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Understanding how disturbance shapes the dynamics of ecological systems is of fundamental importance in ecology. One emerging approach to revealing and appreciating disturbance effects involves examining disturbance-driven changes in the variability of ecological responses. Variability is rarely employed as a response variable to assess the influence of disturbance, but recent studies indicate that it can be an extremely sensitive metric, capturing differences obscured by averaging and conveying important ecological information about underlying causal processes. In this paper, we present a conceptual model to understand and predict the effects of disturbance on variability. The model estimates qualitative changes in variability by considering disturbance extent, frequency and intensity, as well as ecosystem recovery, and thereby captures not only the immediate effects of disturbance but also those that arise over time due to the biotic response to an event. We evaluate how well the model performs by comparing predictions with empirical results from studies examining a wide variety of disturbances and ecosystems, and discuss factors that may modify or even confound predictions. We include a concise guide to characterizing and detecting changes in variability, highlighting the most common and easily applied methods and conclude by describing several future directions for research. By considering variability as a response to disturbance, we gain another metric of fundamental system behaviour, an improved ability to identify organizing features of ecosystems and a better understanding of the predictability of disturbance-driven change – all critical aspects of assessing ecosystem response to disturbance. [ABSTRACT FROM AUTHOR]

The provisioning of sustaining goods and services that we obtain from natural ecosystems is a strong economic justification for the conservation of biological diversity. Understanding the relationship between these goods and services and changes in the size, arrangement, and quality of natural habitats is a fundamental challenge of natural resource management. In this paper, we describe a new approach to assessing the implications of habitat loss for loss of ecosystem services by examining how the provision of different ecosystem services is dominated by species from different trophic levels. We then develop a mathematical model that illustrates how declines in habitat quality and quantity lead to sequential losses of trophic diversity. The model suggests that declines in the provisioning of services will initially be slow but will then accelerate as species from higher trophic levels are lost at faster rates. Comparison of these patterns with empirical examples of ecosystem collapse (and assembly) suggest similar patterns occur in natural systems impacted by anthropogenic change. In general, ecosystem goods and services provided by species in the upper trophic levels will be lost before those provided by species lower in the food chain. The decrease in terrestrial food chain length predicted by the model parallels that observed in the oceans following overexploitation. The large area requirements of higher trophic levels make them as susceptible to extinction as they are in marine systems where they are systematically exploited. Whereas the traditional species area curve suggests that 50% of species are driven extinct by an order-of-magnitude decline in habitat abundance, this magnitude of loss may represent the loss of an entire trophic level and all the ecosystem services performed by the species on this trophic level. [ABSTRACT FROM AUTHOR]

The species–time relationship (STR) describes how the species richness of a community increases with the time span over which the community is observed. This pattern has numerous implications for both theory and conservation in much the same way as the species–area relationship (SAR). However, the STR has received much less attention and to date only a handful of papers have been published on the pattern. Here we gather together 984 community time-series, representing 15 study areas and nine taxonomic groups, and evaluate their STRs in order to assess the generality of the STR, its consistency across ecosystems and taxonomic groups, its functional form, and its relationship to local species richness. In general, STRs were surprisingly similar across major taxonomic groups and ecosystem types. STRs tended to be well fit by both power and logarithmic functions, and power function exponents typically ranged between 0.2 and 0.4. Communities with high richness tended to have lower STR exponents, suggesting that factors increasing richness may simultaneously decrease turnover in ecological systems. Our results suggest that the STR is as fundamental an ecological pattern as the SAR, and raise questions about the general processes underlying this pattern. They also highlight the dynamic nature of most species assemblages, and the need to incorporate time scale in both basic and applied research on species richness patterns. [ABSTRACT FROM AUTHOR]