Testing the precision and sensitivity of density estimates obtained with a camera‐trap method revealed limitations and opportunities

The use of camera traps in ecology helps affordably address questions about the distribution and density of cryptic and mobile species. The random encounter model (REM) is a camera‐trap method that has been developed to estimate population densities using unmarked individuals. However, few studies have evaluated its reliability in the field, especially considering that this method relies on parameters obtained from collared animals (i.e., average speed, in km/h), which can be difficult to acquire at low cost and effort. Our objectives were to (1) assess the reliability of this camera‐trap method and (2) evaluate the influence of parameters coming from different populations on density estimates. We estimated a reference density of black bears (Ursus americanus) in Forillon National Park (Québec, Canada) using a spatial capture–recapture estimator based on hair‐snag stations. We calculated average speed using telemetry data acquired from four different bear populations located outside our study area and estimated densities using the REM. The reference density, determined with a Bayesian spatial capture–recapture model, was 2.87 individuals/10km² [95% CI: 2.41–3.45], which was slightly lower (although not significatively different) than the different densities estimated using REM (ranging from 4.06–5.38 bears/10km² depending on the average speed value used). Average speed values obtained from different populations had minor impacts on REM estimates when the difference in average speed between populations was low. Bias in speed values for slow‐moving species had more influence on REM density estimates than for fast‐moving species. We pointed out that a potential overestimation of density occurs when average speed is underestimated, that is, using GPS telemetry locations with large fix‐rate intervals. Our study suggests that REM could be an affordable alternative to conventional spatial capture–recapture, but highlights the need for further research to control for potential bias associated with speed values determined using GPS telemetry data.     

Effects of environmental synchrony and density-dependent dispersal on temporal and spatial slopes of Taylor's law

Taylor's law (TL) is an empirical rule that describes an approximate relationship between the variance and mean of population density: log₁₀(variance) ≈ log₁₀(a) + b × log₁₀(mean). Population synchrony is another prevailing feature observed in empirical populations. This study investigated the effects of environmental synchrony and density-dependent dispersal on the temporal (b_T) and spatial (b_S) slopes of TL, using an empirical dataset of gray-sided vole populations and simulation analyses based on the second-order autoregressive (AR) model. Eighty-five empirical populations satisfied the temporal and spatial TLs with b_T = 1.943 (±SE 0.143) and b_S = 1.579 (±SE 0.136). The pairwise synchrony of population was 0.377 ± 0.199 (mean ± SD). Most simulated populations that obeyed the AR model satisfied the form of the temporal and spatial TLs without being affected by the environmental synchrony and density-dependent dispersal; however, those simulated slopes were too steep. The incorporation of environmental synchrony resulted in reduced simulated slopes, but those slopes, too, were still unrealistically steep. By incorporating density-dependent dispersal, simulated slopes decreased and fell within a realistic range. However, the simulated populations without environmental synchrony did not exhibit an adequate degree of density synchrony. In simulations that included both environmental synchrony and density-dependent dispersal, 92.7% of the simulated datasets provided realistic values for b_T, b_S and population synchrony. Because the two slopes were more sensitive to the variation of density-dependent dispersal than that of environmental synchrony, density-dependent dispersal may be the key to the determination of b_T and b_S.     

Generalizations of the Moran effect explaining spatial synchrony in population fluctuations

The Moran effect for populations separated in space states that the autocorrelations in the population fluctuations equal the autocorrelation in environmental noise, assuming the same linear density regulation in all populations. Here we generalize the Moran effect to include also nonlinear density regulation with spatial heterogeneity in local population dynamics as well as in the effects of environmental covariates by deriving a simple expression for the correlation between the sizes of two populations, using diffusion approximation to the theta-logistic model. In general, spatial variation in parameters describing the dynamics reduces population synchrony. We also show that the contribution of a covariate to spatial synchrony depends strongly on spatial heterogeneity in the covariate or in its effect on local dynamics. These analyses show exactly how spatial environmental covariation can synchronize fluctuations of spatially segregated populations with no interchange of individuals even if the dynamics are nonlinear.     

