Scale-dependent portfolio effects explain growth inflation and volatility reduction in landscape demography (original) (raw)
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Methods in Ecology and Evolution, 2014
A key challenge for both ecological researchers and biodiversity managers is the measurement and prediction of species richness across spatial scales. Typically, biodiversity is assessed at fine scales (e.g. in quadrats or transects) for practical reasons, but often we are interested in coarser-scale (field, regional, global) diversity issues. Moreover, the pressures affecting biodiversity patterns are often scale specific, making multiscale assessment a crucial methodological priority. As species richness is not additive, it is difficult to translate from the scale of measurement to the scale(s) of interest. A number of methods have been proposed to tackle this problem, but most are too model specific or too rigid to allow general application. Here, we present a general framework (and a specific implementation of it) that allows such scale translations to be performed. 2. Building on the intrinsic relationships among patterns of species richness, abundance and spatial turnover, we introduce a framework that links and predicts the profile of the species-area relationship and the speciesabundance distributions across scales when a limited number of fine-scale scattered samples are available. Using the correlation in species' abundances between pairs of samples as a function of the distance between them, we are able to link the effects of aggregation, similarity decay, species richness and species abundances across scales. 3. Our approach allows one to draw inferences about biodiversity scaling under very general assumptions pertaining to the nature of interactions, the geographical distributions of individuals and ecological processes. 4. We demonstrate the accuracy of our predictions using data from two well-studied forest stands and also demonstrate the potential value of such methods by examining the effects of management on farmland insects across scales. The framework has important applications to biodiversity research and conservation practice.
Do bird spatial distribution patterns reflect population trends in changing landscapes
Landscape Ecology, 2009
Strong relations between population trends and spatial distribution have been suggested at the regional scale: declining species should have more fragmented distributions because decline causes range retractions towards optimal habitats, whereas increasing species should have more aggregated distributions, because colonization processes are constrained by distance. Most analyses of the effects of land use changes on animal populations are diachronic studies of population dynamics or synchronic studies of species habitat selection. Few studies take simultaneously into account temporal changes in habitat distribution and changes in species spatial distribution. We applied the above rationale to the landscape scale and analysed how population declines, increases or stability, as diagnosed in a long term study, correlate with population connectivity or fragmentation at that scale. We used data on changes in faunal distribution and information on temporal changes in the vegetation in a Mediterranean area that had been subjected to land abandonment. We found that species declining at the landscape scale had retracting fragmented distributions and that expanding species had expanding continuous distributions. However, for the latter, we suggest that the factors involved are related to landscape structure and not to dispersal mediated meta-population processes, which are of little relevance at this local scale. We also show that even species that are numerically stable can show fragmentation of their distribution and major spatial distribution shifts in response to land use changes, especially in species that have low occurrence levels or that are associated with transitory habitats such as heterogeneous shrublands (e.g. Sylvia melanocephala). Studying the spatial structure of species distribution patterns at the landscape scale may provide information about population declines and increases both at the regional and the landscape scale and can improve our understanding of short-term risks of local extinction.
Modeling animal population dynamics in changing landscapes
Ibis, 1994
Models of Mobile Animal Populations (MAP models) simulate long-term land use changes, population trends and patterns of biological diversity on landscapes of 103-105 ha. MAP models can incorporate information about past land-use patterns and management practices and can project future patterns based on management plans. We illustrate this approach with an example of how implementation of a U S . Forest Service management plan at the Savannah River Site in South Carolina, U.S.A., might influence population trends of Bachman's Sparrow Airnophila aestivulis, a relatively rare and declining species in southeastern pine forests. In this case, a management plan, largely designed to improve conditions for an endangered species, Red-cockaded Woodpecker Picoides borealis, may have a negative impact, at least in the short term, on another species of management concern, Bachman's Sparrow.
The effects of landscape modifications on the long-term persistence of animal populations.
2010
Background: The effects of landscape modifications on the long-term persistence of wild animal populations is of crucial importance to wildlife managers and conservation biologists, but obtaining experimental evidence using real landscapes is usually impossible. To circumvent this problem we used individual-based models (IBMs) of interacting animals in experimental modifications of a real Danish landscape. The models incorporate as much as possible of the behaviour and ecology of four species with contrasting life-history characteristics: skylark (Alauda arvensis), vole (Microtus agrestis), a ground beetle (Bembidion lampros) and a linyphiid spider (Erigone atra). This allows us to quantify the population implications of experimental modifications of landscape configuration and composition.
