Random Temporary Emigration Research Articles

Killer whale (Orcinus orca) population dynamics in response to a period of rapid ecosystem change in the eastern North Atlantic.

This study investigates survival and abundance of killer whales (Orcinus orca) in Norway in 1988–2019 using capture–recapture models of photo‐identification data. We merged two datasets collected in a restricted fjord system in 1988–2008 (Period 1) with a third, collected after their preferred herring prey shifted its wintering grounds to more exposed coastal waters in 2012–2019 (Period 2), and investigated any differences between these two periods. The resulting dataset, spanning 32 years, comprised 3284 captures of 1236 whales, including 148 individuals seen in both periods. The best‐supported models of survival included the effects of sex and time period, and the presence of transients (whales seen only once). Period 2 had a much larger percentage of transients compared to Period 1 (mean = 30% vs. 5%) and the identification of two groups of whales with different residency patterns revealed heterogeneity in recapture probabilities. This caused estimates of survival rates to be biased downward (females: 0.955 ± 0.027 SE, males: 0.864 ± 0.038 SE) compared to Period 1 (females: 0.998 ± 0.002 SE, males: 0.985 ± 0.009 SE). Accounting for this heterogeneity resulted in estimates of apparent survival close to unity for regularly seen whales in Period 2. A robust design model for Period 2 further supported random temporary emigration at an estimated annual probability of 0.148 (± 0.095 SE). This same model estimated a peak in annual abundance in 2015 at 1061 individuals (95% CI 999–1127), compared to a maximum of 731 (95% CI 505–1059) previously estimated in Period 1, and dropped to 513 (95% CI 488–540) in 2018. Our results indicate variations in the proportion of killer whales present of an undefined population (or populations) in a larger geographical region. Killer whales have adjusted their distribution to shifts in key prey resources, indicating potential to adapt to rapidly changing marine ecosystems.

Using mark-recapture methods to estimate population size and survival of pyjama sharks Poroderma africanum in Mossel Bay, South Africa

The pyjama shark Poroderma africanum (family Scyliorhinidae) is endemic to coastal waters of South Africa but its population characteristics are poorly known. This study aims to estimate baseline demographic parameters for P. africanum in Mossel Bay. We applied mark-recapture methods following Pollock’s robust design (PRD) and Cormack–Jolly–Seber (CJS) models, using five-year tag-recapture data and one-year acoustic-telemetry data, respectively. Estimates of abundance, survival, capture probabilities and temporary emigration were obtained using these models. The PRD model indicated random temporary emigration (0.955 period–1 [95% CI 0.755–0.993]), constant survival, and season-varying capture and recapture probabilities with a negative behavioural response to first capture (β = −5.34 [−6.89 to −3.80]). Abundance estimates ranged from 11 (10.01–13.21) to 53 (52.05–56.82) sharks in Mossel Bay. The CJS model indicated constant survival (0.271 y–1 [95% CI 0.0–0.75]) and sex-independent probabilities of being captured at least once annually (1.0 y–1 for both sexes). This study provides the first demographic information for the management of this population. Further studies should utilise larger sample sizes and more complex models, and investigate specific management options.

Identifying key demographic parameters of a small island-associated population of Indo-Pacific bottlenose dolphins (Reunion, Indian Ocean).

Photo-identification surveys of Indo-Pacific bottlenose dolphins were conducted from 2009 to 2014 off Reunion Island (55°E33’/21°S07’), in the Indian Ocean. Robust Design models were applied to produce the most reliable estimate of population abundance and survival rate, while accounting for temporary emigration from the survey area (west coast). The sampling scheme consisted of a five-month (June–October) sampling period in each year of the study. The overall population size at Reunion was estimated to be 72 individuals (SE = 6.17, 95%CI = 61–85), based on a random temporary emigration (γ”) of 0.096 and a proportion of 0.70 (SE = 0.03) distinct individuals. The annual survival rate was 0.93 (±0.018 SE, 95%CI = 0.886–0.958) and was constant over time and between sexes. Models considering gender groups indicated different movement patterns between males and females. Males showed null or quasi-null temporary emigration (γ” = γ’ < 0.01), while females showed a random temporary emigration (γ”) of 0.10, suggesting that a small proportion of females was outside the survey area during each primary sampling period. Sex-specific temporary migration patterns were consistent with movement and residency patterns observed in other areas. The Robust Design approach provided an appropriate sampling scheme for deriving island-associated population parameters, while allowing to restrict survey effort both spatially (i.e. west coast only) and temporally (five months per year). Although abundance and survival were stable over the six years, the small population size of fewer than 100 individuals suggested that this population is highly vulnerable. Priority should be given to reducing any potential impact of human activity on the population and its habitat.

A Robust Design Capture-Recapture Analysis of Abundance, Survival and Temporary Emigration of Three Odontocete Species in the Gulf of Corinth, Greece.

