Detecting Nonadditive Biotic Interactions and Assessing Their Biological Relevance among Temperate Rainforest Trees

AbstractInteractions between and within abiotic and biotic processes generate nonadditive density-dependent effects on species performance that can vary in strength or direction across environments. If ignored, nonadditivities can lead to inaccurate predictions of species responses to environmental and compositional changes. While there are increasing empirical efforts to test the constancy of pairwise biotic interactions along environmental and compositional gradients, few assess both simultaneously. Using a nationwide forest inventory that spans broad ambient temperature and moisture gradients throughout New Zealand, we address this gap by analyzing the diameter growth of six focal tree species as a function of neighbor densities and climate, as well as neighbor × climate and neighbor × neighbor statistical interactions. The most complex model featuring all interaction terms had the highest predictive accuracy. Compared with climate variables, biotic interactions typically had stronger effects on diameter growth, especially when subjected to nonadditivities from local climatic conditions and the density of intermediary species. Furthermore, statistically strong (or weak) nonadditivities could be biologically irrelevant (or significant) depending on whether a species pair typically interacted under average or more extreme conditions. Our study highlights the importance of considering both the statistical potential and the biological relevance of nonadditive biotic interactions when assessing species performance under global change.

Mean species responses predict effects of environmental change on coexistence

Environmental change research is plagued by the curse of dimensionality: the number of communities at risk and the number of environmental drivers are both large. This raises the pressing question if a general understanding of ecological effects is achievable. Here, we show evidence that this is indeed possible. Using theoretical and simulation-based evidence for bi- and tritrophic communities, we show that environmental change effects on coexistence are proportional to mean species responses and depend on how trophic levels on average interact prior to environmental change. We then benchmark our findings using relevant cases of environmental change, showing that means of temperature optima and of species sensitivities to pollution predict concomitant effects on coexistence. Finally, we demonstrate how to apply our theory to the analysis of field data, finding support for effects of land use change on coexistence in natural invertebrate communities.

Impact of climate change on alpine plant community in Qilian Mountains of China

There is growing evidence that mountains are experiencing some of the highest rates of climate warming, but assessment of the ecological impacts of climate change is often limited due to a lack of long-term monitoring data for comparative study in many ecosystems. In this study, we present an empirical work for assessing ecological responses with botanical legacy data in the Qilian Mountains of China. Plot-scale and transect-wide survey was conducted for alpine shrub communities along an elevational gradient 20 years ago. Recently, we resampled the permanent plots to investigate how the community changes may be linked to climatic variability. We found no significant temporal shifts in species richness; but the community structure underwent substantial changes, as indicated by visible shifts in the relative density of dominant shrub species and the frequency of occurrence of understory herbaceous species. This reshuffling of plant community composition reflected a series of complex responses to climate change. Specifically, wet-demanding species have become more frequent due to the recently enhanced precipitation, while the replacement of some low-statured plants with different requirements for light was indirectly regulated by climate warming via reshaping the altitudinal patterns of dominant shrubs. Climate-mediated shifts in shrub species distribution altered the expected evolutional trajectory of alpine community, which increased the complexity and nonlinearity of the responses of the communities at different altitudes to climatic variability. Our results suggested that in-depth knowledge of indirect effects can facilitate to lessen the uncertainty in predicting future community dynamics in a changing climate.

Hidden layers of density dependence in consumer feeding rates

Functional responses relate a consumer's feeding rates to variation in its abiotic and biotic environment, providing insight into consumer behaviour and fitness, and underpinning population and food-web dynamics. Despite their broad relevance and long-standing history, we show here that the types of density dependence found in classic resource- and consumer-dependent functional-response models equate to strong and often untenable assumptions about the independence of processes underlying feeding rates. We first demonstrate mathematically how to quantify non-independence between feeding and consumer interference and between feeding on multiple resources. We then analyse two large collections of functional-response data sets to show that non-independence is pervasive and borne out in previously hidden forms of density dependence. Our results provide a new lens through which to view variation in consumer feeding rates and disentangle the biological underpinnings of species interactions in multi-species contexts.