Causes and consequences of variation in early‐life telomere length in a bird metapopulation

Environmental conditions during early‐life development can have lasting effects shaping individual heterogeneity in fitness and fitness‐related traits. The length of telomeres, the DNA sequences protecting chromosome ends, may be affected by early‐life conditions, and telomere length (TL) has been associated with individual performance within some wild animal populations. Thus, knowledge of the mechanisms that generate variation in TL, and the relationship between TL and fitness, is important in understanding the role of telomeres in ecology and life‐history evolution. Here, we investigate how environmental conditions and morphological traits are associated with early‐life blood TL and if TL predicts natal dispersal probability or components of fitness in 2746 wild house sparrow (Passer domesticus) nestlings from two populations sampled across 20 years (1994–2013). We retrieved weather data and we monitored population fluctuations, individual survival, and reproductive output using field observations and genetic pedigrees. We found a negative effect of population density on TL, but only in one of the populations. There was a curvilinear association between TL and the maximum daily North Atlantic Oscillation index during incubation, suggesting that there are optimal weather conditions that result in the longest TL. Dispersers tended to have shorter telomeres than non‐dispersers. TL did not predict survival, but we found a tendency for individuals with short telomeres to have higher annual reproductive success. Our study showed how early‐life TL is shaped by effects of growth, weather conditions, and population density, supporting that environmental stressors negatively affect TL in wild populations. In addition, shorter telomeres may be associated with a faster pace‐of‐life, as individuals with higher dispersal rates and annual reproduction tended to have shorter early‐life TL.     

Metapopulation dynamics with quasi-local competition

Stepping-stone models for the ecological dynamics of metapopulations are often used to address general questions about the effects of spatial structure on the nature and complexity of population fluctuations. Such models describe an ensemble of local and spatially isolated habitat patches that are connected through dispersal. Reproduction and hence the dynamics in a given local population depend on the density of that local population, and a fraction of every local population disperses to neighboring patches. In such models, interesting dynamic phenomena, e.g. the persistence of locally unstable predator-prey interactions, are only observed if the local dynamics in an isolated patch exhibit non-equilibrium behavior. Therefore, the scope of these models is limited. Here we extend these models by making the biologically plausible assumption that reproductive success in a given local habitat not only depends on the density of the local population living in that habitat, but also on the densities of neighboring local populations. This would occur if competition for resources occurs between neighboring populations, e.g. due to foraging in neighboring habitats. With this assumption of quasi-local competition the dynamics of the model change completely. The main difference is that even if the dynamics of the local populations have a stable equilibrium in isolation, the spatially uniform equilibrium in which all local populations are at their carrying capacity becomes unstable if the strength of quasi-local competition reaches a critical level, which can be calculated analytically. In this case the metapopulation reaches a new stable state, which is, however, not spatially uniform anymore and instead results in an irregular spatial pattern of local population abundance. For large metapopulations, a huge number of different, spatially non-uniform equilibrium states coexist as attractors of the metapopulation dynamics, so that the final state of the system depends critically on the initial conditions. The existence of a large number of attractors has important consequences when environmental noise is introduced into the model. Then the metapopulation performs a random walk in the space of all attractors. This leads to large and complicated population fluctuations whose power spectrum obeys a red-shifted power law. Our theory reiterates the potential importance of spatial structure for ecological processes and proposes new mechanisms for the emergence of non-uniform spatial patterns of abundance and for the persistence of complicated temporal population fluctuations.     

有色环境噪音对空间异质种群动态同步性的影响

随着种群动态和空间结构研究兴趣的增加,激发了大量的有关空间同步性的理论和实验的研究工作。空间种群的同步波动现象在自然界广泛存在,它的影响和原因引起了很多生态学家的兴趣。Moran定理是一个非常重要的解释。但以往的研究大多假设环境变化为空间相关的白噪音。越来越多的研究表明很多环境变化的时间序列具有正的时间自相关性,也就是说用红噪音来描述更加合理。因此,推广经典的Moran效应来处理空间相关红噪音的情形很有必要。利用线性的二阶自回归过程的种群模型,推导了两种群空间同步性与种群动态异质性和环境变化的时间相关性(即环境噪音的颜色)之间的关系。深入分析了种群异质性和噪音颜色对空间同步性的影响。结果表明种群动态异质性不利于空间同步性,但详细的关系比较复杂。而红色噪音的同步能力体现在两方面:一方面,本身的相关性对同步性有贡献;另一方面,环境变化时间相关性可以通过改变种群密度依赖来影响同步性,但对同步性的影响并无一致性的结论,依赖于种群的平均动态等因素。这些结果对理解同步性的机理、利用同步机理来制定物种保护策略和害虫防治都有重要的意义。     

Taylor's law and body size in exploited marine ecosystems

Taylor's law (TL), which states that variance in population density is related to mean density via a power law, and density‐mass allometry, which states that mean density is related to body mass via a power law, are two of the most widely observed patterns in ecology. Combining these two laws predicts that the variance in density is related to body mass via a power law (variance‐mass allometry). Marine size spectra are known to exhibit density‐mass allometry, but variance‐mass allometry has not been investigated. We show that variance and body mass in unexploited size spectrum models are related by a power law, and that this leads to TL with an exponent slightly <2. These simulated relationships are disrupted less by balanced harvesting, in which fishing effort is spread across a wide range of body sizes, than by size‐at‐entry fishing, in which only fish above a certain size may legally be caught.     

