Bradford, Mark A.; Davies, Christian A.; Frey, Serita D.; Maddox, Thomas R.; Melillo, Jerry M.; Mohan, Jacqueline E.; Reynolds, James F.; Treseder, Kathleen K.; Wallenstein, Matthew D.
doi: 10.1111/j.1461-0248.2008.01251.xpmid: 19046360
In the short‐term heterotrophic soil respiration is strongly and positively related to temperature. In the long‐term, its response to temperature is uncertain. One reason for this is because in field experiments increases in respiration due to warming are relatively short‐lived. The explanations proposed for this ephemeral response include depletion of fast‐cycling, soil carbon pools and thermal adaptation of microbial respiration. Using a > 15 year soil warming experiment in a mid‐latitude forest, we show that the apparent ‘acclimation’ of soil respiration at the ecosystem scale results from combined effects of reductions in soil carbon pools and microbial biomass, and thermal adaptation of microbial respiration. Mass‐specific respiration rates were lower when seasonal temperatures were higher, suggesting that rate reductions under experimental warming likely occurred through temperature‐induced changes in the microbial community. Our results imply that stimulatory effects of global temperature rise on soil respiration rates may be lower than currently predicted.
Tylianakis, Jason M.; Didham, Raphael K.; Bascompte, Jordi; Wardle, David A.
doi: 10.1111/j.1461-0248.2008.01250.xpmid: 19062363
The main drivers of global environmental change (CO2 enrichment, nitrogen deposition, climate, biotic invasions and land use) cause extinctions and alter species distributions, and recent evidence shows that they exert pervasive impacts on various antagonistic and mutualistic interactions among species. In this review, we synthesize data from 688 published studies to show that these drivers often alter competitive interactions among plants and animals, exert multitrophic effects on the decomposer food web, increase intensity of pathogen infection, weaken mutualisms involving plants, and enhance herbivory while having variable effects on predation. A recurrent finding is that there is substantial variability among studies in both the magnitude and direction of effects of any given GEC driver on any given type of biotic interaction. Further, we show that higher order effects among multiple drivers acting simultaneously create challenges in predicting future responses to global environmental change, and that extrapolating these complex impacts across entire networks of species interactions yields unanticipated effects on ecosystems. Finally, we conclude that in order to reliably predict the effects of GEC on community and ecosystem processes, the greatest single challenge will be to determine how biotic and abiotic context alters the direction and magnitude of GEC effects on biotic interactions.
Darling, Emily S.; Côté, Isabelle M.
doi: 10.1111/j.1461-0248.2008.01243.xpmid: 18785986
There is increasing concern that multiple drivers of ecological change will interact synergistically to accelerate biodiversity loss. However, the prevalence and magnitude of these interactions remain one of the largest uncertainties in projections of future ecological change. We address this uncertainty by performing a meta‐analysis of 112 published factorial experiments that evaluated the impacts of multiple stressors on animal mortality in freshwater, marine and terrestrial communities. We found that, on average, mortalities from the combined action of two stressors were not synergistic and this result was consistent across studies investigating different stressors, study organisms and life‐history stages. Furthermore, only one‐third of relevant experiments displayed truly synergistic effects, which does not support the prevailing ecological paradigm that synergies are rampant. However, in more than three‐quarters of relevant experiments, the outcome of multiple stressor interactions was non‐additive (i.e. synergies or antagonisms), suggesting that ecological surprises may be more common than simple additive effects.
Crain, Caitlin Mullan; Kroeker, Kristy; Halpern, Benjamin S.
doi: 10.1111/j.1461-0248.2008.01253.xpmid: 19046359
Humans impact natural systems in a multitude of ways, yet the cumulative effect of multiple stressors on ecological communities remains largely unknown. Here we synthesized 171 studies that manipulated two or more stressors in marine and coastal systems and found that cumulative effects in individual studies were additive (26%), synergistic (36%), and antagonistic (38%). The overall interaction effect across all studies was synergistic, but interaction type varied by response level (community: antagonistic, population: synergistic), trophic level (autotrophs: antagonistic, heterotrophs: synergistic), and specific stressor pair (seven pairs additive, three pairs each synergistic and antagonistic). Addition of a third stressor changed interaction effects significantly in two‐thirds of all cases and doubled the number of synergistic interactions. Given that most studies were performed in laboratories where stressor effects can be carefully isolated, these three‐stressor results suggest that synergies may be quite common in nature where more than two stressors almost always coexist. While significant gaps exist in multiple stressor research, our results suggest an immediate need to account for stressor interactions in ecological studies and conservation planning.
