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Across biomes, soil biodiversity promotes ecosystem functions. However, whether this relationship will be maintained within ecosystems under climate change is uncertain. Here, using two long-term soil warming experiments, we investigated how warming affects the relationship between ecosystem functions and bacterial diversity across seasons, soil horizons, and warming duration. Soils were sampled from these warming experiments located at the Harvard Forest Long-Term Ecological Research (LTER) site, where soils had been heated +5°C above ambient for 13 or 28 years at the time of sampling. We assessed seven measurements representative of different ecosystem functions and nutrient pools. We also surveyed bacterial community diversity. We found that ecosystem function was significantly affected by season, with autumn samples having a higher intercept than summer samples in our model, suggesting a higher overall baseline of ecosystem function in the fall. The effect of warming on bacterial diversity was similarly affected by season, where warming in the summer was associated with decreased bacterial evenness in the organic horizon. Despite the decreased bacterial evenness in the warmed plots, we found that the relationship between ecosystem function and bacterial diversity was unaffected by warming or warming duration. Our findings highlight that season is a consistent driver of ecosystem function as well as a modulator of climate change effects on bacterial community evenness. 

For decades, multiple-driver/stressor research has examined interactions among drivers that will undergo large changes in the future: temperature, pH, nutrients, oxygen, pathogens, and more. However, the most commonly used experimental designs—present-versus-future and ANOVA—fail to contribute to general understanding or predictive power. Linking experimental design to process-based mathematical models would help us predict how ecosystems will behave in novel environmental conditions. We review a range of experimental designs and assess the best experimental path toward a predictive ecology. Full factorial response surface, fractional factorial, quadratic response surface, custom, space-filling, and especially optimal and sequential/adaptive designs can help us achieve more valuable scientific goals. Experiments using these designs are challenging to perform with long-lived organisms or at the community and ecosystem levels. But they remain our most promising path toward linking experiments and theory in multiple-driver research and making accurate, useful predictions. 

Competition is a pervasive interaction known to structure ecological communities. The Lotka-Volterra (LV) model has been foundational for our understanding of competition, and trait-based LV models have been used to model community assembly and eco-evolutionary phenomena like diversification. The intrinsic growth rate function is determined by the underlying resource distribution and is a key deter- minant of the resulting diversity, traits and abundances of species. In these models, the width of the resource distribution relative to the width of the competition kernel has been identified as a key param- eter that leads to diversification. However, studies have only investigated the impact of width at just a few discrete values, while also often assuming the intrinsic growth rate function to be unimodal. Thus, the impact of the underlying resource distribution’s width and shape together remains incompletely explored, particularly for large, diverse communities. In this study, we vary its width continuously for two shapes (unimodal and bimodal) to explore its impact on community structure. When the resource distribution is very narrow in both the unimodal bimodal cases, competition is strong, leading to exclu- sion of all but the best-adapted species. Wider resource distributions allow stable coexistence, where the traits of the species depend on the shape of the resource distribution. Extremely wide resource distribu- tions support a diverse community, where the strength of competition ultimately determines the diver- sity and traits of coexisting species, but their abundances reflect the underlying resource distribution. Further, competition acts to maximize the use of available resources among the competing species. For large communities, the shape of resource distribution becomes immaterial and the width determines the diversity. These results affirm and extend our understanding of limiting similarity. 

Abstract While natural communities can contain hundreds of species, modern coexistence theory focuses primarily on species pairs. Alternatively, the structural stability approach considers the feasibility of equilibria, gaining scalability to larger communities but sacrificing information about dynamic stability. Three‐species competitive communities are a bridge to more‐diverse communities. They display novel phenomena while remaining amenable to mathematical analysis, but remain incompletely understood. Here, we combine these approaches to identify the key quantities that determine three‐species competition outcomes. We show that pairwise niche overlap and fitness differences are insufficient to completely characterize competitive outcomes, which requires a strictly triplet‐wise quantity: cyclic asymmetry, which underlies intransitivity. Low pairwise niche overlap stabilizes the triplet, while high fitness differences promote competitive exclusion. The effect of cyclic asymmetry on stability is complex and depends on pairwise niche overlap. In summary, we elucidate how pairwise niche overlap, fitness differences and cyclic asymmetry determine three‐species competition outcomes.