Diversity loss from multiple interacting disturbances is regime-dependent.

Anthropogenic activities expose many ecosystems to multiple novel disturbances simultaneously. Despite this, how biodiversity responds to simultaneous disturbances remains unclear, with conflicting empirical results on their interactive effects. Here, we experimentally test how one disturbance (an invasive species) affects the diversity of a community over multiple levels of another disturbance regime (pulse mortality). Specifically, we invade stably coexisting bacterial communities under four different pulse frequencies, and compare their final resident diversity to uninvaded communities under the same pulse mortality regimes. Our experiment shows that the disturbances synergistically interact, such that the invader significantly reduces resident diversity at high pulse frequency, but not at low. This work therefore highlights the need to study simultaneous disturbance effects over multiple disturbance regimes as well as to carefully document unmanipulated disturbances, and may help explain the conflicting results seen in previous multiple-disturbance work.

Context-dependent representation of within- and between-model uncertainty: aggregating probabilistic predictions in infectious disease epidemiology.

Probabilistic predictions support public health planning and decision making, especially in infectious disease emergencies. Aggregating outputs from multiple models yields more robust predictions of outcomes and associated uncertainty. While the selection of an aggregation method can be guided by retrospective performance evaluations, this is not always possible. For example, if predictions are conditional on assumptions about how the future will unfold (e.g. possible interventions), these assumptions may never materialize, precluding any direct comparison between predictions and observations. Here, we summarize literature on aggregating probabilistic predictions, illustrate various methods for infectious disease predictions via simulation, and present a strategy for choosing an aggregation method when empirical validation cannot be used. We focus on the linear opinion pool (LOP) and Vincent average, common methods that make different assumptions about between-prediction uncertainty. We contend that assumptions of the aggregation method should align with a hypothesis about how uncertainty is expressed within and between predictions from different sources. The LOP assumes that between-prediction uncertainty is meaningful and should be retained, while the Vincent average assumes that between-prediction uncertainty is akin to sampling error and should not be preserved. We provide an R package for implementation. Given the rising importance of multi-model infectious disease hubs, our work provides useful guidance on aggregation and a deeper understanding of the benefits and risks of different approaches.

Pulse and Press Disturbances Have Different Effects on Transient Community Dynamics.

AbstractDisturbances are important determinants of diversity, and the combination of their aspects (e.g., disturbance intensity, frequency) can result in complex diversity patterns. Here, we leverage an important approach to classifying disturbances in terms of temporal span to understand the implications for species coexistence: pulse disturbances are acute and discrete events, while press disturbances occur continuously through time. We incorporate the resultant mortality rates into a common framework involving disturbance frequency and intensity. Press disturbances can be encoded into models in two distinct ways, and we show that the appropriateness of each depends on the type of data available. Using this framework, we compare the effects of pulse versus press disturbance on both asymptotic and transient dynamics of a two-species Lotka-Volterra competition model to understand how they engage with equalizing mechanisms of coexistence. We show that press and pulse disturbances differ in transient behavior, though their asymptotic diversity patterns are similar. Our work shows that these differences depend on how the underlying disturbance aspects interact and that the two ways of characterizing press disturbances can lead to contrasting interpretations of disturbance-diversity relationships. Our work demonstrates how theoretical modeling can strategically guide and help the interpretation of empirical work.

Disturbance-mediated invasions are dependent on community resource abundance.

Disturbances can facilitate biological invasions, with the associated increase in resource availability being a proposed cause. Here, we experimentally tested the interactive effects of disturbance regime (different frequencies of biomass removal at equal intensities) and resource abundance on invasion success using a factorial design containing five disturbance frequencies and three resource levels. We invaded populations of the bacterium Pseudomonas fluorescens with two ecologically different invader morphotypes: a fast-growing "colonizer" type and a slower growing "competitor" type. As resident populations were altered by the treatments, we additionally tested their effect on invader success. Disturbance frequency and resource abundance interacted to affect the success of both invaders, but this interaction differed between the invader types. The success of the colonizer type was positively affected by disturbance under high resources but negatively under low. However, disturbance negatively affected the success of the competitor type under high resource abundance but not under low or medium. Resident population changes did not alter invader success beyond direct treatment effects. We therefore demonstrate that the same disturbance regime can either be beneficial or detrimental for an invader depending on both community resource abundance and its life history. These results may help to explain some of the inconsistencies found in the disturbance-invasion literature.

How disturbance history alters invasion success: biotic legacies and regime change.