Population Dynamics in Complex Landscapes: A Case Study
Ecological Applications, 1992
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Populations as Fluid on a Landscape Under Global Environmental Change
Frontiers in Ecology and Evolution, 2019
Long-term climate change has been an ever-present feature of the Earth, but in ecology, it has, until recently, been largely ignored outside of paleoecological and dendroecological studies. It is now difficult to ignore due to strong anthropogenic drivers of change. However, standard ecological models and theory have always assumed no long-term trends in the environment, limiting the ability to conceptualize a natural world inescapably influenced by long-term change. Recent theory of asymptotic environmentally determined trajectories (aedts) provides a way forward, but has not previously considered the critical interactions between space and time that are of much importance in understanding ecosystem responses to climate change. Here, this theory is extended to spatial models including long-term environmental change, and is illustrated with simple model examples. Regarding a population as fluid on a landscape allows consideration of how the environment that the population actually experiences changes with time. Here, it is shown that although the environment at any one locality may show strong temporal trends, the environment experienced by a population as it moves around a landscape need not have any strong trends. However, the experienced environment will generally differ by being less favorable on average than without long-term global change. These results suggest theoretical and empirical research programs on the characteristics of landscapes, dispersal, and temporal change affecting the properties of experienced environments. They imply moving away from local population and community thinking to conceptualization and study of populations and communities on multiple spatial and temporal scales. Many standard ecological methods and concepts may still apply to populations tracked as they move on a landscape, while at the same time, understanding is enriched by accounting for how dispersal processes and landscape complexity, interacting with temporal change, affect those moving populations.
Heterogeneous landscapes promote population stability
Ecology Letters, 2010
Ecology Letters (2010) 13: 473–484Ecology Letters (2010) 13: 473–484AbstractHabitat heterogeneity is often suggested as being important for the stability of populations, and promoted as a means to aid the conservation of species, but the evidence for such an assumption is poor. Here we show that heterogeneous landscapes that contain a variety of suitable habitat types are associated with more stable population dynamics for 35 British butterfly species from 166 sites. In addition, topographic heterogeneity may also promote stability. Our results were robust to different measures of population variability, differences in mean abundance among sites, and to the spatial scale (radius 1–5 km around the centres of sites) at which landscapes were analysed. Responses to landscape heterogeneity differed among species; for more mobile ‘wider-countryside’ species, habitat heterogeneity at larger landscape scales had the strongest effect on population dynamics. We suggest that heterogeneous landscapes offer a greater range of resources and microclimates, which can buffer populations against climatic variation and generate more stable population dynamics.Habitat heterogeneity is often suggested as being important for the stability of populations, and promoted as a means to aid the conservation of species, but the evidence for such an assumption is poor. Here we show that heterogeneous landscapes that contain a variety of suitable habitat types are associated with more stable population dynamics for 35 British butterfly species from 166 sites. In addition, topographic heterogeneity may also promote stability. Our results were robust to different measures of population variability, differences in mean abundance among sites, and to the spatial scale (radius 1–5 km around the centres of sites) at which landscapes were analysed. Responses to landscape heterogeneity differed among species; for more mobile ‘wider-countryside’ species, habitat heterogeneity at larger landscape scales had the strongest effect on population dynamics. We suggest that heterogeneous landscapes offer a greater range of resources and microclimates, which can buffer populations against climatic variation and generate more stable population dynamics.
Quantifying species’ geographic range changes: conceptual and statistical issues
Ecosphere, 2020
Geographic range is an important metric used to evaluate species' environmental relationships. Additionally, a very small or rapidly shrinking range may indicate elevated extinction risk. However, a species does not fully occupy its range in the way a lake fills a basin and is instead best thought of as a cloud of points rather than an area per se. Samples of species presence or abundance are subject to issues of both inherent detectability and stochastic detectability due to sample locations in space and time. In addition, populations fluctuate in space and time. These factors mean that the population centroid, range area, and range margin are not deterministic. Examples from the literature demonstrate that multidirectional range changes are ubiquitous due to stochastic effects. Confounding factors, particularly due to human activities such as land use change, also complicate inference about range changes. Herein, statistical tests for centroid and margin changes in the context of stochastic fluctuations of clouds of points and sample error are demonstrated. Scale-dependent area analysis and tests for range area change are presented along with tests for responses at the community level (suites of species). This test allows for evaluation of change in spatial pattern for patchy populations with or without outliers. Geographic range change can reliably be tested with statistics based on distributions of clouds of observed points rather than bounded areas per se, if potential confounding is taken into account.