Schick, Robert S.; Loarie, Scott R.; Colchero, Fernando; Best, Benjamin D.; Boustany, Andre; Conde, Dalia A.; Halpin, Patrick N.; Joppa, Lucas N.; McClellan, Catherine M.; Clark, James S.
doi: 10.1111/j.1461-0248.2008.01249.xpmid: 19046362
Pringle, Robert M.; Fox‐Dobbs, Kena
doi: 10.1111/j.1461-0248.2008.01252.xpmid: 19046361
Understanding food‐web dynamics requires knowing whether species assemblages are compartmentalized into distinct energy channels, and, if so, how these channels are structured in space. We used isotopic analyses to reconstruct the food web of a Kenyan wooded grassland. Insect prey were relatively specialized consumers of either C3 (trees and shrubs) or C4 (grasses) plants. Arboreal predators (arthropods and geckos) were also specialized, deriving c. 90% of their diet from C3‐feeding prey. In contrast, ground‐dwelling predators preyed considerably upon both C3‐ and C4‐feeding prey. This asymmetry suggests a gravity‐driven subsidy of the terrestrial predator community, whereby tree‐dwelling prey fall and are consumed by ground‐dwelling predators. Thus, predators in general couple the C3 and C4 components of this food web, but ground‐dwelling predators perform this ecosystem function more effectively than tree‐dwelling ones. Although prey subsidies in vertically structured terrestrial habitats have received little attention, they are likely to be common and important to food‐web organization.
Graham, Catherine H.; Fine, Paul V. A.
doi: 10.1111/j.1461-0248.2008.01256.xpmid: 19046358
A key challenge in ecological research is to integrate data from different scales to evaluate the ecological and evolutionary mechanisms that influence current patterns of biological diversity. We build on recent attempts to incorporate phylogenetic information into traditional diversity analyses and on existing research on beta diversity and phylogenetic community ecology. Phylogenetic beta diversity (phylobetadiversity) measures the phylogenetic distance among communities and as such allows us to connect local processes, such as biotic interactions and environmental filtering, with more regional processes including trait evolution and speciation. When combined with traditional measures of beta diversity, environmental gradient analyses or ecological niche modelling, phylobetadiversity can provide significant and novel insights into the mechanisms underlying current patterns of biological diversity.
Cloern, James E.; Jassby, Alan D.
doi: 10.1111/j.1461-0248.2008.01244.xpmid: 18793308
Seasonal fluctuations of plant biomass and photosynthesis are key features of the Earth system because they drive variability of atmospheric CO2, water and nutrient cycling, and food supply to consumers. There is no inventory of phytoplankton seasonal cycles in nearshore coastal ecosystems where forcings from ocean, land and atmosphere intersect. We compiled time series of phytoplankton biomass (chlorophyll a) from 114 estuaries, lagoons, inland seas, bays and shallow coastal waters around the world, and searched for seasonal patterns as common timing and amplitude of monthly variability. The data revealed a broad continuum of seasonal patterns, with large variability across and within ecosystems. This contrasts with annual cycles of terrestrial and oceanic primary producers for which seasonal fluctuations are recurrent and synchronous over large geographic regions. This finding bears on two fundamental ecological questions: (1) how do estuarine and coastal consumers adapt to an irregular and unpredictable food supply, and (2) how can we extract signals of climate change from phytoplankton observations in coastal ecosystems where local‐scale processes can mask responses to changing climate?
Showing 1 to 10 of 11 Articles
Animal movement has been the focus on much theoretical and empirical work in ecology over the last 25 years. By studying the causes and consequences of individual movement, ecologists have gained greater insight into the behavior of individuals and the spatial dynamics of populations at increasingly higher levels of organization. In particular, ecologists have focused on the interaction between individuals and their environment in an effort to understand future impacts from habitat loss and climate change. Tools to examine this interaction have included: fractal analysis, first passage time, Lévy flights, multi‐behavioral analysis, hidden markov models, and state‐space models. Concurrent with the development of movement models has been an increase in the sophistication and availability of hierarchical bayesian models. In this review we bring these two threads together by using hierarchical structures as a framework for reviewing individual models. We synthesize emerging themes in movement ecology, and propose a new hierarchical model for animal movement that builds on these emerging themes. This model moves away from traditional random walks, and instead focuses inference on how moving animals with complex behavior interact with their landscape and make choices about its suitability.