Estimating individual fitness in the wild using capture–recapture data

The concept of Darwinian fitness is central in evolutionary ecology, and its estimation has motivated the development of several approaches. However, measuring individual fitness remains challenging in empirical case studies in the wild. Measuring fitness requires a continuous monitoring of individuals from birth to death, which is very difficult to get in part because individuals may or may not be controlled at each reproductive event and recovered at death. Imperfect detection hampers keeping track of mortality and reproductive events over the whole lifetime of individuals. We propose a new statistical approach to estimate individual fitness while accounting for imperfect detection. Based on hidden process modelling of longitudinal data on marked animals, we show that standard metrics to quantify fitness, namely lifetime reproductive success, individual growth rate and lifetime individual contribution to population growth, can be extended to cope with imperfect detection inherent to most monitoring programs in the wild. We illustrate our approach using data collected on individual roe deer in an intensively monitored population.     

Estimating demographic parameters for loggerhead sea turtles using mark–recapture data and a multistate model

The survival for adult loggerhead sea turtles from a saturation tagging study on Bald Head Island, NC, USA, was estimated using a multistate model with unobservable states to relax assumptions that are violated when survival is estimated from multistate models and produce more accurate estimates of survival, recapture, and breeding transition probabilities. The influence of time, trap dependence, and low site fidelity to the study nesting beach on survival and recapture were examined. The best model given the data included an imprecise site-fidelity effect on survival, constrained the reproductive cycle to 4 years, and contained a time effect on recapture rates. The estimate of annual survival for adult females was of 0.85, producing the highest estimate in the literature for loggerhead sea turtles. Multistate models should be applied to other nesting beach data for sea turtles to improve survival estimates and in turn the ability to model and manage populations.     

Monitoring tiger populations using intensive search in a capture–recapture framework

Tigers (Panthera tigris) today face multiple threats to their survival in the form of habitat loss, poaching, depletion of wild prey through illegal hunting and loss of connectivity between populations. Monitoring of tigers is crucial to evaluate their status and react adaptively to management problems. Though camera traps are becoming increasingly popular with researchers enumerating cryptic and elusive animals, they have not been embedded in the regular management activities of tiger reserves. Tiger monitoring, though an important part of the management, is usually implemented using the unreliable pugmark approach. Camera trap-based studies are few, usually of short duration, and are generally conducted by individual scientists and organizations. In this study, we integrate photographic mark–recapture with the routine activity of searching and locating tigers for tourist viewing by the park management in meadows of Kanha Tiger Reserve which form a part of the tourism zone. We validate the density estimates from “tiger search approach” against those obtained from camera trapping and radio-telemetry conducted in conjunction in the same area. Tiger density (\( \hat{D} \) (SE [\( \hat{D} \)]) per 100 km² for camera traps and tiger search, respectively, was estimated at 12.0 (1.95) and 12.0 (1.76) when effective trapping area was estimated using the half mean maximum distance moved (½ MMDM), 7.6 (1.94) and 7.5 (1.97) using the home range radius, 7.3 (1.49) and 7.5 (1.97) with the full MMDM, and 8.0 (3.0) and 6.88 (2.39) with the spatial likelihood method in Program DENSITY 4.1. Camera trapping, however, was five times more expensive than the tiger search method. Our study suggests that “tiger search approach” can be used as a regular monitoring tool in the tourism zones of tiger reserves, where often most of the source populations are located.     

Density estimation in a wolverine population using spatial capture–recapture models

Classical closed-population capture–recapture models do not accommodate the spatial information inherent in encounter history data obtained from camera-trapping studies. As a result, individual heterogeneity in encounter probability is induced, and it is not possible to estimate density objectively because trap arrays do not have a well-defined sample area. We applied newly-developed, capture–recapture models that accommodate the spatial attribute inherent in capture–recapture data to a population of wolverines (Gulo gulo) in Southeast Alaska in 2008. We used camera-trapping data collected from 37 cameras in a 2,140-km² area of forested and open habitats largely enclosed by ocean and glacial icefields. We detected 21 unique individuals 115 times. Wolverines exhibited a strong positive trap response, with an increased tendency to revisit previously visited traps. Under the trap-response model, we estimated wolverine density at 9.7 individuals/1,000 km² (95% Bayesian CI: 5.9–15.0). Our model provides a formal statistical framework for estimating density from wolverine camera-trapping studies that accounts for a behavioral response due to baited traps. Further, our model-based estimator does not have strict requirements about the spatial configuration of traps or length of trapping sessions, providing considerable operational flexibility in the development of field studies. © 2011 The Wildlife Society.     

