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Metapopulation Models (metapopulation + models)

Distribution by Scientific Domains

Life Sciences	87%

Selected Abstracts

Metapopulation ecology in the sea: from Levins' model to marine ecology and fisheries science

FISH AND FISHERIES, Issue 2 2004
Jacob P Kritzer
Abstract Marine and fisheries scientists are increasingly using metapopulation concepts to better understand and model their focal systems. Consequently, they are considering what defines a metapopulation. One perspective on this question emphasizes the importance of extinction probability in local populations. This view probably stems from the focus on extinction in Levins' original metapopulation model, but places unnecessary emphasis on extinction,recolonization dynamics. Metapopulation models with more complex structure than Levins' patch-occupancy model and its variants allow a broader range of population phenomena to be examined, such as changes in population size, age structure and genetic structure. Analyses along these lines are critical in fisheries science, where presence,absence resolution is far too coarse to understand stock dynamics in a meaningful way. These more detailed investigations can, but need not, aim to assess extinction risk or deal with extinction-prone local populations. Therefore, we emphasize the coupling of spatial scales as the defining feature of metapopulations. It is the degree of demographic connectivity that characterizes metapopulations, with the dynamics of local populations strongly dependent upon local demographic processes, but also influenced by a nontrivial element of external replenishment. Therefore, estimating rates of interpopulation exchange must be a research priority. We contrast metapopulations with other spatially structured populations that differ in the degree of local closure of their component populations. We conclude with consideration of the implications of metapopulation structure for spatially explicit management, particularly the design of marine protected area networks. [source]

The equilibrium assumption in estimating the parameters of metapopulation models

JOURNAL OF ANIMAL ECOLOGY, Issue 1 2000
Atte Moilanen
1.,The construction of a predictive metapopulation model includes three steps: the choice of factors affecting metapopulation dynamics, the choice of model structure, and finally parameter estimation and model testing. 2.,Unless the assumption is made that the metapopulation is at stochastic quasi-equilibrium and unless the method of parameter estimation of model parameters uses that assumption, estimates from a limited amount of data will usually predict a trend in metapopulation size. 3.,This implicit estimation of a trend occurs because extinction-colonization stochasticity, possibly amplified by regional stochasticity, leads to unequal numbers of observed extinction and colonization events during a short study period. 4.,Metapopulation models, such as those based on the logistic regression model, that rely on observed population turnover events in parameter estimation are sensitive to the implicit estimation of a trend. 5.,A new parameter estimation method, based on Monte Carlo inference for statistically implicit models, allows an explicit decision about whether metapopulation quasi-stability is assumed or not. 6.,Our confidence in metapopulation model parameter estimates that have been produced from only a few years of data is decreased by the need to know before parameter estimation whether the metapopulation is in quasi-stable state or not. 7.,The choice of whether metapopulation stability is assumed or not in parameter estimation should be done consciously. Typical data sets cover only a few years and rarely allow a statistical test of a possible trend. While making the decision about stability one should consider any information about the landscape history and species and metapopulation characteristics. [source]

Linking movement behaviour, dispersal and population processes: is individual variation a key?

