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Fort Nelson, Canada

Gervasi V.,University of Rome La Sapienza | Ciucci P.,University of Rome La Sapienza | Boulanger J.,Integrated Ecological Research | Randi E.,Laboratorio Of Genetica | Boitani L.,University of Rome La Sapienza
Biological Conservation | Year: 2012

When dealing with small populations of elusive species, capture-recapture methods suffer from sampling and analytical limitations, making abundance assessment particularly challenging. We present an empirical and theoretical evaluation of multiple data source sampling as a flexible and effective way to improve the performance of capture-recapture models for abundance estimation of small populations. We integrated three data sources to estimate the size of the relict Apennine brown bear (Ursus arctos marsicanus) population in central Italy, and supported our results with simulations to assess the robustness of multiple data source capture-recapture models to violations of main assumptions. During May-August 2008, we non-invasively sampled bears using systematic hair traps on a grid of 41 5×5km cells, moving trap locations between five sampling sessions. We also live-trapped, ear-tagged, and genotyped 17 bears (2004-2008), and integrated resights of marked bears and family units (July-September 2008) into a multiple data source capture-recapture dataset. Population size was estimated at 40 (95% CI=37-52) bears, with a corresponding closure-corrected density of 32 bears/1000km 2 (95% CI=28-36). Given the average capture probability we obtained with all data sources combined (p̂=0.311), simulations suggested that the expected degree of correlation among data sources did not seriously affect model performance, with expected level of bias <5%. Our results refine previous simulation work on larger populations, cautioning on the combined effect of lack of independence and low capture probability in application of multiple data source sampling to very small populations (N<100). © 2012 Elsevier Ltd. Source

Boulanger J.,Integrated Ecological Research | Poole K.G.,Aurora Wildlife Research | Gunn A.,368 Roland Road | Wierzchowski J.,Consulting Inc.
Wildlife Biology | Year: 2012

Wildlife species may respond to industrial development with changes in distribution. However, discerning a response to development from differences in habitat selection is challenging. Since the early 1990s, migratory tundra Bathurst caribou Rangifer tarandus groenlandicus in the Canadian Arctic have been exposed to the construction and operation of two adjacent open-pit mines within the herd's summer range. We developed a statistical approach to directly estimate the zone of influence (area of reduced caribou occupancy) of the mines during mid-July-mid-October. We used caribou presence recorded during aerial surveys and locations of satellite-collared cow caribou as inputs to a model to account for patterns in habitat selection as well as mine activities. We then constrained the zone of influence curve to asymptote, such that the average distance from the mine complex where caribou habitat selection was not affected by the mine could be estimated. During the operation period for the two open-pit mines, we detected a 14-km zone of influence from the aerial survey data, and a weaker 11-km zone from the satellite-collar locations. Caribou were about four times more likely to select habitat at distances greater than the zone of influence compared to the two-mine complex, with a gradation of increasing selection up to the estimated zone of influence. Caribou are responding to industrial developments at greater distances than shown in other areas, possibly related to fine dust deposition from mine activities in open, tundra habitats. The methodology we developed provides a standardized approach to estimate the spatial impact of stressors on caribou or other wildlife species. © 2012 Wildlife Biology, NKV. Source

Dumond M.,Environment Canada | Boulanger J.,Integrated Ecological Research | Paetkau D.,Wildlife Genetics International
Wildlife Society Bulletin | Year: 2015

Assessing grizzly bears' (Ursus arctos) abundance in the Arctic has been challenging because of the large scale of their movements and the remoteness of field locations. We modified a post sampling method used for wolverines (Gulo gulo) to allow collection of hair samples from grizzly bears in the Canadian tundra. We deployed 1 post/cell in a sampling grid of 393 10 × 10-km cells sampled in 2008 and 2009 for two 14-day sessions in July-August of both years. We then compared density estimates from mark-recapture estimators that used telemetry data from previous years with spatially explicit mark-recapture models that used only genetic detections. Over the 2 years of sampling, we detected 98 female and 81 male grizzly bears. We found that the DNA degradation rate was related to collection interval and the number of days between rainfall events and sample collection. Estimates of density were in the order of 5 bears/1,000 km2. The estimates from the 2 methods were statistically similar, but spatially explicit estimates were more precise than those using radiocollar data. Our results provide the first demonstration of the viability of posts as hair-snagging stations to obtain DNA from grizzly bears, and of spatially explicit mark-recapture methods to estimate population size and density for grizzly bears above the tree line. © 2015 The Wildlife Society. © The Wildlife Society, 2015. Source