Direct and indirect effects of environmental factors, spatial constraints, and functional traits on shaping the plant diversity of montane forests

Understanding the relative importance of the factors driving the patterns of biodiversity is a key research topic in community ecology and biogeography. However, the main drivers of plant species diversity in montane forests are still not clear. In addition, most existing studies make no distinction between direct and indirect effects of environmental factors and spatial constraints on plant biodiversity. Using data from 107 montane forest plots in Sichuan Giant Panda habitat, China, we quantified the direct and indirect effects of abiotic environmental factors, spatial constraints, and plant functional traits on plant community diversity. Our results showed significant correlations between abiotic environmental factors and trees (r = .10, p value = .001), shrubs (r = .19, p value = .001), or overall plant diversity (r = .18, p value = .001) in montane forests. Spatial constraints also showed significant correlations with trees and shrubs. However, no significant correlations were found between functional traits and plant community diversity. Moreover, the diversity (richness and abundance) of shrubs, trees, and plant communities was directly affected by precipitation, latitude, and altitude. Mean annual temperature (MAT) had no direct effect on the richness of tree and plant communities. Further, MAT and precipitation indirectly affected plant communities via the tree canopy. The results revealed a stronger direct effect on montane plant diversity than indirect effect, suggesting that single-species models may be adequate for forecasting the impacts of climate factors in these communities. The shifting of tree canopy coverage might be a potential indicator for trends of plant diversity under climate change.

Limiting Similarity? The Ecological Dynamics of Natural Selection among Resources and Consumers Caused by Both Apparent and Resource Competition

Much of ecological theory presumes that natural selection should foster species coexistence by phenotypically differentiating competitors so that the stability of the community is increased, but whether this will actually occur is a question of the ecological dynamics of natural selection. I develop an evolutionary model of consumer-resource interactions based on MacArthur's and Tilman's classic works, including both resource and apparent competition, to explore what fosters or retards the differentiation of resources and their consumers. Analyses of this model predict that consumers will differentiate only on specific ranges of environmental gradients (e.g., greater productivity, weaker stressors, lower structural complexity), and where it occurs, the magnitude of differentiation also depends on gradient position. In contrast to "limiting similarity" expectations, greater intraspecific phenotypic variance results in less differentiation among the consumers because of how phenotypic variation alters the fitness landscapes driving natural selection. In addition, the final structure of the community that results from the coevolution of these interacting species may be highly contingent on the initial properties of the species as the community is being assembled. These results highlight the fact that evolutionary conclusions about community structure cannot be based on ecological arguments of community stability or coexistence but rather must be explicitly based on the ecological dynamics of natural selection.

Direct effects of warming increase woody plant abundance in a subarctic wetland

Both the direct effects of warming on a species' vital rates and indirect effects of warming caused by interactions with neighboring species can influence plant populations. Furthermore, herbivory mediates the effects of warming on plant community composition in many systems. Thus, determining the importance of direct and indirect effects of warming, while considering the role of herbivory, can help predict long-term plant community dynamics. We conducted a field experiment in the coastal wetlands of western Alaska to investigate how warming and herbivory influence the interactions and abundances of two common plant species, a sedge, Carex ramenskii, and a dwarf shrub, Salix ovalifolia. We used results from the experiment to model the equilibrium abundances of the species under different warming and grazing scenarios and to determine the contribution of direct and indirect effects to predict population changes. Consistent with the current composition of the landscape, model predictions suggest that Carex is more abundant than Salix under ambient temperatures with grazing (53% and 27% cover, respectively). However, with warming and grazing, Salix becomes more abundant than Carex (57% and 41% cover, respectively), reflecting both a negative response of Carex and a positive response of Salix to warming. While grazing reduced the cover of both species, herbivory did not prevent a shift in dominance from sedges to the dwarf shrub. Direct effects of climate change explained about 97% of the total predicted change in species cover, whereas indirect effects explained only 3% of the predicted change. Thus, indirect effects, mediated by interactions between Carex and Salix, were negligible, likely due to use of different niches and weak interspecific interactions. Results suggest that a 2°C increase could cause a shift in dominance from sedges to woody plants on the coast of western Alaska over decadal timescales, and this shift was largely a result of the direct effects of warming. Models predict this shift with or without goose herbivory. Our results are consistent with other studies showing an increase in woody plant abundance in the Arctic and suggest that shifts in plant-plant interactions are not driving this change.

Direct effects dominate responses to climate perturbations in grassland plant communities

Theory predicts that strong indirect effects of environmental change will impact communities when niche differences between competitors are small and variation in the direct effects experienced by competitors is large, but empirical tests are lacking. Here we estimate negative frequency dependence, a proxy for niche differences, and quantify the direct and indirect effects of climate change on each species. Consistent with theory, in four of five communities indirect effects are strongest for species showing weak negative frequency dependence. Indirect effects are also stronger in communities where there is greater variation in direct effects. Overall responses to climate perturbations are driven primarily by direct effects, suggesting that single species models may be adequate for forecasting the impacts of climate change in these communities.