphibian population

Breeding rate is associated with pheomelanism in male and with eumelanism in female barn owls

Melanin-based coloration exists in 2 types: black eumelanism and reddish-brown pheomelanism, which both have a strong heritable component. To test whether these 2 types of melanism are associated with alternative adaptations, we carried out a correlative study over 8 years and an experiment in a Swiss population of barn owls, Tyto alba. This species varies in coloration from reddish-brown to white and from lightly to heavily marked with black spots. Based on the fact that plumage coloration and spottiness are male- and female-specific secondary sexual characters, respectively, we examined whether the probability of breeding is associated with the degree of pheomelanism in males and of eumelanism in females. In males, recruited nestlings were significantly less reddish-brown than their nonrecruited nest mates. In females, individuals displaying larger black spots started to breed at a younger age and had a higher survival, and females with experimentally reduced plumage spottiness bred less often than control females. Therefore, in the barn owl, the degree of male pheomelanism is associated with the probability of being recruited in the local population, whereas the degree of female eumelanism correlates with age at sexual maturity, survival probability, and also the probability of skipping reproductio

Departures from the energy-biodiversity relationship in south african passerines: are the legacies of past climates mediated by behavioral constraints on dispersal?

Legacies of paleoclimates in contemporary biodiversity patterns have mostly been investigated with global datasets, or with weakly dispersive organisms, and as a consequence been interpreted in terms of geographical or physical constraints. If paleoclimatic legacies also occurred at the regional scale in the distributions of vagile organisms within biomes, they would rather suggest behavioral constraints on dispersal, i.e., philopatric syndromes. We examined 1) the residuals of the regression between contemporary energy and passerine species richness in South African biomes and 2) phylogenetic dispersion of passerine assemblages, using occupancy models and quarter-degree resolution citizen science data. We found a northeast to southwest gradient within mesic biomes congruent with the location of Quaternary mesic refugia, overall suggesting that as distance from refugia increased, more clades were lacking from local assemblages. A similar but weaker pattern was detected in the arid Karoo Biomes. In mobile organisms such as birds, behavioral constraints on dispersal appear strong enough to influence species distributions thousands of years after historical range contractions

Functional responses can’t unify invasion ecology

Dick et al. (Biol Invasions, 2017) propose that the comparative functional response framework provides a unifying approach for the study of invasive species. We agree that functional responses are an important and powerful quantitative description of consumer effects on resources, and co-opting classical ecological theory to better predict invasive species impacts is a laudable move for invasion biology. However, we fear that the early successes of select examples of the comparative functional response (CFR) approach has led Dick et al. to exaggerate the generality of its utility, and about its ability to unify the field. Further, they fail to provide a convincing argument why CFR is better than existing tools such as invasion history or impact indices, even when considering emerging or potential invaders. In this response we provide details of three conceptual issues stemming from classical ecological theoretical frameworks and two practical problems that Dick et al. and other CFR proponents need to address

Revisiting the effect of capture heterogeneity on survival estimates in capture-mark-recapture studies: does it matter?

Recently developed capture-mark-recapture methods allow us to account for capture heterogeneity among individuals in the form of discrete mixtures and continuous individual random effects. In this article, we used simulations and two case studies to evaluate the effectiveness of continuously distributed individual random effects at removing potential bias due to capture heterogeneity, and to evaluate in what situation the added complexity of these models is justified. Simulations and case studies showed that ignoring individual capture heterogeneity generally led to a small negative bias in survival estimates and that individual random effects effectively removed this bias. As expected, accounting for capture heterogeneity also led to slightly less precise survival estimates. Our case studies also showed that accounting for capture heterogeneity increased in importance towards the end of study. Though ignoring capture heterogeneity led to a small bias in survival estimates, such bias may greatly impact management decisions. We advocate reducing potential heterogeneity at the sampling design stage. Where this is insufficient, we recommend modelling individual capture heterogeneity in situations such as when a large proportion of the individuals has a low detection probability (e.g. in the presence of floaters) and situations where the most recent survival estimates are of great interest (e.g. in applied conservation)