While the Mediterranean Sea has been designated as a Global Biodiversity Hotspot, assessments of cetacean population abundance are lacking for large portions of the region, particularly in the southern and eastern basins. The challenges and costs of obtaining the necessary data often result in absent or poor abundance information. We applied capture-recapture models to estimate abundance, survival and temporary emigration of odontocete populations within a 2,400 km2 semi-enclosed Mediterranean bay, the Gulf of Corinth. Boat surveys were conducted in 2011–2015 to collect photo-identification data on striped dolphins Stenella coeruleoalba, short-beaked common dolphins Delphinus delphis (always found together with striped dolphins in mixed groups) and common bottlenose dolphins Tursiops truncatus, totaling 1,873 h of tracking. After grading images for quality and marking distinctiveness, 23,995 high-quality photos were included in a striped and common dolphin catalog, and 2,472 in a bottlenose dolphin catalog. The proportions of striped and common dolphins were calculated from the photographic sample and used to scale capture-recapture estimates. Best-fitting robust design capture-recapture models denoted no temporary emigration between years for striped and common dolphins, and random temporary emigration for bottlenose dolphins, suggesting different residency patterns in agreement with previous studies. Average estimated abundance over the five years was 1,331 (95% CI 1,122–1,578) striped dolphins, 22 (16–32) common dolphins, 55 (36–84) “intermediate” animals (potential striped x common dolphin hybrids) and 38 (32–46) bottlenose dolphins. Apparent survival was constant for striped, common and intermediate dolphins (0.94, 95% CI 0.92–0.96) and year-dependent for bottlenose dolphins (an average of 0.85, 95% CI 0.76–0.95). Our work underlines the importance of long-term monitoring to contribute reliable baseline information that can help assess the conservation status of wildlife populations.

Reducing bias in survival under nonrandom temporary emigration.

Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard survival parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration, unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates, and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified; nonetheless, there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable nonrandom temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data were effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naive constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, although still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several sources of data improved parameter estimates and reduced terminal bias. Efforts to incorporate or acquire such data should be considered by researchers and wildlife managers, especially in the years leading up to status assessments of species of interest. Simulation modeling is a very cost-effective method to explore the potential impacts of using different sources of data to produce high-quality demographic data to inform management.

Modeling the effects of life-history traits on estimation of population parameters for a cryptic stream species

Estimating demographic values and rates for populations of cryptic stream species frequently is difficult because of prohibitively low capture probabilities. When assessing cryptic populations, researchers often are forced to make simplifying assumptions that could alter their conclusions about a population. We constructed models based on different assumptions about cohort structure, behavioral responses to capture, temporary emigration, and survival in a cryptic, larval population of red salamanders (Pseudotriton ruber) and fitted models to capture-mark-recapture data. Overall, models based on 2 cohorts were favored over models based on 1 cohort. Models based on assumptions of constant survival, behavioral responses to capture, and random temporary emigration were ranked higher than models lacking these assumptions. Consistent behavioral responses to capture demonstrated that using uncorrected counts to assess trends for this, and perhaps other larval amphibian populations, yields misleading results. Counts that are not corrected for trap-shy behavior may inherently show negative temporal trends. Temporary emigration was a critical assumption when describing larval salamander demography because only 27% of the larvae were active on the surface (the rest were in substratum habitats). Our study demonstrates the importance of making appropriate assumptions about demographic parameters and shows how population models can quantify aspects of the natural history of cryptic species.

Abundance, survival and temporary emigration of bottlenose dolphins (Tursiops sp.) off Useless Loop in the western gulf of Shark Bay, Western Australia

Capture–recapture models were used to provide estimates of abundance, apparent survival and temporary emigration of Indo-Pacific bottlenose dolphins (Tursiops sp.) in a 226-km2 study area off Useless Loop in the western gulf of Shark Bay, Western Australia. Photo-identification data were collected during boat-based surveys in Austral autumn to early spring (April–September) from 2007 to 2011. Abundance estimates varied from 115 (s.e. 5.2, 95% CI 105–126) individuals in 2008 to 208 (s.e. 17.3, 95% CI 177–245) individuals in 2010. The variability in abundance estimates is likely to be a reflection of how individuals used the study area, rather than fluctuations in true population size. The best fitting capture–recapture model suggested a random temporary emigration pattern and, when coupled with relatively high temporary emigration rates (0.33 (s.e. 0.07) – 0.66 (s.e. 0.05)) indicated that the study area did not cover the entire ranges of the photo-identified dolphins. Apparent survival rate is a product of true survival and permanent emigration and was estimated annually at 0.95 (s.e. 0.02). Since permanent emigration from the study area is unlikely, true survival was estimated to be close to 0.95. This study provides a robust baseline for future comparisons of dolphin demographics, which may be of importance should climate change or increasing anthropogenic activity affect this population.

