ALBERT

Description: Theory describing the positive effects of patch size and connectivity on diversity in fragmented systems has stimulated a large body of empirical work, yet predicting when and how local species interactions mediate these responses remains challenging. We used insects that specialize on milkweed plants as a model metacommunity to investigate how local predation alters the effects of biogeographic constraints on species distributions. Species-specific dispersal ability and susceptibility to predation were used to predict when patch size and connectivity should shape species distributions, and when these should be modified by local predator densities. We surveyed specialist herbivores and their predators in milkweed patches in two matrix types, a forest and an old field. Predator-resistant species showed the predicted direct positive effects of patch size and connectivity on occupancy rates. For predator-susceptible species, predators consistently altered the impact of biogeographic constraints, rather than acting independently. Finally, differences between matrix types in species’ responses and overall occupancy rates indicate a potential role of the inter-patch environment in mediating the joint effects of predators and spatial drivers. Together, these results highlight the importance of local top-down pressure in mediating classic biogeographic relationships, and demonstrate how species-specific responses to local and regional constraints can be used to predict these effects. This article is protected by copyright. All rights reserved

Description: How plant functional traits (e.g. seed mass) drive species abundance within communities remains an unsolved question. Borrowing concepts from natural selection theory, we propose that trait–abundance relationships can generally correspond to one of three modes of trait selection: directional (a rectilinear relationship, where species at one end of a trait axis are most abundant), stabilizing (an n-shaped relationship), and disruptive (a u-shaped relationship). Stabilizing selection (i.e. the functional convergence of abundant species) would result from positive density-dependent interactions (e.g. facilitation) or due to generalized trade-offs in resource acquisition/use, while disruptive selection (i.e. the divergence of abundant species) would result from negative density-dependent interactions (e.g. competition) or due to environmental heterogeneity. These selection modes can be interpreted as proxies for community-level trait–fitness functions, which establish the degree to which traits are truly “functional”. We searched for selection modes in a desert annual-plant community in Argentina (which was divided into winter and summer guilds) to test the hypothesis that the relative importance of disruptive mechanisms (competition, disturbances) decreases with the increase of abiotic stress, a stabilizing agent. Average density was analyzed as a function of eight traits generally linked to resource acquisition and competitive ability (maximum plant height, leaf size, specific leaf area, specific root length), resource retention and stress tolerance (leaf dissection, leaf dry matter content, specific root volume), and regeneration (seed mass) using multiple quadratic-regression models. Trait selection was stabilizing and/or directional when the environment was harshest (winter) while disruptive and/or directional when conditions were milder (summer). Selection patterns differed between guilds for two important traits: plant height and seed mass. These results suggest that abiotic stress may drive within-community functional convergence independently of the trait considered, opposing the view that some traits may be inherently convergent while others divergent. Our quadratic model-based approach provides standardized metrics of both linear and nonlinear selection that may allow simple comparisons among communities subjected to contrasting environmental conditions. These concepts, rooted in natural selection theory, may clarify the functional link between traits and species abundance, and thus help untangle the contributions of deterministic and stochastic processes on community assembly. This article is protected by copyright. All rights reserved

Description: Invasive plants can alter ecosystem properties, leading to changes in the ecosystem services on which humans depend. However, generalizing about these effects is difficult because invasive plants represent a wide range of life forms, and invaded ecosystems differ in their plant communities and abiotic conditions. We hypothesize that differences in traits between the invader and native species can be used to predict impacts and so aid generalization. We further hypothesize that environmental conditions at invaded sites modify the effect of trait differences and so combine with traits to predict invasion impacts. To test these hypotheses, we used systematic review to compile data on changes in aboveground and soil carbon pools following non-native plant invasion from studies across the World. Maximum potential height ( H max ) of each species was drawn from trait databases and other sources. We used meta-regression to assess which of invasive species’ H max , differences in this height trait between native and invasive plants, and climatic water deficit, a measure of water stress, were good predictors of changes in carbon pools following invasion. We found that aboveground biomass in invaded ecosystems relative to uninvaded ones increased as the value of H max of invasive relative to native species increased, but that this effect was reduced in more water stressed ecosystems. Changes in soil carbon pools were also positively correlated with the relative H max of invasive species, but were not altered by water stress. This study is one of the first to show quantitatively that the impact of invasive species on an ecosystem may depend on differences in invasive and native species’ traits, rather than solely the traits of invasive species. Our study is also the first to show that the influence of trait differences can be altered by climate. Further developing our understanding of the impacts of invasive species using this framework could help researchers to identify not only potentially dangerous invasive species, but also the ecosystems where impacts are likely to be greatest. This article is protected by copyright. All rights reserved.