An improved procedure to estimate wolf abundance using non-invasive genetic sampling and capture–recapture mixture models

Non-invasive genetic sampling (NGS) is increasingly used to estimate the abundance of rare or elusive species such as the wolf (Canis lupus), which cannot be directly counted in forested mountain habitats. Wolf individual and familial home ranges are wide, potentially connected by long-range dispersers, and their populations are intrinsically open. Appropriate demographic estimators are needed, because the assumptions of homogeneous detection probability and demographic closeness are violated. We compiled the capture–recapture record of 418 individual wolf genotypes identified from ca. 4,900 non-invasive samples, collected in the northern Italian Apennines from January 2002 to June 2009. We analysed this dataset using novel capture–recapture multievent models for open populations that explicitly account for individual detection heterogeneity (IDH). Overall, the detection probability of the weakly detectable individuals, probably pups, juveniles and migrants (P = 0.08), was ca. six times lower than that of the highly detectable wolves (P = 0.44), probably adults and dominants. The apparent annual survival rate of weakly detectable individuals was lower (Φ = 0.66) than those of highly detectable wolves (Φ = 0.75). The population mean annual finite rate of increase was λ = 1.05 ± 0.11, and the mean annual size ranged from N = 117 wolves in 2003 to N = 233 wolves in 2007. This procedure, combining large-scale NGS and multievent IDH demographic models, provides the first estimates of abundance, multi-annual trend and survival rates for an open large wolf population in the Apennines. These results contribute to deepen our understanding of wolf population ecology and dynamics, and provide new information to implement sound long-term conservation plans.     

Leopard density in post-conflict landscape,Cambodia: Evidence from spatially explicit capture–recapture

Effective conservation of large carnivores requires reliable estimates of population density, often obtained through capture–recapture analysis, in order to prioritize investments and assess conservation intervention effectiveness. Recent statistical advances and development of user-friendly software for spatially explicit capture–recapture (SECR) circumvent the difficulties in estimating effective survey area, and hence density, from capture–recapture data. We conducted a camera-trapping study on leopards (Panthera pardus) in Mondulkiri Protected Forest, Cambodia. We compared density estimates using SECR with those obtained from conventional approaches in which the effective survey area is estimated using a boundary strip width based on observed animal movements. Density estimates from Chao heterogeneity models (3.8 ± SE 1.9 individuals/100 km²) and Pledger heterogeneity models and models accounting for gender-specific capture and recapture rates (model-averaged density 3.9 ± SE 2.9 individuals/100 km²) were similar to those from SECR in program DENSITY (3.6 ± SE 1.0/100 km²) but higher than estimates from Jack-knife heterogeneity models (2.9 ± SE 0.9 individuals/100 km²). Capture probabilities differed between male and female leopards probably resulting from differences in the use of human-made trails between sexes. Given that there are a number of biologically plausible reasons to expect gender-specific variation in capture probabilities of large carnivores, we recommend exploratory analysis of data using models in which gender can be included as a covariate affecting capture probabilities particularly given the demographic importance of breeding females for population recovery of threatened carnivores. © 2011 The Wildlife Society.     

Evaluating the potential biases in carnivore capture–recapture studies associated with the use of lure and varying density estimation techniques using photographic-sampling data of the Malagasy civet

Estimating density of elusive carnivores with capture–recapture analyses is increasingly common. However, providing unbiased and precise estimates is still a challenge due to uncertainties arising from the use of (1) bait or lure to attract animals to the detection device and (2) ad hoc boundary-strip methods to compensate for edge effects in area estimation. We used photographic-sampling data of the Malagasy civet Fossa fossana collected with and without lure to assess the effects of lure and to compare the use of four density estimators which varied in methods of area estimation. The use of lure did not affect permanent immigration or emigration, abundance and density estimation, maximum movement distances, or temporal activity patterns of Malagasy civets, but did provide more precise population estimates by increasing the number of recaptures. The spatially-explicit capture–recapture (SECR) model density estimates ±SE were the least precise as they incorporate spatial variation, but consistent with each other (Maximum likelihood-SECR = 1.38 ± 0.18, Bayesian-SECR = 1.24 ± 0.17 civets/km²), whereas estimates relying on boundary-strip methods to estimate effective trapping area did not incorporate spatial variation, varied greatly and were generally larger than SECR model estimates. Estimating carnivore density with ad hoc boundary-strip methods can lead to overestimation and/or increased uncertainty as they do not incorporate spatial variation. This may lead to inaction or poor management decisions which may jeopardize at-risk populations. In contrast, SECR models free researchers from making subjective decisions associated with boundary-strip methods and they estimate density directly, providing more comparable and valuable population estimates.     

