Time Series Of Population Size Research Articles

Multiple‐model stock assessment frameworks for precautionary management and conservation on fishery‐targeted coastal dolphin populations off Japan

Abstract Stock assessment approaches are often oversimplified due to lack of biological knowledge and insufficient data. In spite of world‐wide attention, fishery‐targeted coastal dolphin species in Japan have lacked in‐depth quantitative stock assessments because of limited time series of population size and an absence of associated biological information. We consequently developed integrated population models that analysed multiple sources of data simultaneously with published biological information within a Bayesian framework. We estimate population status and trends for three main species targeted by fisheries, bottlenose dolphins Tursiops truncatus, Risso's dolphins Grampus griseu, and short‐finned pilot whales Globicephala macrorhynchus, using single‐species age‐aggregated and age‐structured population dynamics models. Models were fit to absolute abundance estimates from systematic line‐transect surveys, four series of abundance indices calculated from fisher's logbooks, and historical catch records. Published biological information was used to develop prior distributions for the biological parameters. We assessed the possible effects of ecological disturbance and competition using state‐space and multispecies models. The multispecies model was selected by the model selection both for the age‐aggregated and the age‐structured approaches. Single‐species assessments found that population size declined 4.2% (Risso's dolphin) to 8.0% (bottlenose dolphin) for three species since the late 1800s based on median posterior values, while the state‐space and multispecies models found that environmental disturbance and an interaction among species could have reduced population size more substantially. Policy implications. Simple single‐species models are often used to provide conservation and management advice for wild animals but, in this case, results from such models are overly optimistic because they overlook important ecological process. In contrast, current population status could be less favorable if environmental disturbance and interspecific competition actually control population dynamics. Even if that is not the case, considering ecological process in the model will provide more precautionary ways. Our approach of combining multiple modelling frameworks is applicable to many other management systems, and offers increased confidence in estimated status and trends over assessments that consider only a single model.

King Penguin populations increase on South Georgia but explanations remain elusive

While dramatic increases in populations of King Penguins (Aptenodytes patagonicus) have been documented throughout their range, population changes on the island of South Georgia have not been assessed. We reconstructed time series of population size for six major colonies across South Georgia using historical data stretching back to 1883 and new population estimates derived from direct on-the-ground censuses and oblique, high-resolution digital photographs. We find evidence for a significant increase in the population of King Penguins at all colonies examined over the 124 years of available survey data. We discuss our findings in the context of four established hypotheses explaining King Penguin population growth: (1) favorable changes in the pelagic food web; (2) climate forcing; (3) greater availability of breeding habitat; and (4) the cessation of harvesting. While we do find evidence that glacial retreat may have increased suitable breeding habitat at some colonies and facilitated population expansion, glacial retreat is not associated with all of South Georgia’s growing populations. Local anomalies in sea surface temperature have increased in parallel with King Penguin population growth rate, suggesting that climate forcing may contribute to colony growth, but a complete explanation for the island’s rapidly growing King Penguin population remains unclear.

Rapid Assessment and Stochastic Modeling to Avert Extinction in the Endangered Amargosa Vole

The Amargosa vole, Microtus californicus scirpensis, is an endangered microtine rodent obligately found in marshes near the Amargosa River, Mojave Desert in California. Very few data to inform modeling and adaptive management. If interventions are postponed until data are available, the vole could go extinct in the interim, making a more flexible modeling approach imperative. The voles face threats from environmental and demographic stochasticity, Allee effects, inbreeding, genetic drift, intense predation, and disease. The modeling approach used here is based on diffusion methods for time series of population size constrained by a carrying capacity, focusing on environmental stochasticity and the probability that the variance in population growth could allow the population to encounter the lower “absorbing” boundary and go extinct. We parameterized the model with Amargosa vole data that stand as Bayesian “priors” for carrying capacity, until more data can be obtained and allow us to refine a more accurate estimate. There are no multiple-year time series data or data for most demographic characteristics of the Amargosa vole, forcing us to look to California vole time series as a Bayesian prior. Our analysis indicated expected 20-24 years to extinction and 4-5% probability of extinction in one year due to environmental stochasticity: the real time could even be shorter if there is significant demographic stochasticity. Implementation of management based on best available modeling will be crucial to avert this risk. This modeling approach also has merit for other species in urgent need of management even in the face of early projects lacking mature data sets.