An open spatial capture–recapture model for estimating density,movement, and population dynamics from line‐transect surveys

The purpose of many wildlife population studies is to estimate density, movement, or demographic parameters. Linking these parameters to covariates, such as habitat features, provides additional ecological insight and can be used to make predictions for management purposes. Line‐transect surveys, combined with distance sampling methods, are often used to estimate density at discrete points in time, whereas capture–recapture methods are used to estimate movement and other demographic parameters. Recently, open population spatial capture–recapture models have been developed, which simultaneously estimate density and demographic parameters, but have been made available only for data collected from a fixed array of detectors and have not incorporated the effects of habitat covariates. We developed a spatial capture–recapture model that can be applied to line‐transect survey data by modeling detection probability in a manner analogous to distance sampling. We extend this model to a) estimate demographic parameters using an open population framework and b) model variation in density and space use as a function of habitat covariates. The model is illustrated using simulated data and aerial line‐transect survey data for North Atlantic right whales in the southeastern United States, which also demonstrates the ability to integrate data from multiple survey platforms and accommodate differences between strata or demographic groups. When individuals detected from line‐transect surveys can be uniquely identified, our model can be used to simultaneously make inference on factors that influence spatial and temporal variation in density, movement, and population dynamics.     

Modelling single nucleotide effects in phosphoglucose isomerase on dispersal in the Glanville fritillary butterfly: coupling of ecological and evolutionary dynamics

Dispersal comprises a complex life-history syndrome that influences the demographic dynamics of especially those species that live in fragmented landscapes, the structure of which may in turn be expected to impose selection on dispersal. We have constructed an individual-based evolutionary sexual model of dispersal for species occurring as metapopulations in habitat patch networks. The model assumes correlated random walk dispersal with edge-mediated behaviour (habitat selection) and spatially correlated stochastic local dynamics. The model is parametrized with extensive data for the Glanville fritillary butterfly. Based on empirical results for a single nucleotide polymorphism (SNP) in the phosphoglucose isomerase (Pgi) gene, we assume that dispersal rate in the landscape matrix, fecundity and survival are affected by a locus with two alleles, A and C, individuals with the C allele being more mobile. The model was successfully tested with two independent empirical datasets on spatial variation in Pgi allele frequency. First, at the level of local populations, the frequency of the C allele is the highest in newly established isolated populations and the lowest in old isolated populations. Second, at the level of sub-networks with dissimilar numbers and connectivities of patches, the frequency of C increases with decreasing network size and hence with decreasing average metapopulation size. The frequency of C is the highest in landscapes where local extinction risk is high and where there are abundant opportunities to establish new populations. Our results indicate that the strength of the coupling of the ecological and evolutionary dynamics depends on the spatial scale and is asymmetric, demographic dynamics having a greater immediate impact on genetic dynamics than vice versa.     

Propagation of dynamic changes in barnase upon binding of barstar: an NMR and computational study

NMR spectroscopy and computer simulations were used to examine changes in chemical shifts and in dynamics of the ribonuclease barnase that result upon binding to its natural inhibitor barstar. Although the spatial structures of free and bound barnase are very similar, binding results in changes of the dynamics of both fast side-chains, as revealed by (2)H relaxation measurements, and NMR chemical shifts in an extended beta-sheet that is located far from the binding interface. Both side-chain dynamics and chemical shifts are sensitive to variations in the ensemble populations of the inter-converting molecular states, which can escape direct structural observation. Molecular dynamics simulations of free barnase and barnase in complex with barstar, as well as a normal mode analysis of barnase using a Gaussian network model, reveal relatively rigid domains that are separated by the extended beta-sheet mentioned above. The observed changes in NMR parameters upon ligation can thus be rationalized in terms of changes in inter-domain dynamics and in populations of exchanging states, without measurable structural changes. This provides an alternative model for the propagation of a molecular response to ligand binding across a protein that is based exclusively on changes in dynamics.     