Description: Placing invasion in a more complete food-web context expands our understanding of species invasions to reflect the inherent complexity of ecological networks. Garlic mustard ( Alliaria petiolata ) has traditionally been predicted to dominate native communities through mechanisms embodied in popular hypotheses such as direct plant-plant interactions (allelopathy) and plant-herbivore interactions (enemy escape). However, garlic mustard also interacts directly with native predators by providing habitat for web-building spiders, which colonize the dry fruit structures (siliques) that garlic mustard leaves behind after it senesces. This interaction may lead to altered food web structure, resulting previously unexamined invasion consequences. This idea was tested in a field experiment including three treatments in which garlic mustard siliques were left intact (S+), removed (S-), or native species dominated and garlic mustard was absent (N). When siliques were intact, estimated insect abundance was locally reduced in invaded plots compared to native plots, but this relationship disappeared when siliques were removed. Phosphorus availability and the growth of one native plant species were both elevated in invaded plots where siliques were intact compared to plots where siliques were removed. Results indicate that garlic mustard's close association with web-building spiders initiates cascading invader impacts on the native community and ecosystem properties. This work supports recent theory suggesting that taking a broader food web perspective may help predict invasion impacts in different environmental contexts. This article is protected by copyright. All rights reserved.

Description: Many host-plants exhibit genetic variation in resistance to pathogens; however, little is known about the extent to which genetic variation in pathogen resistance influences other members of the host-plant community, especially arthropods at higher trophic levels. We addressed this knowledge gap by using a common garden experiment to examine whether genotypes of Populus trichocarpa varied in resistance to a leaf-blistering pathogen, Taphrina sp., and in the density of web-building spiders, the dominant group of predatory arthropods. In addition, we examined whether variation in spider density was explained by variation in the density and size of leaf blisters caused by Taphrina . We found that P. trichocarpa genotypes exhibited strong differences in their resistance to Taphrina and that P. trichocarpa genotypes that were more susceptible to Taphrina supported more web-building spiders, the dominant group of predatory arthropods. We suspect that this result is caused by blisters increasing the availability of suitable habitat for predators, and not due to variation in herbivores because including herbivore density as a covariate did not affect our models. Our study highlights a novel pathway by which genetic variation in pathogen resistance may affect higher trophic levels in arthropod communities. This article is protected by copyright. All rights reserved.

Description: By inflicting damage to prey tissues, consumer species may increase stress in prey hosts and reduce overall fitness (i.e., primary effects, such as growth or reproduction) or cause secondary effects by affecting prey interactions with other species such as microbes. However, little is known about how abiotic conditions affect the outcomes of these biotic interactions. In coral reef communities, both nutrient enrichment and predation have been linked to reduced fitness and disease facilitation in corals, yet no study to date has tested their combined effects on corals or their associated microbial communities (i.e., microbiomes). Here, we assess the effects of grazing by a prevalent coral predator (the short coral snail, Coralliophila abbreviata ) and nutrient enrichment on staghorn coral, Acropora cervicornis , and its microbiomes using a factorial experiment and high-throughput DNA sequencing. We found that predation, but not nutrients, significantly reduced coral growth and increased mortality, tissue loss, and turf algae colonization. Partial predation and nutrient enrichment both independently altered coral microbiomes such that one bacterial genera came to dominate the microbial community. Nutrient-enriched corals were associated with significant increases in the genera Rickettsia , which is currently one of several microbial groups being investigated as a disease agent in this coral species. However, we found no effects of nutrient enrichment on coral health, disease, or their predators. This research suggests that in the several months following coral transplantation (i.e., restoration) or disturbance (i.e., recovery), Caribbean acroporid corals appear to be highly susceptible to negative effects caused by predators, but not or not yet susceptible to nutrient enrichment despite changes to their microbial communities. This article is protected by copyright. All rights reserved.