Disturbance is a key factor shaping ecological communities, but little is understood about how the effects of disturbance processes accumulate over time. When disturbance regimes change, historical processes may influence future community structure, for example, by altering invasibility compared to communities with stable regimes. Here, we use an annual plant model to investigate how the history of disturbance alters invasion success. In particular, we show how two communities can have different outcomes from species introduction, solely due to past differences in disturbance regimes that generated different biotic legacies. We demonstrate that historical differences can enhance or suppress the persistence of introduced species, and that biotic legacies generated by stable disturbance history decay over time, though legacies can persist for unexpectedly long durations. This establishes a formal theoretical foundation for disturbance legacies having profound effects on communities, and highlights the value of further research on the biotic legacies of disturbance.

Spatiotemporally Heterogeneous Population Dynamics of Gut Bacteria Inferred from Fecal Time Series Data.

A priority in gut microbiome research is to develop methods to investigate ecological processes shaping microbial populations in the host from readily accessible data, such as fecal samples. Here, we demonstrate that these processes can be inferred from the proportion of ingested microorganisms that is egested and their egestion time distribution, by using general mathematical models that link within-host processes to statistics from fecal time series. We apply this framework to Drosophila melanogaster and its gut bacterium Acetobacter tropicalis Specifically, we investigate changes in their interactions following ingestion of a food bolus containing bacteria in a set of treatments varying the following key parameters: the density of exogenous bacteria ingested by the flies (low/high) and the association status of the host (axenic or monoassociated with A. tropicalis). At 5 h post-ingestion, ~35% of the intact bacterial cells have transited through the gut with the food bolus and ~10% are retained in a viable and culturable state, leaving ~55% that have likely been lysed in the gut. Our models imply that lysis and retention occur over a short spatial range within the gut when the bacteria are ingested from a low density, but more broadly in the host gut when ingested from a high density, by both gnotobiotic and axenic hosts. Our study illustrates how time series data complement the analysis of static abundance patterns to infer ecological processes as bacteria traverse the host. Our approach can be extended to investigate how different bacterial species interact within the host to understand the processes shaping microbial community assembly.IMPORTANCE A major challenge to our understanding of the gut microbiome in animals is that it is profoundly difficult to investigate the fate of ingested microbial cells as they travel through the gut. Here, we created mathematical tools to analyze microbial dynamics in the gut from the temporal pattern of their abundance in fecal samples, i.e., without direct observation of the dynamics, and validated them with Drosophila fruit flies. Our analyses revealed that over 5 h after ingestion, most bacteria have likely died in the host or have been egested as intact cells, while some living cells have been retained in the host. Bacterial lysis or retention occurred across a larger area of the gut when flies ingest bacteria from high densities than when flies ingest bacteria from low densities. Our mathematical tools can be applied to other systems, including the dynamics of gut microbial populations and communities in humans.

Transient overexpression of alpha-Ca2+/calmodulin-dependent protein kinase II in the nucleus accumbens shell enhances behavioral responding to amphetamine.

Ca(2+)/calmodulin-dependent protein kinase II (CaMKII) is known to contribute to the expression of psychostimulant sensitization by regulating dopamine (DA) overflow from DA neuron terminals in the nucleus accumbens (NAcc). The present experiments explored the contribution of CaMKII in NAcc neurons postsynaptic to these terminals where it is known to participate in a number of signaling pathways that regulate responding to psychostimulant drugs. Exposure to amphetamine transiently increased alphaCaMKII levels in the shell but not the core of the NAcc. Thus, HSV (herpes simplex viral) vectors were used to transiently overexpress alphaCaMKII in NAcc neurons in drug-naive rats, and behavioral responding to amphetamine was assessed. Transiently overexpressing alphaCaMKII in the NAcc shell led to long-lasting enhancement of amphetamine-induced locomotion and self-administration manifested when alphaCaMKII levels were elevated and persisting long after they had returned to baseline. Enhanced locomotion was not observed after infection in the NAcc core or sites adjacent to the NAcc. Transient elevation of NAcc shell alphaCaMKII levels also enhanced locomotor responding to NAcc AMPA and increased phosphorylation levels of GluR1 (Ser831), a CaMKII site, both soon and long after infection. Similar increases in pGluR1 (Ser831) were observed both soon and long after exposure to amphetamine. These results indicate that the transient increase in alphaCaMKII observed in neurons of the NAcc shell after viral-mediated gene transfer and likely exposure to amphetamine leads to neuroadaptations in AMPA receptor signaling in this site that may contribute to the long-lasting maintenance of behavioral and incentive sensitization by psychostimulant drugs like amphetamine.