Estimating multiple years,tributary-specific,and overall Atlantic salmon smolt abundance in a large Canadian catchment using capture–mark–recapture experiments

Population monitoring of Atlantic salmon (Salmo salar L.) abundance is an essential element to understand annual stock variability and inform fisheries management processes. Smolts are the life stage marking the transition from the freshwater to the marine phase of anadromous Atlantic salmon. Estimating smolt abundance allows for subsequent inferences on freshwater and marine survival rates. Annual abundances of out-migrating Atlantic salmon smolts were estimated using Bayesian models and an 18-year capture–mark–recapture time series from two to five trapping locations within the Restigouche River (Canada) catchment. Some of the trapping locations were at the outlet of large upstream tributaries, and these sampled a portion of the total out-migrating population of smolts for the watershed, whereas others were located just above the head of tide of the Restigouche River and sampled the entire run of salmon smolts. Due to logistic and environmental conditions, not all trapping locations were operational each year. Additionally, recapture rates were relatively low (<5%), and the absolute number of recaptures was relatively few (most often a few dozen), leading to incoherent and highly uncertain estimates of tributary-specific and whole catchment abundance estimates when the data were modeled independently among trapping locations and years. Several models of increasing complexity were tested using simulated data, and the best-performing model in terms of bias and precision incorporated a hierarchical structure among years on the catchability parameters and included an explicit spatial structure to account for the annual variations in the number of sampled locations within the watershed. When the best model was applied to the Restigouche River catchment dataset, the annual smolt abundance estimates varied from 250,000 to 1 million smolts, and the subbasin estimates of abundance were consistent with the spatial structure of the monitoring programme. Ultimately, increasing the probabilities of capture and the absolute number of recaptures at the different traps will be required to improve the precision and reduce the bias of the estimates of smolt abundance for the entire basin and within subbasins of the watershed. The model and approach provide a significant improvement in the models used to date based on independent estimates of abundance by trapping location and year. Total abundance and relative production in discrete spawning, nesting, or rearing areas provide critical information to appropriately understand and manage the threats to species that can occur at subpopulation spatial scales.     

Estimating local population size of the European Nightjar Caprimulgus europaeus using territory capture–recapture models

Capsule The capture–recapture model M(o) is an efficient way to estimate local population size.

Aims To test if a single capture–recapture modelling approach, combined with a simple survey method, can produce estimates of local population size from a dataset involving large‐scale multi‐observer surveys

Methods We sampled the presence of Nightjars in three separate sessions at three forests. Territory numbers were estimated using conventional territory‐mapping criteria. We ran different capture–recapture models to analyse the detection histories of territories obtained across the three sampling sessions and in the three different forests, using either only registrations of churring birds or all contacts.

Results The capture–recapture model M(o), assuming a constant detection probability, was the most efficient one to produce estimates of local population size. Using only two of the three sampling sessions gave less precise, though quite similar, estimates of the number of territories, with standard deviations representing 5–10% of the estimate values. However, this was reduced to 0.7–3.5%, i.e. three to seven times lower, when using the three sessions.

Conclusion Repeated sampling sessions to map territories can be efficiently used within the capture–recapture model M(o) to estimate detection probability and produce precise estimates of local population size.     

Plant height–crown radius and canopy coverage–density relationships determine above-ground biomass–density relationship in stressful environments

Debate continues in theoretical ecology over whether and why the scaling exponent of biomass–density (M–N) relationship varies along environmental gradients. By developing a novel geometric model with assumptions of allometric growth at the individual level and open canopy at the stand level, we propose that plant height–crown radius and canopy coverage–density relationships determine the above-ground M–N relationship in stressful environments. Results from field investigation along an aridity gradient (from eastern to western China) confirmed our model prediction and showed that the above-ground M–N scaling exponent increased with drought stress. Therefore, the ‘universal’ scaling exponents (−3/2 or −4/3) of the M–N relationship predicted by previous models may not hold for above-ground parts in stressful environments.     

Genetic mark–recapture population estimation in black bears and issues of scale

Abundance estimates for black bears (Ursus americanus) are important for effective management. Recently, DNA technology has resulted in widespread use of noninvasive, genetic capture–mark–recapture (CMR) approaches to estimate populations. Few studies have compared the genetic CMR methods to other estimation methods. We used genetic CMR to estimate the bear population at 2 study sites in northern New Hampshire (Pittsburg and Milan) in 2 consecutive years. We compared these estimates to those derived from traditional methods used by the New Hampshire Fish and Game Department (NHFG) using hunter harvest and mortality data. Density estimates produced with genetic CMR methods were similar both years and were comparable to those derived from traditional methods. In 2006, the estimated number of bears in Pittsburg was 79 (95% CI = 60–98) corresponding to a density of 15–24 (95% CI) bears/100 km²; the 2007 estimate was 83 (95% CI = 67–99; density = 16–24 bears/100 km²). In 2006, the estimated number of bears in Milan was 95 (95% CI = 74–117; density = 16–25 bears/100 km²); the 2007 estimate was 96 (95% CI = 77–114; density = 17–25 bears/100 km²). We found that genetic CMR methods were able to identify demographic variation at a local scale, including a strongly skewed sex ratio (2 M:1 F) in the Milan population. Genetic CMR is a useful tool for wildlife managers to monitor populations of local concern, where abundance or demographic characteristics may deviate from regional estimates. Future monitoring of the Milan population with genetic CMR is recommended to determine if the sex ratio bias continues, possibly warranting a change in local harvest regimes. © 2011 The Wildlife Society.     

