scholarly journals On the Estimation of Dispersal and Movement of Birds

The Condor ◽  
2004 ◽  
Vol 106 (4) ◽  
pp. 720-731 ◽  
Author(s):  
William L. Kendall ◽  
James D. Nichols

Abstract The estimation of dispersal and movement is important to evolutionary and population ecologists, as well as to wildlife managers. We review statistical methodology available to estimate movement probabilities. We begin with cases where individual birds can be marked and their movements estimated with the use of multisite capture-recapture methods. Movements can be monitored either directly, using telemetry, or by accounting for detection probability when conventional marks are used. When one or more sites are unobservable, telemetry, band recoveries, incidental observations, a closed- or open-population robust design, or partial determinism in movements can be used to estimate movement. When individuals cannot be marked, presence-absence data can be used to model changes in occupancy over time, providing indirect inferences about movement. Where abundance estimates over time are available for multiple sites, potential coupling of their dynamics can be investigated using linear cross-correlation or nonlinear dynamic tools. Sobre la Estimación de la Dispersión y el Movimiento de las Aves Resumen. La estimación de la dispersión y el movimiento es importante para los ecó logos evolutivos y de poblaciones, así como también para los encargados del manejo de vida silvestre. Revisamos la metodología estadística disponible para estimar probabilidades de movimiento. Empezamos con casos donde aves individuales pueden ser marcadas y sus movimientos estimados con el uso de métodos de captura-repactura para múltiples sitios. Los movimientos pueden ser monitoreados ya sea directamente, usando telemetría o teniendo en cuenta las probabilidades de detección cuando se usan marcas convencionales. Cuando uno o más sitios no pueden ser observados, se puede estimar el movimiento usando telemetría, recuperación de anillos, observaciones circunstanciales, un diseño poblacional robusto cerrado o abierto, o determinismo parcial de los movimientos. Cuando los individuos no pueden ser marcados, se pueden usar datos de presencia-ausencia para modelar los cambios en el tiempo de la ocupación, brindando inferencias indirectas sobre los movimientos. Cuando las estimaciones de abundancia a lo largo del tiempo están disponibles para varios sitios, se puede investigar la interrelación potencial de sus dinámicas usando correlaciones cruzadas lineales o herramientas para dinámica no lineal.

2020 ◽  
Author(s):  
Ehsan M. Moqanaki ◽  
Cyril Milleret ◽  
Mahdieh Tourani ◽  
Pierre Dupont ◽  
Richard Bischof

AbstractContextSpatial capture-recapture (SCR) models are increasingly popular for analyzing wildlife monitoring data. SCR can account for spatial heterogeneity in detection that arises from individual space use (detection kernel), variation in the sampling process, and the distribution of individuals (density). However, unexplained and unmodeled spatial heterogeneity in detectability may remain due to cryptic factors, intrinsic and extrinsic to the study system.ObjectivesWe identify how the magnitude and configuration of unmodeled, spatially variable detection probability influence SCR parameter estimates.MethodsWe simulated realistic SCR data with spatially variable and autocorrelated detection probability. We then fitted a single-session SCR model ignoring this variation to the simulated data and assessed the impact of model misspecification on inferences.ResultsHighly autocorrelated spatial heterogeneity in detection probability (Moran’s I = 0.85 - 0.96), modulated by the magnitude of that variation, can lead to pronounced negative bias (up to 75%), reduction in precision (249%), and decreasing coverage probability of the 95% credible intervals associated with abundance estimates to 0. Conversely, at low levels of spatial autocorrelation (median Moran’s I = 0), even severe unmodeled heterogeneity in detection probability did not lead to pronounced bias and only caused slight reductions in precision and coverage of abundance estimates.ConclusionsUnknown and unmodeled variation in detection probability is liable to be the norm, rather than the exception, in SCR studies. We encourage practitioners to consider the impact that spatial autocorrelation in detectability has on their inferences and urge the development of SCR methods that can take structured unknown or partially unknown spatial variability in detection probability into account.