JOURNAL OF ANIMAL ECOLOGY, Issue 5 2009
Colin Hawkes
Summary 1Movement behaviour has become increasingly important in dispersal ecology and dispersal is central to the development of spatially explicit population ecology. The ways in which the elements have been brought together are reviewed with particular emphasis on dispersal distance distributions and the value of mechanistic models. 2There is a continuous range of movement behaviours and in some species, dispersal is a clearly delineated event but not in others. The biological complexities restrict conclusions to high-level generalizations but there may be principles that are common to dispersal and other movements. 3Random walk and diffusion models when appropriately elaborated can provide an understanding of dispersal distance relationships on spatial and temporal scales relevant to dispersal. Leptokurtosis in the relationships may be the result of a combination of factors including population heterogeneity, correlation, landscape features, time integration and density dependence. The inclusion in diffusion models of individual variation appears to be a useful elaboration. The limitations of the negative exponential and other phenomenological models are discussed. 4The dynamics of metapopulation models are sensitive to what appears to be small differences in the assumptions about dispersal. In order to represent dispersal realistically in population models, it is suggested that phenomenological models should be replaced by those based on movement behaviour incorporating individual variation. 5The conclusions are presented as a set of candidate principles for evaluation. The main features of the principles are that uncorrelated or correlated random walk, not linear movement, is expected where the directions of habitat patches are unpredictable and more complex behaviour when organisms have the ability to orientate or navigate. Individuals within populations vary in their movement behaviour and dispersal; part of this variation is a product of random elements in movement behaviour and some of it is heritable. Local and metapopulation dynamics are influenced by population heterogeneity in dispersal characteristics and heritable changes in dispersal propensity occur on time-scales short enough to impact population dynamics. [source]

Incorporating movement into models of grey seal population dynamics

JOURNAL OF ANIMAL ECOLOGY, Issue 3 2006
PHILIP J. HARRISON
Summary 1One of the most difficult problems in developing spatially explicit models of population dynamics is the validation and parameterization of the movement process. We show how movement models derived from capture,recapture analysis can be improved by incorporating them into a spatially explicit metapopulation model that is fitted to a time series of abundance data. 2We applied multisite capture,recapture analysis techniques to photo-identification data collected from female grey seals at the four main breeding colonies in the North Sea between 1999 and 2001. The best-fitting movement models were then incorporated into state-space metapopulation models that explicitly accounted for demographic and observational stochasticity. 3These metapopulation models were fitted to a 20-year time series of pup production data for each colony using a Bayesian approach. The best-fitting model, based on the Akaike Information Criterion (AIC), had only a single movement parameter, whose confidence interval was 82% less than that obtained from the capture,recapture study, but there was some support for a model that included an effect of distance between colonies. 4The state-space modelling provided improved estimates of other demographic parameters. 5The incorporation of movement, and the way in which it was modelled, affected both local and regional dynamics. These differences were most evident as colonies approached their carrying capacities, suggesting that our ability to discriminate between models should improve as the length of the grey seal time series increases. [source]

The equilibrium assumption in estimating the parameters of metapopulation models

Importance of Hydrologic and Landscape Heterogeneity for Restoring Bank Swallow (Riparia riparia) Colonies along the Sacramento River, California

RESTORATION ECOLOGY, Issue 2 2005
Kerry C. Moffatt
Abstract Human activities have degraded riparian systems in numerous ways, including homogenization of the floodplain landscape and minimization of extreme flows. We analyzed the effects of changes in these and other factors for extinction,colonization dynamics of a threatened Bank Swallow population along the upper Sacramento River, California, U.S.A. We monitored Bank Swallow distributions along a 160-km stretch of the river from 1986,1992 and 1996,2003 and tested whether site extinctions and colonizations corresponded with changes in maximum river discharge, surrounding land cover, estimated colony size, temperature, and precipitation. Colonization probabilities increased with maximum discharge. Extinction probabilities decreased with proximity to the nearest grassland, decreased with colony size, and increased with maximum discharge. To explore the implications for restoration, we incorporated the statistically estimated effects of distance to grassland and maximum discharge into simple metapopulation models. Under current conditions, the Bank Swallow metapopulation appears to be in continued decline, although stable or increasing numbers cannot be ruled out with the existing data. Maximum likelihood parameters from these regression models suggest that the Sacramento River metapopulation could be restored to 45 colonies through moderate amounts of grassland restoration, large increases in discharge, or direct restoration of nesting habitat by removing approximately 10% of existing bank protection (riprap) from suitable areas. Our results highlight the importance of grassland restoration, mixed benefits of restoring high spring discharge, and the importance of within-colony dynamics as areas for future research. [source]