Description: The last decade has seen a dramatic increase in the use of species distribution models (SDMs) to characterize patterns of species’ occurrence and abundance. Efforts to parameterize SDMs often create a tension between the quality and quantity of data available to fit models. Estimation methods that integrate both standardized and non-standardized data types offer a potential solution to the trade-off between data quality and quantity. Recently several authors have developed approaches for jointly modeling two sources of data (one of high quality and one of lesser quality). We extend their work by allowing for explicit spatial autocorrelation in occurrence and detection error using a Multivariate Conditional Autoregressive (MVCAR) model and develop three models that share information in a less direct manner resulting in more robust performance when the auxiliary data is of lesser quality. We describe these three new approaches (‘Shared’, ‘Correlation’, ‘Covariates’) for combining data sources and show their use in a case study of the Brown-headed Nuthatch in the Southeastern U.S. and through simulations. All three of the approaches which used the second data source improved out-of-sample predictions relative to a single data source (‘Single’). When information in the second data source is of high quality, the Shared model performs the best, but the Correlation and Covariates model also perform well. When the information quality in the second data source is of lesser quality, the Correlation and Covariates model performed better suggesting they are robust alternatives when little is known about auxiliary data collected opportunistically or through citizen scientists. Methods that allow for both data types to be used will maximize the useful information available for estimating species distributions. This article is protected by copyright. All rights reserved.

Description: The effects of resource stoichiometry and growth rate on the elemental composition of biomass have been examined in a wide variety of organisms, but the interaction among these effects is often overlooked. To determine how growth rate and resource imbalance affect bacterial carbon (C): nitrogen (N): phosphorus (P) stoichiometry and elemental content, we cultured two strains of aquatic heterotrophic bacteria in chemostats at a range of dilution rates and P supply levels (C:P of 100:1 to 10,000:1). When growing below 50% of their maximum growth rate, P availability and dilution rate had strong interactive effects on biomass C:N:P, elemental quotas, cell size, respiration rate, and growth efficiency. In contrast, at faster growth rates, biomass stoichiometry was strongly homeostatic in both strains (C:N:P of 70:13:1 and 73:14:1) and elemental quotas of C, N, and P were tightly coupled (but not constant). Respiration and cell size increased with both growth rate and P limitation, and P limitation induced C accumulation and excess respiration. These results show that bacterial biomass stoichiometry is relatively constrained when all resources are abundant and growth rates are high, but at low growth rates resource imbalance is relatively more important than growth rate in controlling bacterial biomass composition. This article is protected by copyright. All rights reserved.

Description: Disease dynamics during pathogen invasion and establishment determine the impacts of disease on host populations and determine the mechanisms of host persistence. Temporal progression of prevalence and infection intensity illustrate whether tolerance, resistance, reduced transmission, or demographic compensation allow initially declining populations to persist. We measured infection dynamics of the fungal pathogen Pseudogymnoascus destructans that causes white-nose syndrome in bats by estimating pathogen prevalence and load in seven bat species at 167 hibernacula over a decade as the pathogen invaded, became established, and some host populations stabilized. Fungal loads increased rapidly and prevalence rose to nearly 100% at most sites within two years of invasion in six of seven species. Prevalence and loads did not decline over time despite huge reductions in colony sizes, likely due to an extensive environmental reservoir. However, there was substantial variation in fungal load among sites with persisting colonies, suggesting that both tolerance and resistance developed at different sites in the same species. In contrast, one species disappeared from hibernacula within three years of pathogen invasion. Variable host responses to pathogen invasion require different management strategies to prevent disease-induced extinction and to facilitate evolution of tolerance or resistance in persisting populations. This article is protected by copyright. All rights reserved.

Description: Demographic analysis can elucidate how driving factors, such as climate or species interactions,affect populations. One important question is how growth would respond to future changes in the mean intensity of a driving factor or in its variability, such as might be expected in a fluctuating and shifting climate. Here I develop an approach to computing new stochastic elasticities to address this question. The linchpin of this novel approach is the multidimensional demographic difference that expresses how a population responds to change in the driving factor between two discrete levels of intensity. I use this difference to design a perturbation matrix that links data from common empirical sampling schemes with rigorous theory for stochastic elasticities. Although the starting point is a difference, the products of this synthesis are true derivatives: they are elasticity with respect to the mean intensity of a driving factor, and elasticity with respect to variability in a driving factor. Applying the methods to published data, I demonstrate how these new elasticities can shed light on growth rate response within and at the boundary of the previously observed range of the driving factor, thus helpfully indicating nonlinearity in the observed and in the potential future response. The stochastic approach simplifies in a fixed environment, yielding a compact formula for deterministic elasticity to a driving factor. This article is protected by copyright. All rights reserved.