ASSESSING TIGER POPULATION DYNAMICS USING PHOTOGRAPHIC CAPTURE–RECAPTURE SAMPLING

Although wide-ranging, elusive, large carnivore species, such as the tiger, are of scientific and conservation interest, rigorous inferences about their population dynamics are scarce because of methodological problems of sampling populations at the required spatial and temporal scales. We report the application of a rigorous, noninvasive method for assessing tiger population dynamics to test model-based predictions about population viability. We obtained photographic capture histories for 74 individual tigers during a nine-year study involving 5725 trap-nights of effort. These data were modeled under a likelihood-based, "robust design" capture-recapture analytic framework. We explicitly modeled and estimated ecological parameters such as time-specific abundance, density, survival, recruitment, temporary emigration, and transience, using models that incorporated effects of factors such as individual heterogeneity, trap-response, and time on probabilities of photo-capturing tigers. The model estimated a random temporary emigration parameter of gamma" = gamma' = 0.10 +/- 0.069 (values are estimated mean +/- SE). When scaled to an annual basis, tiger survival rates were estimated at S = 0.77 +/- 0.051, and the estimated probability that a newly caught animal was a transient was tau = 0.18 +/- 0.11. During the period when the sampled area was of constant size, the estimated population size N(t) varied from 17 +/- 1.7 to 31 +/- 2.1 tigers, with a geometric mean rate of annual population change estimated as lambda = 1.03 +/- 0.020, representing a 3% annual increase. The estimated recruitment of new animals, B(t), varied from 0 +/- 3.0 to 14 +/- 2.9 tigers. Population density estimates, D, ranged from 7.33 +/- 0.8 tigers/100 km2 to 21.73 +/- 1.7 tigers/100 km2 during the study. Thus, despite substantial annual losses and temporal variation in recruitment, the tiger density remained at relatively high levels in Nagarahole. Our results are consistent with the hypothesis that protected wild tiger populations can remain healthy despite heavy mortalities because of their inherently high reproductive potential. The ability to model the entire photographic capture history data set and incorporate reduced-parameter models led to estimates of mean annual population change that were sufficiently precise to be useful. This efficient, noninvasive sampling approach can be used to rigorously investigate the population dynamics of tigers and other elusive, rare, wide-ranging animal species in which individuals can be identified from photographs or other means.

ESTIMATING SURVIVAL AND TEMPORARY EMIGRATION IN THE MULTISTATE CAPTURE–RECAPTURE FRAMEWORK

The open population Cormack-Jolly-Seber (CJS) capture–mark–recapture model for estimating survival allows for random temporary emigration from the sampling area, but Markovian temporary emigration can bias estimates of survival. We explore a multistate capture–recapture model that has been proposed for coping with Markovian temporary emigration. We provide a comprehensive assessment of the performance of this model using computer algebra and simulation. We found that most model parameters were identifiable unless survival, emigration, and immigration were all time dependent. Simulation results showed that intrinsically identifiable parameters were estimated without bias and that precision of survival estimates was always high. When temporary emigration was Markovian, precision of estimates of emigration, immigration, and recapture probabilities was acceptable; otherwise it was not. Test component 2.Ct of the goodness-of-fit test for the CJS model had good power to detect Markovian temporary emigration. We conclude that the multistate model works well when temporary emigration is Markovian (i.e., when the CJS model should not be used) and when survival and recapture probabilities are high.

Adult survival and temporary emigration in the common toad

In vertebrates exhibiting intermittent breeding, breeding activity is a factor of critical importance in capture–recapture studies using data from individually marked animals. Nonbreeders can be absent from locations used by breeders and can be considered "temporary emigrants". We addressed the influence of sex on survival in common toads, Bufo bufo (L., 1758), using the Joly–Seber model and the existance of temporary emigration in male common toads by assessing trap-dependence and by conducting a robust design analysis. We addressed the hypothesis that the probability of the presence of an individual in the study area depends on the presence of the individual the year before (i.e., that transitions between reproductive states are a first-order Markovian process). Results provided support for the hypotheses of random temporary emigration, of sex-specific differences in survival, and of the presence of "transients" in males. Females had intermediate survival compared with the groups of "transients + residents" and "resident" males. Females had lower recapture probability under the Joly–Seber model, which may be interpreted as evidence of lower breeding probability or lower detectability of breeding females. Behaviour may explain this difference in that females may attend ponds for shorter periods. This may be common in species where females aggregate to seek fertilization and lay eggs in locations attended by males and in species with a "resource-based lek" mating system.