Robustness of Taylor’s law under spatial hierarchical groupings of forest tree samples

Testing how well Taylor's law (TL) describes spatial variation of the population density of a species requires grouping sampling areas (patches of habitat) into blocks so that a mean and a variance of the population density can be calculated over the patches in each block. The relationship between specific groupings and TL remains largely unknown. Here, using tree counts from a deciduous forest, we studied the effect of four biological methods of grouping sampling areas into blocks on the form and parameters of TL. Regardless of the method of grouping, the species-specific basal area densities obeyed TL, and the estimated slopes were not significantly different from one grouping method to another. Surprisingly, TL remained valid when four kinds of randomizations were performed to the biological groupings and tree census. These randomizations randomly assigned sampling areas to blocks, and/or randomized the species composition within or across sampling areas. We found that the form of TL was robust to different grouping methods and species randomizations, but its parameter values depended significantly on species compositions at sampling areas.     

Plague epizootic cycles in Central Asia

Infection thresholds, widely used in disease epidemiology, may operate on host abundance and, if present, on vector abundance. For wildlife populations, host and vector abundances often vary greatly across years and consequently the threshold may be crossed regularly, both up- and downward. Moreover, vector and host abundances may be interdependent, which may affect the infection dynamics. Theory predicts that if the relevant abundance, or combination of abundances, is above the threshold, then the infection is able to spread; if not, it is bound to fade out. In practice, though, the observed level of infection may depend more on past than on current abundances. Here, we study the temporal dynamics of plague (Yersinia pestis infection), its vector (flea) and its host (great gerbil) in the PreBalkhash region in Kazakhstan. We describe how host and vector abundances interact over time and how this interaction drives the dynamics of the system around the infection threshold, consequently affecting the proportion of plague-infected sectors. We also explore the importance of the interplay between biological and detectability delays in generating the observed dynamics.     

Sex-specific costs of reproduction on survival in a long-lived seabird

Costs of reproduction on survival have captured the attention of researchers since life history theory was formulated. Adults of long-lived species may increase survival by reducing their breeding effort or even skipping reproduction. In this study, we aimed to evaluate the costs of current reproduction on survival and whether skipping reproduction increases adult survival in a long-lived seabird. We used capture–mark–recapture data (1450 encounters) from two populations of Bulwer''s petrel (Bulweria bulwerii), breeding in the Azores and Canary Islands, North Atlantic Ocean. Using a multi-event model with two different breeding statuses (breeders versus non-breeders), we calculated probabilities of survival and of transitions between breeding statuses, evaluating potential differences between sexes. Females had lower survival probabilities than males, independent of their breeding status. When considering breeding status, breeding females had lower survival probabilities than non-breeding females, suggesting costs of reproduction on survival. Breeding males had higher survival probabilities than non-breeding males, suggesting that males do not incur costs of reproduction on survival and that only the highest quality males have access to breeding. The highest and the lowest probabilities of skipping reproduction were found in breeding males from the Azores and in breeding males from the Canary Islands, respectively. Intermediate values were observed in the females from both populations. This result is probably due to differences in the external factors affecting both populations, essentially predation pressure and competition. The existence of sex-specific costs of reproduction on survival in several populations of this long-lived species may have important implications for species population dynamics.     

Demographic models reveal the shape of density dependence for a specialist insect herbivore on variable host plants

1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.     

Movements of genes between populations: are pollinators more effective at transferring their own or plant genetic markers?

The transfer of genes between populations is increasingly important in a world where pollinators are declining, plant and animal populations are increasingly fragmented and climate change is forcing shifts in distribution. The distances that pollen can be transported by small insects are impressive, as is the extensive gene flow between their own populations. We compared the relative ease by which small insects introduce genetic markers into their own and host-plant populations. Gene flow via seeds and pollen between populations of an Asian fig species were evaluated using cpDNA and nuclear DNA markers, and between-population gene flow of its pollinator fig wasp was determined using microsatellites. This insect is the tree''s only pollinator locally, and only reproduces in its figs. The plant''s pollen-to-seed dispersal ratio was 9.183–9.437, smaller than that recorded for other Ficus. The relative effectiveness of the pollinator at introducing markers into its own populations was higher than the rate it introduced markers into the plant''s populations (ratio = 14 : 1), but given the demographic differences between plant and pollinator, pollen transfer effectiveness is remarkably high. Resource availability affects the dispersal of fig wasps, and host-plant flowering phenology here and in other plant–pollinator systems may strongly influence relative gene flow rates.     

