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Interannual variation of 45 annually resolved time series of environmental, limnological, and biotic parameters was quantified (1994-2009) in six lakes within 52000 km2 to test the hypothesis that influx of energy (E; as irradiance, heat, wind) varies synchronously among sites and induces temporal coherence in lakes and their food webs, whereas influx of mass (m; as water, solutes, particles) reduces synchrony because local catchments uniquely modify hydrologic inputs. Overall, 82% of parameters exhibited significant (P < 0.05) synchrony (S) estimated as mean pair-wise correlation of Z-transformed time series. Influx of E as atmospheric heat and irradiance was both more highly synchronous and less temporally variable (months-to-decades) than influx of m as summer precipitation, snow, or river discharge. Similarly, S of limnological parameters varied from 0.08 to 0.85, with variables known to be regulated by E influx (ice melt, gas solubility) up to twofold more coherent than those regulated by m inputs (organic solutes). Pairs of variables linked by simple direct mechanisms exhibited similar S values (air temperature and ice melt, nutrients and algae), whereas the coherence of other parameters (water temperature, mixing) was intermediate to that of multiple regulatory agents. Overall, aggregate measures of plankton density varied more coherently among lakes than did constituent taxa. These findings suggest that environmental variability is transmitted to most levels of aquatic ecosystems, but that the precise effects depend on whether E or in fluxes predominate, the coherence of each forcing mechanism, and the strength of linkages between exogenous forcing and lake response. [ABSTRACT FROM AUTHOR]

Researchers have long viewed patterns of species association as key to understanding the processes that structure communities. Community‐level tests of species association have received the most attention; however, pairwise species associations may offer greater opportunity for linking patterns to specific mechanisms. Although several tests of pairwise association have been developed, there remain gaps in our understanding of their performance. Consequently, it is unclear whether these methods reliably detect patterns of association, or if any one method is superior. We maximized association patterns for single species pairs in synthetic community matrices and examined how accurately five pairwise association tests found that pair, while not finding others (i.e., type I and II error rates). All tests are more likely to miss patterns of association than to falsely detect them. When we maximized association for a species pair that included one or more rare or common species, tests were frequently unable to identify that pair as significantly associated. Consequently, these tests are best suited for identifying significant associations between pairs of species that occur in an intermediate number of samples; for such pairs, three of the five tests considered here detected 100% of the pairs for which we maximized associations. [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-area relationship (SAR) plays a central role in biodiversity research, and recent work has increased awareness of its temporal analogue, the species-time relationship (STR). Here we provide evidence for a general' species-time-area relationship (STAR), in which species number is a function of the area and time span of sampling, as well as their interaction. For eight assemblages, ranging from lake zooplankton to desert rodents, this model outperformed a sampling-based model and two simpler models in which area and time had independent effects. In every case, the interaction term was negative, meaning that rates of species accumulation in space decreased with the time span of sampling, while species accumulation rates in time decreased with area sampled. Although questions remain about its precise functional form, the STAR provides a tool for scaling species richness across time and space, for comparing the relative rates of species turnover in space and time at different scales of sampling, and for rigorous testing of mechanisms proposed to drive community dynamics. Our results show that the SAR and STR are not separate relationships but two dimensions of one unified pattern. [ABSTRACT FROM AUTHOR]