Elasticity–density and viscoelasticity–density relationships at the tibia mid-diaphysis assessed from resonant ultrasound spectroscopy measurements

Cortical bone tissue is an anisotropic material characterized by typically five independent elastic coefficients (for transverse isotropy) governing shear and longitudinal deformations in the different anatomical directions. It is well established that the Young’s modulus in the direction of the bone axis of long bones has a strong relationship with mass density. It is not clear, however, whether relationships of similar strength exist for the other elastic coefficients, for they have seldom been investigated, and the results available in the literature are contradictory. The objectives of the present work were to document the anisotropic elastic properties of cortical bone at the tibia mid-diaphysis and to elucidate their relationships with mass density. Resonant ultrasound spectroscopy (RUS) was used to measure the transverse isotropic stiffness tensor of 55 specimens from 19 donors. Except for Poisson’s ratios and the non-diagonal stiffness coefficient, strong linear correlations between the different elastic coefficients \((0.7 < {r^{2}} < 0.99)\) and between these coefficients and density \((0.79 < {r^{2}} < 0.89)\) were found. Comparison with previously published data from femur specimens suggested that the strong correlations evidenced in this study may not only be valid for the mid-tibia. RUS also measures the viscous part of the stiffness tensor. An anisotropy ratio close to two was found for damping coefficients. Damping increased as the mass density decreased. The data suggest that a relatively accurate estimation of all the mid-tibia elastic coefficients can be derived from mass density. This is of particular interest (1) to design organ-scale bone models in which elastic coefficients are mapped according to Hounsfield values from computed tomography scans as a surrogate for mass density and (2) to model ultrasound propagation at the mid-tibia, which is an important site for the in vivo assessment of bone status with axial transmission techniques.     

Theoretical investigation of cyromazine tautomerism using density functional theory and Møller–Plesset perturbation theory methods

A computational chemistry analysis of six unique tautomers of cyromazine, a pesticide used for fly control, was performed with density functional theory (DFT) and canonical second-order Møller–Plesset perturbation theory (MP2) methods to gain insight into the contributions of molecular structure to detection properties. Full geometry optimisation using the 6-311++G** basis set provided energetic properties, natural charges, frontier orbitals and vibrational modes. Excitation energies were obtained using time-dependent DFT. Hydrogen location and bond order contribute significantly to the electronic properties. The common cyromazine tautomer possesses the lowest energy, highest band gap energy and highest excitation energy. B3LYP/6-31G** dynamics simulations indicate each tautomer possesses a stable structure with limited rotation about the single bonds. Tautomerisation involving intramolecular hydrogen transfer influences the natural charges of neighbouring atoms and the frontier orbital properties. The excitation energies are highly correlated with band gap energies of the frontier orbitals. The calculated infrared and Raman spectra are suitable for vibrational assignments associated with the chemical structure. The tautomeric forms of cyromazine possess similar spatial properties and significant variation in electronic properties.     

Sources of variability in spotted owl population growth rate: testing predictions using long-term mark–recapture data

For long-lived iteroparous vertebrates that annually produce few young, life history theory predicts that reproductive output (R) and juvenile survival should influence temporal variation in population growth rate (λ) more than adult survival does. We examined this general prediction using 15 years of mark–recapture data from a population of California spotted owls (Strix occidentalis occidentalis). We found that survival of individuals ≥1 year old (ϕ) exhibited much less temporal variability , where CV is coefficient of variation, than R and that R was strongly influenced by environmental stochasticity. Although λ was most sensitive ( ; log-transformed sensitivity) to ϕ and much less sensitive to either R or juvenile survival (survival rate of owls from fledging to 1 year old; ), we estimated that R contributed as much as ϕ to the observed annual variability in λ. The contribution of juvenile survival to variability in λ was proportional to its These results are consistent with the hypothesis that natural selection may have favored the evolution of longevity in spotted owls as a strategy to increase the probability of experiencing favorable years for reproduction. Our finding that annual weather patterns that most affected R (temperature and precipitation during incubation) and ϕ (conditions during winter related to the Southern Oscillation Index) were equally good at explaining temporal variability in λ supports the conclusion that R and ϕ were equally responsible for variability in λ. Although currently accepted conservation measures for spotted owl populations attempt to enhance survival, our results indicated that conservation measures that target R may be as successful, as long as actions do not reduce ϕ.