A model of canine leukocyte telomere dynamics

Recent studies have found associations of leukocyte telomere length (TL) with diseases of aging and with longevity. However, it is unknown whether birth leukocyte TL or its age-dependent attrition--the two factors that determine leukocyte TL dynamics--explains these associations because acquiring this information entails monitoring individuals over their entire life course. We tested in dogs a model of leukocyte TL dynamics, based on the following premises: (i) TL is synchronized among somatic tissues; (ii) TL in skeletal muscle, which is largely postmitotic, is a measure of TL in early development; and (iii) the difference between TL in leukocytes and muscle (ΔLMTL) is the extent of leukocyte TL shortening since early development. Using this model, we observed in 83 dogs (ages, 4-42 months) no significant change with age in TLs of skeletal muscle and a shorter TL in leukocytes than in skeletal muscle (P<0.0001). Age explained 43% of the variation in ΔLMTL (P<0.00001), but only 6% of the variation in leukocyte TL (P=0.035) among dogs. Accordingly, muscle TL and ΔLMTL provide the two essential factors of leukocyte TL dynamics in the individual dog. When applied to humans, the partition of the contribution of leukocyte TL during early development vs. telomere shortening afterward might provide information about whether the individual's longevity is calibrated to either one or both factors that define leukocyte TL dynamics.     

Can inverse density dependence at small spatial scales produce dynamic instability in animal populations?

All else being equal, inversely density-dependent (IDD) mortality destabilizes population dynamics. However, stability has not been investigated for cases in which multiple types of density dependence act simultaneously. To determine whether IDD mortality can destabilize populations that are otherwise regulated by directly density-dependent (DDD) mortality, I used scale transition approximations to model populations with IDD mortality at smaller “aggregation” scales and DDD mortality at larger “landscape” scales, a pattern observed in some reef fish and insect populations. I evaluated dynamic stability for a range of demographic parameter values, including the degree of compensation in DDD mortality and the degree of spatial aggregation, which together determine the relative importance of DDD and IDD processes. When aggregation-scale survival was a monotonically increasing function of density (a “dilution” effect), dynamics were stable except for extremely high levels of aggregation combined with either undercompensatory landscape-scale density dependence or certain values of adult fecundity. When aggregation-scale survival was a unimodal function of density (representing both “dilution” and predator “detection” effects), instability occurred with lower levels of aggregation and also depended on the values of fecundity, survivorship, detection effect, and DDD compensation parameters. These results suggest that only in extreme circumstances will IDD mortality destabilize dynamics when DDD mortality is also present, so IDD processes may not affect the stability of many populations in which they are observed. Model results were evaluated in the context of reef fish, but a similar framework may be appropriate for a diverse range of species that experience opposing patterns of density dependence across spatial scales.     

Modelling and predicting the spatial distribution of tree root density in heterogeneous forest ecosystems

Background and Aims In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m^–2). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape.Methods The model comprises three sub-models for predicting: (1) the spatial heterogeneity – RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum – the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile – the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition.Key Results In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data.Conclusions The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems.     

How fast is fast? Eco‐evolutionary dynamics and rates of change in populations and phenotypes

It is increasingly recognized that evolution may occur in ecological time. It is not clear, however, how fast evolution – or phenotypic change more generally – may be in comparison with the associated ecology, or whether systems with fast ecological dynamics generally have relatively fast rates of phenotypic change. We developed a new dataset on standardized rates of change in population size and phenotypic traits for a wide range of species and taxonomic groups. We show that rates of change in phenotypes are generally no more than 2/3, and on average about 1/4, the concurrent rates of change in population size. There was no relationship between rates of population change and rates of phenotypic change across systems. We also found that the variance of both phenotypic and ecological rates increased with the mean across studies following a power law with an exponent of two, while temporal variation in phenotypic rates was lower than in ecological rates. Our results are consistent with the view that ecology and evolution may occur at similar time scales, but clarify that only rarely do populations change as fast in traits as they do in abundance.     

Lions in a coexistence landscape: Repurposing a traditional field technique to monitor an elusive carnivore

Throughout Africa, lions are thought to have experienced dramatic population decline and range contraction. The greatest declines are likely occurring in human‐dominated landscapes where reliably estimating lion populations is particularly challenging. By adapting a method that has thus far only been applied to animals that are habituated to vehicles, we estimate lion density in two community areas in Kenya''s South Rift, located more than 100 km from the nearest protected area (PA). More specifically, we conducted an 89‐day survey using unstructured spatial sampling coupled with playbacks, a commonly used field technique, and estimated lion density using spatial capture‐recapture (SCR) models. Our estimated density of 5.9 lions over the age of 1 year per 100 km² compares favorably with many PAs and suggests that this is a key lion population that could be crucial for connectivity across the wider landscape. We discuss the possible mechanisms supporting this density and demonstrate how rigorous field methods combined with robust analyses can produce reliable population estimates within human‐dominated landscapes.