Exact Likelihoods for N-mixture models with Time-to-Detection Data

This paper is concerned with the formulation of $N$-mixture models for estimating the abundance and probability of detection of a species from binary response, count and time-to-detection data. A modelling framework, which encompasses time-to-first-detection within the context of detection/non-detection and time-to-each-detection and time-to-first-detection within the context of count data, is introduced. Two observation processes which depend on whether or not double counting is assumed to occur are also considered. The main focus of the paper is on the derivation of explicit forms for the likelihoods associated with each of the proposed models. Closed-form expressions for the likelihoods associated with time-to-detection data are new and are developed from the theory of order statistics. A key finding of the study is that, based on the assumption of no double counting, the likelihoods associated with times-to-detection together with count data are the product of the likelihood for the counts alone and a term which depends on the detection probability parameter. This result demonstrates that, in this case, recording times-to-detection could well improve precision in estimation over recording counts alone. In contrast, for the double counting protocol with exponential arrival times, no information was found to be gained by recording times-to-detection in addition to the count data. An R package and an accompanying vignette are also introduced in order to complement the algebraic results and to demonstrate the use of the models in practice.Comment: 21 pages, 1 figur

Efficient Bayesian analysis of occupancy models with logit link functions

Occupancy models (Ecology, 2002; 83: 2248) were developed to infer the probability that a species under investigation occupies a site. Bayesian analysis of these models can be undertaken using statistical packages such as WinBUGS, OpenBUGS, JAGS, and more recently Stan, however, since these packages were not developed specifically to fit occupancy models, one often experiences long run times when undertaking an analysis. Bayesian spatial single‐season occupancy models can also be fit using the R package stocc. The approach assumes that the detection and occupancy regression effects are modeled using probit link functions. The use of the logistic link function, however, is algebraically more tractable and allows one to easily interpret the coef‐ ficient effects of an estimated model by using odds ratios, which is not easily done for a probit link function for models that do not include spatial random effects. We de‐ velop a Gibbs sampler to obtain posterior samples from the posterior distribution of the parameters of various occupancy models (nonspatial and spatial) when logit link functions are used to model the regression effects of the detection and occupancy processes. We apply our methods to data extracted from the 2nd Southern African Bird Atlas Project to produce a species distribution map of the Cape weaver (Ploceus capensis) and helmeted guineafowl (Numida meleagris) for South Africa. We found that the Gibbs sampling algorithm developed produces posterior samples that are identical to those obtained when using JAGS and Stan and that in certain cases the posterior chains mix much faster than those obtained when using JAGS, stocc, and Stan. Our algorithms are implemented in the R package, Rcppocc. The software is freely available and stored on GitHub (https://github.com/AllanClark/Rcppocc)

Is climate change causing the range contraction of Cape Rock-jumpers (\u3ci\u3eChaetops frenatus\u3c/i\u3e)?

Species distribution models often suggest strong links between climate and species\u27 distribution boundaries and project large distribution shifts in response to climate change. However, attributing distribution shifts to climate change requires more than correlative models. One idea is to examine correlates of the processes that cause distribution shifts, namely colonization and local extinction, by using dynamic occupancy models. The Cape Rock-jumper (Chaetops frenatus) has disappeared over most of its distribution where temperatures are the highest. We used dynamic occupancy models to analyse Cape Rock-jumper distribution with respect to climate (mean temperature and precipitation over the warmest annual quarter), vegetation (proportion of natural vegetation, fynbos) and land-use type (protected areas). Detection/non-detection data were collected over two phases of the Southern African Bird Atlas Project (SABAP): 1987–1991 (SABAP1) and 2008–2014 (SABAP2). The model described the contraction of the Cape Rock-jumper\u27s distribution between SABAP1 and SABAP2 well. Occupancy probability during SABAP1 increased with the proportion of fynbos and protected area per grid cell, and decreased with increases in mean temperature and precipitation over the warmest annual quarter. Mean extinction probability increased with mean temperature and precipitation over the warmest annual quarter, although the associated confidence intervals were wide. Nonetheless, our results showed a clear correlation between climate and the distribution boundaries of the Cape Rock-jumper, and in particular, the species\u27 aversion for higher temperatures. The data were less conclusive on whether the observed range contraction was linked to climate change or not. Examining the processes underlying distribution shifts requires large datasets and should lead to a better understanding of the drivers of these shifts