Modelling Population Dynamics Using Closed-Population Abundance Estimates

2014 ◽  
pp. 123-145
Author(s):  
K. B. Newman ◽  
S. T. Buckland ◽  
B. J. T. Morgan ◽  
R. King ◽  
D. L. Borchers ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Population Abundance ◽  
Closed Population ◽  
Abundance Estimates

Annual flooding, survival and recruitment in a rodent population from the Niger River plain in Mali

2008 ◽  
Vol 24 (4) ◽  
pp. 375-386 ◽  
Author(s):  
Laurent Crespin ◽  
Yves Papillon ◽  
Doukary Abdoulaye ◽  
Laurent Granjon ◽  
Bruno Sicard
Keyword(s):  
Population Dynamics ◽  
Water Level ◽  
Pest Species ◽  
Population Abundance ◽  
Mark Recapture ◽  
Closed Population ◽  
Survival Probabilities ◽  
Local Survival ◽  
Niger River ◽  
A Site

AbstractMultimammate rats of the genus Mastomys are among the most widespread pest species in Africa. Previous studies of Mastomys population dynamics have generally reported variation in abundance but few have investigated the demographic parameters underlying this variation, and in particular recruitment. Capture-mark-recapture data were collected for Mastomys erythroleucus several times a year from 2000 to 2004 at a site annually flooded by the Niger River in Mali. Closed-population models were used to estimate population abundance. Both seniority (a parameter inversely linked to recruitment) and survival probabilities were estimated by capture-mark-recapture models. The impacts of water level, population abundance and cumulative rainfall were assessed for each demographic parameter. Survival probabilities (local survival) were negatively correlated with water level, suggesting that rodents emigrated out of the study zone during flooding. As for seniority probabilities, 86% of temporal variation was explained by a model with season, abundance, water level and the interaction between abundance and water level. This suggests that density-dependence in recruitment was mediated by intraspecific competition for food or refuge from floodwaters, or by predation. The flood of the Niger River greatly impacts Mastomys erythroleucus population dynamics, affecting both survival and seniority probabilities.

Food supplementation and abundance estimation in the white-footed mouse

2006 ◽  
Vol 84 (8) ◽  
pp. 1210-1215 ◽  
Author(s):  
Pei-Jen L. Shaner
Keyword(s):  
Population Dynamics ◽  
Food Availability ◽  
Robust Design ◽  
Meta Analysis ◽  
Design Model ◽  
Food Supplementation ◽  
Abundance Estimates ◽  
Abundance Indices ◽  
Consumer Population ◽  
White Footed Mouse

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.

A multifrequency method to classify and evaluate fisheries acoustics data

2006 ◽  
Vol 63 (10) ◽  
pp. 2225-2235 ◽  
Author(s):  
J Michael Jech ◽  
William L Michaels
Keyword(s):  
Clupea Harengus ◽  
Biological Information ◽  
Classification Algorithms ◽  
Atlantic Herring ◽  
Population Abundance ◽  
Acoustic Data ◽  
Video Images ◽  
Abundance Estimates ◽  
Fisheries Acoustics ◽  
Acoustic Surveys

Acoustic surveys have been conducted on Georges Bank from 1998 to present to estimate Atlantic herring (Clupea harengus) population abundance. Acoustic data were collected with a 12 or 18, 38, and 120 kHz Simrad EK500 scientific echo sounder. A pelagic trawl and underwater video images were used to collect biological information and to verify the species composition of acoustic backscatter. A multifrequency classification method was developed to improve the efficiency and accuracy of classifying species from acoustic echograms. In this method, a volume backscatter (Sv) threshold was applied equivalently to all echograms, and then a composite echogram was created based on which frequencies had Sv greater than or less than the Sv threshold. The results of this method were compared with the standard method of visually scrutinizing regions, and metrics were developed to evaluate the accuracy of classification algorithms relative to current methods, as well as to assess the effects of classification methods on population abundance estimates. In general, this method matched visually scrutinized Atlantic herring regions, but with consistent biases in classifying 38 kHz backscatter. The metrics highlighted spatial and temporal changes in the acoustic landscape, which may be indicative of intra- and inter-annual biological changes.