Gervasi V.,University of Rome La Sapienza | Ciucci P.,University of Rome La Sapienza | Davoli F.,Istituto Nazionale per la Fauna Selvatica | Boulanger J.,Integrated Ecological Research | And 2 more authors.
Conservation Genetics | Year: 2010

It is often difficult to determine optimal sampling design for non-invasive genetic sampling, especially when dealing with rare or elusive species depleted of genetic diversity. To address this problem, we ran a hair-snag pilot study on the remnant Apennine brown bear population. We used occupancy models to estimate the performance of an improved field protocol, a meta-analysis approach to indirectly model capture probability, and simulations to evaluate the effect of genotyping errors on the accuracy of capture-recapture population estimates. In spring 2007 we collected 70 bear hair samples in 15 5 × 5 km cells, using 5 10-day trapping sessions. Bear detectability was higher in 2007 than in a previous attempt on the same population in 2004, reflecting improved field protocols and sampling design. However, individual capture probability was 0.136 (95% CI = 0.120-0.152), still below the minimum requirements of capture-mark-recapture closed population models. We genotyped hair samples (n = 63) at 9 microsatellite loci, obtaining 94% Polymerase Chain Reaction success, and 13 bear genotypes. Estimated P IDsib was 0.00594, and per-genotype error rate was 0.13, corresponding to a 99% probability of correct individual identification. Simulation studies showed that the effect of non-corrected or filtered genetic errors on the accuracy of population estimates was negligible only when individual capture probability was >0.2. Our results underline how the interaction among field protocols, sampling strategies and genotyping errors may affect the accuracy of DNA-based estimates of small and genetically depleted populations, and warned us about the feasibility of a survey using only traditional hair-snag sampling. In this and similar cases, indications from pilot studies can provide cost-effective means to evaluate the efficiency of designed sampling and modelling procedures. © 2010 Springer Science+Business Media B.V. Source

Boulanger J.,Integrated Ecological Research | Gunn A.,368 Roland Road | Adamczewski J.,Natural Resources Canada | Croft B.,Natural Resources Canada
Journal of Wildlife Management | Year: 2011

The Bathurst herd of barren-ground caribou (Rangifer tarandus groenlandicus) in the Canadian central arctic declined from an estimated 203,800 to 16,400 breeding females from 1986 to 2009, with the most rapid decline from 2006 to 2009. A key research and management question was whether the decline was mainly due to decreases in productivity alone or also due to reduced adult female survival. Investigating causes of the decline was hampered by a lack of direct estimates of caribou demographic parameters. We developed a demographic model that could be objectively fitted to field data to explore the mechanisms for the Bathurst decline, with a focus on the recent accelerated decline from 2006 to 2009. Our modeling indicated that the decline was driven by increasing negative trends in adult female and calf survival rates and possibly reduced fecundity The effect of a constant hunter harvest on the declining herd was one potential cause for the recent accelerated decline in adult survival. The demographic model detected negative trends in adult female survival that were not detected using standalone analyses of collar-based survival data. The model allowed rigorous interpretation of trends in productivity by controlling for the simultaneous influence of trends in adult, calf, and yearling survival and adult fecundity on field-based calf-cow ratios. Stochastic simulations suggested that large increases in adult survival and productivity would be needed for the herd to recover. Our methods enable objective modeling of caribou demography that can assist in caribou management based upon all sources of available data. © 2011 The Wildlife Society. Source

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