2021 ◽  
Author(s):  
Ehsan M. Moqanaki ◽  
Cyril Milleret ◽  
Mahdieh Tourani ◽  
Pierre Dupont ◽  
Richard Bischof

Abstract Context Spatial capture-recapture (SCR) models are increasingly popular for analyzing wildlife monitoring data. SCR can account for spatial heterogeneity in detection that arises from individual space use (detection kernel), variation in the sampling process, and the distribution of individuals (density). However, unexplained and unmodeled spatial heterogeneity in detectability may remain due to cryptic factors, both intrinsic and extrinsic to the study system. This is the case, for example, when covariates coding for variable effort and detection probability in general are incomplete or entirely lacking. Objectives We identify how the magnitude and configuration of unmodeled, spatially variable detection probability influence SCR parameter estimates. Methods We simulated SCR data with spatially variable and autocorrelated detection probability. We then fitted an SCR model ignoring this variation to the simulated data and assessed the impact of model misspecification on inferences. Results Highly-autocorrelated spatial heterogeneity in detection probability (Moran’s I = 0.85–0.96), modulated by the magnitude of the unmodeled heterogeneity, can lead to pronounced negative bias (up to 65%, or about 44-fold decrease compared to the reference scenario), reduction in precision (249% or 2.5-fold) and coverage probability of the 95% credible intervals associated with abundance estimates to 0. Conversely, at low levels of spatial autocorrelation (median Moran’s I = 0), even severe unmodeled heterogeneity in detection probability did not lead to pronounced bias and only caused slight reductions in precision and coverage of abundance estimates. Conclusions Unknown and unmodeled variation in detection probability is liable to be the norm, rather than the exception, in SCR studies. We encourage practitioners to consider the impact that spatial autocorrelation in detectability has on their inferences and urge the development of SCR methods that can take structured, unknown or partially unknown spatial variability in detection probability into account.


2006 ◽  
Vol 84 (8) ◽  
pp. 1210-1215 ◽  
Author(s):  
Pei-Jen L. Shaner

Food availability often drives consumer population dynamics. However, food availability may also influence capture probability, which if not accounted for may create bias in estimating consumer abundance and confound the effects of food availability on consumer population dynamics. This study compared two commonly used abundance indices (minimum number alive (MNA) and number of animals captured per night per grid) with an abundance estimator based on robust design model as applied to the white-footed mouse ( Peromyscus leucopus (Rafinesque, 1818)) in food supplementation experiments. MNA consistently generated abundance estimates similar to the robust design model, regardless of food supplementation. The number of animals captured per night per grid, however, consistently generated lower abundance estimates compared with MNA and the robust design model. Nevertheless, the correlations between abundance estimates from MNA, number of animals captured, and robust design model were not influenced by food supplementation. This study demonstrated that food supplementation is not likely to create bias among these different measures of abundance. Therefore, there is a great potential for conducting meta-analysis of food supplementation effect on consumer population dynamics (particularly in small mammals) across studies using different abundance indices and estimators.


2020 ◽  
Vol 94 ◽  
Author(s):  
A.L. May-Tec ◽  
N.A. Herrera-Castillo ◽  
V.M. Vidal-Martínez ◽  
M.L. Aguirre-Macedo

Abstract We present a time series of 13 years (2003–2016) of continuous monthly data on the prevalence and mean abundance of the trematode Oligogonotylus mayae for all the hosts involved in its life cycle. We aimed to determine whether annual (or longer than annual) environmental fluctuations affect these infection parameters of O. mayae in its intermediate snail host Pyrgophorus coronatus, and its second and definitive fish host Mayaheros urophthalmus from the Celestun tropical coastal lagoon, Yucatan, Mexico. Fourier time series analysis was used to identify infection peaks over time, and cross-correlation among environmental forcings and infection parameters. Our results suggest that the transmission of O. mayae in all its hosts was influenced by the annual patterns of temperature, salinity and rainfall. However, there was a biannual accumulation of metacercarial stages of O. mayae in M. urophthalmus, apparently associated with the temporal range of the El Niño-Southern Oscillation (five years) and the recovery of the trematode population after a devasting hurricane. Taking O. mayae as an example of what could be happening to other trematodes, it is becoming clear that environmental forcings acting at long-term temporal scales affect the population dynamics of these parasites.


