All ecosystems are exposed to gradual changes in climate, nutrient loading, habitat fragmentation or biotic exploitation. Nature is usually assumed to respond to gradual change in a smooth way. However, studies on lakes, coral reefs, oceans, forests and arid lands have shown that smooth change can be interrupted by sudden drastic switches to a contrasting state. Although diverse events can trigger such shifts, recent studies show that a loss of resilience usually paves the way for a switch to an alternative state. This suggests that strategies for sustainable management of such ecosystems should focus on maintaining resilience.

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Catastrophic shifts in ecosystems.

Metabolism provides a basis for using first principles of physics, chemistry, and biology to link the biology of individual organisms to the ecology of populations, communities, and ecosystems. Metabolic rate, the rate at which organisms take up, transform, and expend energy and materials, is the most fundamental biological rate. We have developed a quantitative theory for how metabolic rate varies with body size and temperature. Metabolic theory predicts how metabolic rate, by setting the rates of resource uptake from the environment and resource allocation to survival, growth, and reproduction, controls ecological processes at all levels of organization from individuals to the biosphere. Examples include: (1) life history attributes, including devel- opment rate, mortality rate, age at maturity, life span, and population growth rate; (2) population interactions, including carrying capacity, rates of competition and predation, and patterns of species diversity; and (3) ecosystem processes, including rates of biomass production and respiration and patterns of trophic dynamics. Data compiled from the ecological literature strongly support the theoretical predictions. Even- tually, metabolic theory may provide a conceptual foundation for much of ecology, just as genetic theory provides a foundation for much of evolutionary biology.

/pdf/toward-a-metabolic-theory-of-ecology-1dxmg8xr3n.pdf

Toward a metabolic theory of ecology

Recently, researchers in several areas of ecology and evolution have begun to change the way in which they analyze data and make biological inferences. Rather than the traditional null hypothesis testing approach, they have adopted an approach called model selection, in which several competing hypotheses are simultaneously confronted with data. Model selection can be used to identify a single best model, thus lending support to one particular hypothesis, or it can be used to make inferences based on weighted support from a complete set of competing models. Model selection is widely accepted and well developed in certain fields, most notably in molecular systematics and mark-recapture analysis. However, it is now gaining support in several other areas, from molecular evolution to landscape ecology. Here, we outline the steps of model selection and highlight several ways that it is now being implemented. By adopting this approach, researchers in ecology and evolution will find a valuable alternative to traditional null hypothesis testing, especially when more than one hypothesis is plausible.

https://faculty.washington.edu/skalski/classes/QERM597/papers/Johnson%20and%20Omland.pdf

Model selection in ecology and evolution

The package “adehabitat” for the R software: A tool for the analysis of space and habitat use by animals

Occasionally, surprisingly large shifts occur in ecosystems. Theory suggests that such shifts can be attributed to alternative stable states. Verifying this diagnosis is important because it implies a radically different view on management options, and on the potential effects of global change on such ecosystems. For instance, it implies that gradual changes in temperature or other factors might have little effect until a threshold is reached at which a large shift occurs that might be difficult to reverse. Strategies to assess whether alternative stable states are present are now converging in fields as disparate as desertification, limnology, oceanography and climatology. Here, we review emerging ways to link theory to observation, and conclude that although, field observations can provide hints of alternative stable states, experiments and models are essential for a good diagnosis.

/pdf/catastrophic-regime-shifts-in-ecosystems-linking-theory-to-4cjnkgwe9s.pdf

Catastrophic regime shifts in ecosystems: linking theory to observation

Why study movement? data for measuring movement modelling movement building behaviourally based models analysis of movement paths mass mark-recapture individual mark-recapture. Appendix A: diffusion for ecologists.

Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants

Complex Population Dynamics: A Theoretical/Empirical Synthesis

Although the possibility of complex dynamical behaviors-limit cycles, quasiperiodic oscillations, and aperiodic chaos-has been recognized theoretically, most ecologists are skeptical of their importance in nature. In this paper we develop a meth- odology for reconstructing endogenous (or deterministic) dynamics from ecological time series. Our method consists of fitting a response surface to the yearly population change as a function of lagged population densities. Using the version of the model that includes two lags, we fitted time-series data for 14 insect and 22 vertebrate populations. The 14 insect populations were classified as: unregulated (1 case), exponentially stable (three cases), damped oscillations (six cases), limit cycles (one case), quasiperiodic oscillations (two cases), and chaos (one case). The vertebrate examples exhibited a similar spectrum of dynamics, although there were no cases of chaos. We tested the results of the response-surface meth- odology by calculating autocorrelation functions for each time series. Autocorrelation pat- terns were in agreement with our findings of periodic behaviors (damped oscillations, limit cycles, and quasiperiodicity). On the basis of these results, we conclude that the complete spectrum of dynamical behaviors, ranging from exponential stability to chaos, is likely to be found among natural populations.

https://www.jstor.org/stable/pdfplus/1938740.pdf

Complex Dynamics in Ecological Time Series

Quantitative analysis of movement

We review the role of chaos and the study of chaos in ecology. We use sensitive dependence on initial conditions as the best heuristic definition of chaos. This definition forms the common theme for our review of approaches for demonstrating the importance of chaos in ecology. We emphasize that this

Peter Turchin

Papers

Quantitative analysis of movement : measuring and modeling population redistribution in animals and plants

Complex Population Dynamics: A Theoretical/Empirical Synthesis

Complex Dynamics in Ecological Time Series

Quantitative analysis of movement

Chaos in Ecology: Is Mother Nature a Strange Attractor?*