Cryptic local populations in a temperate rainforest bat Chalinolobus tuberculatus in New Zealand

ANIMAL CONSERVATION, Issue 4 2000
Colin F. J. O'Donnell
Population structure of the threatened long-tailed bat (Chalinolobus tuberculatus) was studied over five summers between 1993 and 1998, in temperate Nothofagus rainforest in Fiordland, New Zealand. Composition of 95 communal groups was sampled and spatial distribution of individually marked bats investigated. Individual C. tuberculatus moved to new roost sites virtually every day. Long term non-random associations among individuals were found by a cluster analysis that revealed three distinct social groups. Groups contained on average 72.0 (± 26.0) (mean ± SD), 99.3 (± 19.0) and 131.7 (± 16.5) marked individuals/year. Collective foraging ranges of the three groups overlapped but roosting occurred in three geographically distinct adjacent areas. Only 1.6% of individuals switched between groups. Non-reproductive females and males switched between groups more often than reproductive females but individuals switched only once or twice during the study and then just for one night. Juveniles of both sexes were associated with their natal group as 1 year-olds and then later when breeding. Social groups were cryptic because foraging ranges of groups overlapped, bats belonging to each group spread over many roosts each day, and these roost sites changed from day to day. Bats moved infrequently between groups, potentially linking the local population assemblages. Future research should explore whether the population is structured in demes. Population structure did not conform to traditional metapopulation models because groups occurred in homogeneous habitat extending over a large geographical area. Conserving bat populations should entail preserving a representative number of subgroups but development of models for predicting minimum number of effective local populations is still required. [source]

Occupancy frequency distributions: patterns, artefacts and mechanisms

BIOLOGICAL REVIEWS, Issue 3 2002
MELODIE A. McGEOCH
ABSTRACT Numerous hypotheses have been proposed to explain the shape of occupancy frequency distributions (distributions of the numbers of species occupying different numbers of areas). Artefactual effects include sampling characteristics, whereas biological mechanisms include organismal, niche-based and metapopulation models. To date, there has been little testing of these models. In addition, although empirically derived occupancy distributions encompass an array of taxa and spatial scales, comparisons between them are often not possible because of differences in sampling protocol and method of construction. In this paper, the effects of sampling protocol (grain, sample number, extent, sampling coverage and intensity) on the shape of occupancy distributions are examined, and approaches for minimising artefactual effects recommended. Evidence for proposed biological determinants of the shape of occupancy distributions is then examined. Good support exists for some mechanisms (habitat and environmental heterogeneity), little for others (dispersal ability), while some hypotheses remain untested (landscape productivity, position in geographic range, range size frequency distributions), or are unlikely to be useful explanations for the shape of occupancy distributions (species specificity and adaptation to habitat, extinction,colonization dynamics). The presence of a core (class containing species with the highest occupancy) mode in occupancy distributions is most likely to be associated with larger sample units, and small homogenous sampling areas positioned well within and towards the range centers of a sufficient proportion of the species in the assemblage. Satellite (class with species with the lowest occupancy) modes are associated with sampling large, heterogeneous areas that incorporate a large proportion of the assemblage range. However, satellite modes commonly also occur in the presence of a core mode, and rare species effects are likely to contribute to the presence of a satellite mode at most sampling scales. In most proposed hypotheses, spatial scale is an important determinant of the shape of the observed occupancy distribution. Because the attributes of the mechanisms associated with these hypotheses change with spatial scale, their predictions for the shape of occupancy distributions also change. To understand occupancy distributions and the mechanisms underlying them, a synthesis of pattern documentation and model testing across scales is thus needed. The development of null models, comparisons of occupancy distributions across spatial scales and taxa, documentation of the movement of individual species between occupancy classes with changes in spatial scale, as well as further testing of biological mechanisms are all necessary for an improved understanding of the distribution of species and assemblages within their geographic ranges. [source]