Predicting the fundamental thermal niche of ectotherms.

Climate warming is predicted to increase mean temperatures and thermal extremes on a global scale. Because their body temperature depends on the environmental temperature, ectotherms bear the full brunt of climate warming. Predicting the impact of climate warming on ectotherm diversity and distributions requires a framework that can translate temperature effects on ectotherm life-history traits into population- and community-level outcomes. Here we present a mechanistic theoretical framework that can predict the fundamental thermal niche and climate envelope of ectotherm species based on how temperature affects the underlying life-history traits. The advantage of this framework is twofold. First, it can translate temperature effects on the phenotypic traits of individual organisms to population-level patterns observed in nature. Second, it can predict thermal niches and climate envelopes based solely on trait response data and, hence, completely independently of any population-level information. We find that the temperature at which the intrinsic growth rate is maximized exceeds the temperature at which abundance is maximized under density-dependent growth. As a result, the temperature at which a species will increase the fastest when rare is lower than the temperature at which it will recover from a perturbation the fastest when abundant. We test model predictions using data from a naturalized-invasive interaction to identify the temperatures at which the invasive can most easily invade the naturalized's habitat and the naturalized is most likely to resist the invasive. The framework is sufficiently mechanistic to yield reliable predictions for individual species and sufficiently broad to apply across a range of ectothermic taxa. This ability to predict the thermal niche before a species encounters a new thermal environment is essential to mitigating some of the major effects of climate change on ectotherm populations around the globe.

Social Learning of Innovations in Dynamic Predator-Prey Systems.

AbstractWe investigate the social transmission of innovations between predators. We focus on two classic predator-prey models. We assume that innovations increase predator attack rates or conversion efficiencies or that innovations reduce predator mortality or handling time. We find that a common outcome is the destabilization of the system. Destabilizing effects include increasing oscillations or limit cycles. Particularly, in more realistic systems (where prey are self-limiting and predators have a type II functional response), destabilization occurs because of overexploitation of the prey. Whenever instability increases the risk of extinction, innovations that benefit individual predators may not have positive long-term effects on predator populations. Additionally, instability could maintain behavioral variability among predators. Interestingly, when predator populations are low despite coexisting with prey populations near their carrying capacity, innovations that could help predators better exploit their prey are least likely to spread. Precisely how unlikely this is depends on whether naive individuals need to observe an informed individual interact with prey to learn the innovation. Our findings help illuminate how innovations could affect biological invasions, urban colonization, and the maintenance of behavioral polymorphisms.

Litter, Plant Competition, and Ecosystem Dynamics: A Theoretical Perspective.

AbstractCommunity structure depends jointly on species' responses to, and effects on, environmental factors. Many such factors, including detritus, are studied in ecosystem ecology. Detritus in terrestrial ecosystems is dominated by plant litter (nonliving organic material), which, in addition to its role in material cycling, can act as a niche factor modulating interactions among plants. Litter thus links traditional community and ecosystem processes, which are often studied separately. We explore this connection using population dynamics models of two plant species and a litter pool. We first find conditions determining the outcome of interactions between these species, highlighting the role that litter plays and the role of broader ecosystem parameters, such as decomposition rate. Species trade-offs in tolerance to direct competition and litter-based interference competition allow for coexistence, provided the litter-tolerant species produces more litter at the population level; otherwise, priority effects may result. When species coexist, litter-mediated interactions between plants disrupt the traditional relationship between biomass accumulation and decomposition. Increasing decomposition rate may have no effect on standing litter density and, in some cases, may even increase litter load. These results illustrate how ecosystem variables can influence community outcomes that then feed back to influence the ecosystem.

The interplay of movement and spatiotemporal variation in transmission degrades pandemic control.

Successful public health regimes for COVID-19 push below unity long-term regional Rt -the average number of secondary cases caused by an infectious individual. We use a susceptible-infectious-recovered (SIR) model for two coupled populations to make the conceptual point that asynchronous, variable local control, together with movement between populations, elevates long-term regional Rt , and cumulative cases, and may even prevent disease eradication that is otherwise possible. For effective pandemic mitigation strategies, it is critical that models encompass both spatiotemporal heterogeneity in transmission and movement.

Latitudinal directionality in ectotherm invasion success.

A striking pattern, seen in both fossil and extant taxa, is that tropical ectotherms are better at invading temperate habitats than vice versa. This is puzzling because tropical ectotherms, being thermal specialists, face a harsher abiotic environment and competition from temperate residents that are thermal generalists. We develop a mathematical framework to address this puzzle. We find that (i) tropical ectotherms can invade temperate habitats if they have higher consumption rates and lower mortality during warmer summers, (ii) stronger seasonal fluctuations at higher latitudes create more temporal niches, allowing coexistence of tropical invaders and temperate residents, and (iii) temperate ectotherms' failure to invade tropical habitats is due to greater mortality rather than lower competitive ability. Our framework yields predictions about population-level outcomes of invasion success based solely on species' trait responses to temperature. It provides a potential ecological explanation for why the tropics constitute both a cradle and a museum of biodiversity.

Filtering nucleotide sites by phylogenetic signal to noise ratio increases confidence in the Neoaves phylogeny generated from ultraconserved elements.

Despite genome scale analyses, high-level relationships among Neoaves birds remain contentious. The placements of the Neoaves superorders are notoriously difficult to resolve because they involve deep splits followed by short internodes. Using our approach, we investigate whether filtering UCE loci on their phylogenetic signal to noise ratio helps to resolve key nodes in the Neoaves tree of life. We find that our analysis of data sets filtered for high signal to noise ratio results in topologies that are inconsistent with unfiltered results but that are congruent with whole-genome analyses. These relationships include the Columbea + Passerea sister relationship and the Phaethontimorphae + Aequornithia sister relationship. We also find increased statistical support for more recent nodes (i.e. the Pelecanidae + Ardeidae sister relationship, the Eucavitaves clade, and the Otidiformes + Musophagiformes sister relationship). We also find instances where support is reduced for well-established clades, possibly due to the removal of sites with moderate signal-to-noise ratio. Our results suggest that filtering on the basis of signal to noise ratio is a useful tool for resolving problematic splits in phylogenomic data sets.