The impact of alternative harvesting strategies in a resource–consumer metapopulation

Summary1. The majority of our knowledge of harvested populations has been drawn from studies on single‐species occupying continuous landscapes. Population dynamics in spatially structured landscapes are markedly different from those in continuous habitats. We investigate the effects of several harvesting strategies on the metapopulation dynamics of the bruchid beetle Callosobruchus maculatus and its parasitoid Anisopteromalus calandrae, when locally extinction prone populations of bruchids were harvested. By harvesting the resource in this closed resource–consumer interaction, we could examine the scenario where humans and natural predators share a common resource.2. Using population‐level models in single and coupled‐patch systems, simulations were run to estimate sustainable harvesting levels for each harvesting strategy. These harvesting levels were then implemented in experimental metapopulation microcosms. Experiments were run for multiple generations and long‐term time series of population size and harvest yield were collected.3. Controversially, harvesting resulted in larger regional population sizes in harvested metapopulations than in unharvested metapopulations. Similarly, conservative harvesting strategies such as fixed escapement harvesting and harvesting with refuges resulted in smaller population sizes than fixed quota or fixed proportion harvesting strategies. Fixed proportion harvesting gave rise to the largest population sizes, fewest local extinctions and largest yields. Assuming both species are of ecological importance, fixed proportion is therefore the optimal harvesting strategy for this model system.4. Synthesis and applications. We demonstrate that, under certain conditions, increasing local mortality can increase population sizes. This ‘hydra effect’ may be caused by the advantage of higher rates of local population turnover for dispersive species in patchy landscapes, or due to the interruption of overcompensatory density‐dependence in the host populations. These results are of particular relevance both in the development of sustainable harvesting policies in multi‐species communities or, conversely, the control of pest species inhabiting spatially structured landscapes. We have shown that predictive models can be a useful tool in the estimation of sustainable harvesting limits where no a priori knowledge of the system exists. We also demonstrate that spatial structure, the effects of interspecific interactions and knowledge of density‐dependent population dynamics must be included in the generation of sustainable harvesting theory.

The Allure of the Few

The Allure of the Few

Demographic processes in colonizing populations of isard (Rupicapra pyrenaica) and ibex (Capra ibex)

AbstractRates of increase, survival and reproduction were studied in two re‐introduced populations of mountain ungulates, the Pyrenean chamois (also named isard, Rupicapra pyrenaica) and the ibex (Capra ibex) in the French Alps. The populations were monitored from 1983 to 1998 (ibex) or 1984 to 1999 (isard) using capture, marking and resighting of individuals. Population rates of increase were estimated during the colonizing phase from: (1) a time series of estimates of population size; (2) projection matrices based on rates of survival and fecundity. Both populations had exponential rates of increase, with annual multiplication rates of 1.28 for isard and 1.30 for ibex. Age of first reproduction was 2 years in both species, with 77% of females breeding at this age in isard and 43% in ibex. From 3 years of age onwards, 90% of isard and 87% of ibex females bred each year. Survival rates of adult females, estimated using capture–recapture models, equalled 0.94 for isard and 0.98 for ibex, whatever the age and year. The projection matrix led to a slightly lower asymptotic multiplication rate than the time series of population size. Despite adult body size of the ibex being about twice that of the isard, no difference was detected in the intrinsic rate of increase between the two species. This supported the hypotheses of homogeneous life‐history traits among ungulates, varying little with body size.

Extinction Risk of a Density-dependent Population Estimated from a Time Series of Population Size

Environmental threats, such as habitat size reduction or environmental pollution, may not cause immediate extinction of a population but shorten the expected time to extinction. We develop a method to estimate the mean time to extinction for a density-dependent population with environmental fluctuation. We first derive a formula for a stochastic differential equation model (canonical model) of a population with logistic growth with environmental and demographic stochasticities. We then study an approximate maximum likelihood (AML) estimate of three parameters (intrinsic growth rater , carrying capacity K, and environmental stochasticity σ2e) from a time series of population size. The AML estimate of r has a significant bias, but by adopting the Monte Carlo method, we can remove the bias very effectively (bias-corrected estimate). We can also determine the confidence interval of the parameter based on the Monte Carlo method. If the length of the time series is moderately long (with 40–50 data points), parameter estimation with the Monte Carlo sampling bias correction has a relatively small variance. However, if the time series is short (less than or equal to 10 data points), the estimate has a large variance and is not reliable. If we know the intrinsic growth rater , however, the estimate of K and σ2eand the mean extinction timeT are reliable even if only a short time series is available. We illustrate the method using data for a freshwater fish, Japanese crucian carp (Carassius auratus subsp.) in Lake Biwa, in which the growth rate and environmental noise of crucian carp are estimated using fishery records.