2018 ◽  
Vol 75 (9) ◽  
pp. 1357-1368 ◽  
Author(s):  
Christopher L. Cahill ◽  
Stephanie Mogensen ◽  
Kyle L. Wilson ◽  
Ariane Cantin ◽  
R. Nilo Sinnatamby ◽  
...  

Catch-and-release regulations designed to protect fisheries may fail to halt population declines, particularly in situations where fishing effort is high and when multiple stressors threaten a population. We demonstrate this claim using Alberta’s Bow River, which supports a high-effort rainbow trout (Oncorhynchus mykiss) fishery where anglers voluntarily release >99% of their catch. We examined the population trend of adult trout, which were tagged and recaptured using electrofishing surveys conducted intermittently during 2003–2013. We constructed Bayesian multisession capture–recapture models in Stan to obtain abundance estimates for trout and regressed trend during two periods to account for variation in sampling locations. General patterns from all models indicated the population declined throughout the study. Potential stressors to this system that may have contributed to the decline include whirling disease (Myxobolus cerebralis), which was detected for the first time in 2016, notable floods, and release mortality. Because disease and floods are largely uncontrollable from a management perspective, we suggest that stringent tactics such as angler effort restrictions may be necessary to maintain similar fisheries.


Economies ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 133
Author(s):  
Derick Quintino ◽  
José Telo da Gama ◽  
Paulo Ferreira

Brazil is one of the world’s largest producers and exporters of cattle, chicken and swine. Therefore, co-movements of Brazilian meat prices are important for both domestic and foreign stakeholders. We propose to analyse the cross-correlation between meat prices in Brazil, namely, cattle, swine and chicken, including also in the analysis information from some commodities, namely maize, soya beans, oil, and the Brazilian exchange rate. Our sample covers the recent period which coincided with extensive macroeconomic and institutional changes in Brazil, from 2011 to 2020, and is divided in two periods: (i) presidential pre-impeachment (P1), occurring in August 2016, and; (ii) post-impeachment (P2). Our results indicate that in P1, only the prices of swine and chicken showed a positive and strong correlation over time, and that cattle showed some positive correlation with chicken only in the short run. In P2, there was also a positive and consistent correlation between swine and chicken, and only a positive association with swine and cattle in the long run. For more spaced time scales (days), the changes in the degree of correlation were significant only in the long run for swine and cattle.


Author(s):  
Peter A. Henderson

The main methods used to estimate population size using capture–recapture for both closed and open populations are described, including the Peterson–Lincoln estimator, the Schabel census, Bailey’s triple catch, the Jolly–Seber stochastic method, and Cormack’s log-linear method. The robust design approach is described. R code listings for commonly used packages are presented. The assumptions common to capture–recapture methods are reviewed, and tests for assumptions such as equal catchability described. The use of programs to select model assumptions are described. The main methods for marking different animal groups are described, together with the use of natural marks and parasites and DNA. Marking methods include paint marks, dyes, tagging, protein marking, DNA, natural marks, tattooing, and mutilation. Methods for handling and release are described.


Ecosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
Author(s):  
Christopher B. Satter ◽  
Ben C. Augustine ◽  
Bart J. Harmsen ◽  
Rebecca J. Foster ◽  
Marcella J. Kelly

Ecosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
Author(s):  
Cyril Milleret ◽  
Pierre Dupont ◽  
Joseph Chipperfield ◽  
Daniel Turek ◽  
Henrik Brøseth ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document