ESTIMATING DETECTION PROBABILITY PARAMETERS FOR PLETHODON SALAMANDERS USING THE ROBUST CAPTURE–RECAPTURE DESIGN

Recent concern over global amphibian population declines has highlighted a need for more extensive, rigorous monitoring programs. Two sources of variation, spatial variation and variation in detection probability, make the design and implementation of effective monitoring programs difficult. We used Pollock's robust design in a 3-year capture–recapture study to estimate detection probability and temporary emigration for Plethodon salamanders in Great Smoky Mountains National Park (Tennessee/North Carolina), USA. We used 12 competing models to determine the importance of temporary emigration, and we explored temporal and behavioral effects on conditional capture probabilities. The top 4 models all included random temporary emigration, and Akaike model weights indicated that this parameter was the most important. Models that contained behavioral effects in capture probabilities were selected more often than models with equal capture probabilities for marked and previously unmarked individuals. The “best” model contained random emigration and behavioral effects and was selected 4 times as often as any other model. When we included Markovian emigration, the probability of emigrating from the surface usually was less than the probability of remaining an emigrant (73% of site-years). Markovian emigration estimates often were similar and always had overlapping confidence intervals, thus the Markovian model rarely was chosen over the random emigration models (only 9.6% of site-years). Our study is the first to formally estimate temporary emigration in terrestrial salamander populations, and our results verify that significant proportions of terrestrial salamander populations are subterranean. We determined that the probability of capturing salamanders on the surface may also vary temporally within a sampling season. Therefore, we caution against using unadjusted count indices to compare salamander populations over time or space unless detection probabilities are estimated. Temporary emigration models will improve abundance estimates when a large proportion of the population is unavailable for capture during a given sampling period.

Estimating Temporary Migration Using the Robust Design

One of the basic assumptions central to the analysis of capture-recapture experiments is that all marked animals remain in the population under study for the duration of the sampling, or if they migrate out of the population they do so permanently. Burnham (1993, in Marked Individuals in the Study of Bird Populations,199-213), Kendall and Nichols (1995, Applied Statistics 22, 751-762), and Kendall, Nichols, and Hines (in press) showed that completely random temporary emigration influences only estimates of the probability of capture, these now estimating the product of the temporary emigration rate and the conditional probability of capture given the animal remains in the population. Estimates of abundance or survival that refer to the entire population, including the temporary emigrants, remain unaffected. Kendall et al. (in press) further showed that Pollock's (1982, Journal of Wildlife Management 46, 757-760) robust design could be used to estimate the temporary emigration rate when the population was assumed closed during the secondary samples. We generalize this result to allow animals to enter and leave the population during the secondary samples. We apply the results to a study of Grey Seals and perform simulation experiments to assess the robustness of our estimator to errors in field identification of brands and other violations of our assumptions.

ESTIMATING TEMPORARY EMIGRATION USING CAPTURE–RECAPTURE DATA WITH POLLOCK’S ROBUST DESIGN

Statistical inference for capture–recapture studies of open animal populations typically relies on the assumption that all emigration from the studied population is permanent. However, there are many instances in which this assumption is unlikely to be met. We define two general models for the process of temporary emigration: completely random and Markovian. We then consider effects of these two types of temporary emigration on Jolly–Seber estimators and on estimators arising from the full-likelihood approach to robust design data. Capture–recapture data arising from Pollock’s robust design provide the basis for obtaining unbiased estimates of demographic parameters in the presence of temporary emigration, and for estimating the probability of temporary emigration. We present a likelihood-based approach to dealing with temporary emigration that permits estimation under different models of temporary emigration and yields tests for completely random and Markovian emigration. In addition, we use the relationship between capture probability estimates based on closed and open models under completely random temporary emigration to derive three ad hoc estimators for the probability of temporary emigration. Two of these should be especially useful in situations where capture probabilities are heterogeneous among individual animals. Ad hoc and full-likelihood estimators are illustrated for small-mammal capture–recapture data sets. We believe that these models and estimators will be useful for testing hypotheses about the process of temporary emigration, for estimating demographic parameters in the presence of temporary emigration, and for estimating probabilities of temporary emigration. These latter estimates are frequently of ecological interest as indicators of animal movement and, in some sampling situations, as direct estimates of breeding probabilities and proportions.

On the use of secondary capture-recapture samples to estimate temporary emigration and breeding proportions

The use of the Cormack-Jolly-Seber model under a standard sampling scheme of one sample per time period, when the Jolly-Seber assumption that all emigration is permanent does not hold, leads to the confounding of temporary emigration probabilities with capture probabilities. This biases the estimates of capture probability when temporary emigration is a completely random process, and both capture and survival probabilities when there is a temporary trap response in temporary emigration, or it is Markovian. The use of secondary capture samples over a shorter interval within each period, during which the population is assumed to be closed (Pollock's robust design), provides a second source of information on capture probabilities. This solves the confounding problem, and thus temporary emigration probabilities can be estimated. This process can be accomplished in an ad hoc fashion for completely random temporary emigration and to some extent in the temporary trap response case, but modelling the complete sam...