scholarly journals A Simplified Population-Level Landscape Model Identifying Ecological Risk Drivers of Pesticide Applications, Part One: Case Study for Large Herbivorous Mammals

2021 ◽  
Vol 18 (15) ◽  
pp. 7720
Author(s):  
David Tarazona ◽  
Guillermo Tarazona ◽  
Jose V. Tarazona
Keyword(s):  
Population Dynamics ◽  
Pesticide Exposure ◽  
Population Level ◽  
Guidance Document ◽  
Population Abundance ◽  
Landscape Model ◽  
Ecological Data ◽  
Conceptual Approach ◽  
Terrestrial Vertebrates ◽  
The Impact

Environmental risk assessment is a key process for the authorization of pesticides, and is subjected to continuous challenges and updates. Current approaches are based on standard scenarios and independent substance-crop assessments. This arrangement does not address the complexity of agricultural ecosystems with mammals feeding on different crops. This work presents a simplified model for regulatory use addressing landscape variability, co-exposure to several pesticides, and predicting the effect on population abundance. The focus is on terrestrial vertebrates and the aim is the identification of the key risk drivers impacting on mid-term population dynamics. The model is parameterized for EU assessments according to the European Food Safety Authority (EFSA) Guidance Document, but can be adapted to other regulatory schemes. The conceptual approach includes two modules: (a) the species population dynamics, and (b) the population impact of pesticide exposure. Population dynamics is modelled through daily survival and seasonal reproductions rates; which are modified in case of pesticide exposure. All variables, parameters, and functions can be modified. The model has been calibrated with ecological data for wild rabbits and brown hares and tested for two herbicides, glyphosate and bromoxynil, using validated toxicity data extracted from EFSA assessments. Results demonstrate that the information available for a regulatory assessment, according to current EU information requirements, is sufficient for predicting the impact and possible consequences at population dynamic levels. The model confirms that agroecological parameters play a key role when assessing the effect of pesticide exposure on population abundance. The integration of laboratory toxicity studies with this simplified landscape model allows for the identification of conditions leading to population vulnerability or resilience. An Annex includes a detailed assessment of the model characteristics according to the EFSA scheme on Good Modelling Practice.

scholarly journals Abundance of East coast Australian humpback whales (Megaptera novaeangliae) in 2005 estimated using multi-point sampling and capture-recapture analysis

2020 ◽  
pp. 253-259
Author(s):  
David A. Paton ◽  
Lyndon Brooks ◽  
Daniel Burns ◽  
Trish Franklin ◽  
Wally Franklin ◽  
...  
Keyword(s):  
East Coast ◽  
Megaptera Novaeangliae ◽  
Humpback Whales ◽  
Migration Route ◽  
Closed Population ◽  
Breeding Stock ◽  
Abundance Estimate ◽  
Abundance Estimates ◽  
Capture Recapture ◽  
Near Extinction

The humpback whales (Megaptera novaeangliae) that migrate along the east coast of Australia were hunted to near extinction during the lastcentury. This remnant population is part of Breeding Stock E. Previous abundance estimates for the east Australian portion of Breeding Stock Ehave been based mainly on land-based counts. Here we present a capture-recapture abundance estimate for this population using photo-identificationdata. These data were collected at three locations on the migration route (Byron Bay – northern migration, Hervey Bay and Ballina – southernmigration) in order to estimate the population of humpback whales that migrated along the east coast of Australia in 2005. The capture-recapturedata were analysed using a variety of closed population models with a model-averaged estimate of 7,041 (95% CI 4,075–10,008) whales.

