Challenges in quantifying, interpreting and predicting distributional shifts of marine species
C. Tara MarshallAsta AudzijonytėAlan BaudronCurtis ChampionNiall G. FallonAlan C. HaynieMelissa A. HaltuchBryony L. TownhillP. Daniël van DenderenGT PeclJohn K. PinnegarMalin L. PinskyPaul D. SpencerChristine C. StawitzJim Thorsen
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Interpreting Ecological Data The Interpretation of Ecological Data: A Primer on Classification and Ordination. Pielou E. C.. John Wiley & Sons, New York, 1984. 263 pp., illus. $32.50 (cloth). John H. Crow John H. Crow Department of Botany, Rutgers University, Newark, NJ 07102 Search for other works by this author on: Oxford Academic Google Scholar BioScience, Volume 36, Issue 3, March 1986, Pages 205–206, https://doi.org/10.2307/1310324 Published: 01 March 1986
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Abstract Anthropogenic climate change affects both phenology and distribution patterns of the world's biota including marine species. During the last decade, species distribution models have been more frequently used to assess the potential distributions of species and possible effects of climate change. However, unlike for terrestrial species, there have been few investigations assessing climate change effects on distribution patterns of marine organisms. An overview of marine species distribution modelling is given. Possibilities of how to characterize and project the environmental niches of species onto climatic change scenarios are highlighted and novel techniques for addressing specific needs in a 3‐D context are proposed. A detailed introduction into different modelling tools and databases for environmental parameters given provides a starting point for the application of these models. Application of a species distribution model and its projections onto a glacial and future scenario on a global scale are presented for the great white shark ( Carcharodon carcharias ) for illustrative purposes. An approach for addressing marine migratory species with seasonal distribution patterns is presented. Copyright © 2010 John Wiley & Sons, Ltd.
Species distribution
Environmental niche modelling
Carcharias
Marine species
Biota
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Environmental niche modelling
Correlative
Species distribution
Generalized additive model
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Abstract Changes in species distributions constitute strong evidence that global change is affecting ecosystems and biodiversity. Expansion of invasive species and retraction of endangered species are examples of environmental issues that need to be understood and addressed. Monitoring range shifts require that we can accurately estimate the state(s) of the system – that is, the present and past distributions – its rate of change, and assess the underlying causes. Existing monitoring programs differ in terms of data quality and coverage of the environmental space, and very few have considered different sources of errors as well as alternative explanations of observed changes. Modeling species distributions is needed to derive alternative predictions of future changes. The design of monitoring programs should assess the assumptions and the predictions of these models.
Species distribution
Environmental change
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Aim Species distribution models (SDMs) have been used to address a wide range of theoretical and applied questions in the terrestrial realm, but marine-based applications remain relatively scarce. In this review, we consider how conceptual and practical issues associated with terrestrial SDMs apply to a range of marine organisms and highlight the challenges relevant to improving marine SDMs. Location We include studies from both marine and terrestrial systems that encompass many geographic locations around the globe. Methods We first performed a literature search and analysis of marine and terrestrial SDMs in ISI Web of Science to assess trends and applications. Using knowledge from terrestrial applications, we critically evaluate the application of SDMs in marine systems in the context of ecological factors (dispersal, species interactions, aggregation and ontogenetic shifts) and practical considerations (data quality, alternative modelling approaches and model validation) that facilitate or create difficulties for model application. Results The relative importance of ecological factors to be considered when applying SDMs varies among terrestrial and marine organisms. Correctly incorporating dispersal is frequently considered an important issue for terrestrial models, but because there is greater potential for dispersal in the ocean, it is often less of a concern in marine SDMs. By contrast, ontogenetic shifts and feeding have received little attention in terrestrial SDM applications, but these factors are important to many marine SDMs. Opportunities also exist for applying more advanced SDM approaches in the marine realm, including mechanistic ecophysiological models, where water balance and heat transfer equations are simpler for some marine organisms relative to their terrestrial counterparts. Main conclusions SDMs have generally been under-utilized in the marine realm relative to terrestrial applications. Correlative SDM methods should be tested on a range of marine organisms, and we suggest further development of methods that address ontogenetic shifts and feeding interactions. We anticipate developments in, and cross-fertilization between, coupled correlative and process-based SDMs, mechanistic eco-physiological SDMs, and spatial population dynamic models for climate change and species invasion applications in particular. Comparisons of the outputs of different model types will provide insight that is useful for improved spatial management of marine species.
Species distribution
Temporal scales
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As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some "hotspots" of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option.
Environmental niche modelling
Species distribution
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