Incorporating Uncertainty into Fishery Models

2002 ◽  
Keyword(s):  
Population Dynamics ◽  
Parameter Uncertainty ◽  
Model Uncertainty ◽  
Oncorhynchus Tshawytscha ◽  
Population Abundance ◽  
Management Options ◽  
Population Survival ◽  
Model Parameter Uncertainty ◽  
Recruitment Model ◽  
The Bayesian Approach

<em>Abstract.—</em>Spring and summer chinook salmon <em>Oncorhynchus tshawytscha </em>populations of the Snake River basin provide the setting for an application of Bayesian analysis to derive risks of population survival and recovery for these endangered populations. The Bayesian approach is appealing because it provides a theoretical framework within which uncertainty about population dynamics is directly translated into measures of probability of achieving various population abundance targets, given certain types of actions in the future. Uncertainty about parameters governing the population dynamics is based on an application of the Bayes Theorem to the likelihood of observations about past recruitment, as viewed in the context of a generalized Ricker spawner and recruitment model. Uncertainty about future dynamics is based on simulations of population abundance over the next 100 years, and they contain both model parameter uncertainty and annual stochastic elements affecting survival. Results show substantial reductions in mortality rate (on the order of 0.5–0.7 per year, as compared with rates in recent years) are required in order for the populations to meet recovery and survival standards set for the next 48– 100 years. The level of mortality reduction needed to achieve these standards can assist in guiding potential hydropower system management options.

scholarly journals Estimating Detection Probabilities From Multiple-Observer Point Counts

The Auk ◽  
2006 ◽  
Vol 123 (4) ◽  
pp. 1172-1182 ◽  
Author(s):  
Mathew W. Alldredge ◽  
Kenneth H. Pollock ◽  
Theodore R. Simons
Keyword(s):  
Individual Differences ◽  
Large Scale ◽  
Detection Distance ◽  
Independent Observer ◽  
Closed Population ◽  
Point Count ◽  
Point Counts ◽  
Individual Bird ◽  
Abundance Estimates ◽  
Detection Probabilities

Abstract Point counts are commonly used to obtain indices of bird population abundance. We present an independent-observer point-count method, a generalization of the dependent-observer approach, based on closed-population capture- recapture methods. The approach can incorporate individual covariates, such as detection distance, to account for individual differences in detection probabilities associated with measurable sources of variation. We demonstrate a negative bias in two-observer estimates by comparing abundance estimates from two- and four- observer point counts. Models incorporating data from four independent observers were capable of accounting for this bias. Modeling individual bird differences in detection probabilities produced abundance estimates 15–21% higher than models that did not account for individual differences, in four out of five data sets analyzed. Although independent-observer methods are expensive and impractical for large- scale applications, we believe they can provide important insights into the sources and degree of perception bias (i.e., probability of detecting an individual, given that it is available for detection) in avian point-count estimates. Therefore, they may be useful in a two-stage sampling framework to calibrate larger surveys based on single-observer estimates. Estimación de Probabilidades de Detección a Partir de Conteos en Puntos Hechos por Varios Observadores

scholarly journals Estimating population abundance with a mixture of physical capture and PIT tag antenna detection data

2020 ◽  
Vol 77 (7) ◽  
pp. 1163-1171
Author(s):  
Mary M. Conner ◽  
Phaedra E. Budy ◽  
Richard A. Wilkison ◽  
Michael Mills ◽  
David Speas ◽  
...  
Keyword(s):  
Coefficient Of Variation ◽  
Population Abundance ◽  
Dramatic Reduction ◽  
Pit Tag ◽  
Abundance Estimates ◽  
Detection Probabilities ◽  
Significant Change ◽  
The Difference

The inclusion of passive interrogation antenna (PIA) detection data has promise to increase precision of population abundance estimates ([Formula: see text]). However, encounter probabilities are often higher for PIAs than for physical capture. If the difference is not accounted for, [Formula: see text] may be biased. Using simulations, we estimated the magnitude of bias resulting from mixed capture and detection probabilities and evaluated potential solutions for removing the bias for closed capture models. Mixing physical capture and PIA detections (pdet) resulted in negative biases in [Formula: see text]. However, using an individual covariate to model differences removed bias and improved precision. From a case study of fish making spawning migrations across a stream-wide PIA (pdet ≤ 0.9), the coefficient of variation (CV) of [Formula: see text] declined 39%–82% when PIA data were included, and there was a dramatic reduction in time to detect a significant change in [Formula: see text]. For a second case study, with modest pdet (≤0.2) using smaller PIAs, CV ([Formula: see text]) declined 4%–18%. Our method is applicable for estimating abundance for any situation where data are collected with methods having different capture–detection probabilities.

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