A Time for Every Purpose: Using Time-Dependent Sensitivity Analysis to Help Understand and Manage Dynamic Ecological Systems.

AbstractSensitivity analysis is often used to help understand and manage ecological systems by assessing how a constant change in vital rates or other model parameters might affect the management outcome. This allows the manager to identify the most favorable course of action. However, realistic changes are often localized in time-for example, a short period of culling leads to a temporary increase in the mortality rate over the period.

Predicting and Controlling Spillover in Multispecies Disease Transmission Networks: Steady-State Analysis.

AbstractIn multispecies disease systems, pathogen spillover from a "reservoir community" can maintain disease in a "sink community" where it would otherwise die out. We develop and analyze models for spillover and disease spread in sink communities, focusing on questions of control: which species or transmission links are the most important to target to reduce the disease impact on a species of concern? Our analysis focuses on steady-state disease prevalence, assuming that the timescale of interest is long compared with that of disease introduction and establishment in the sink community. We identify three regimes as the sink community scales from 0 to 1.

A time for every purpose: using time-dependent sensitivity analysis to help understand and manage dynamic ecological systems.

Sensitivity analysis is often used to help understand and manage ecological systems, by assessing how a constant change in vital rates or other model parameters might affect the management outcome. This allows the manager to identify the most favorable course of action. However, realistic changes are often localized in time-for example, a short period of culling leads to a temporary increase in the mortality rate over the period.

Floral shape predicts bee-parasite transmission potential.

The spread of parasites is one of the primary drivers of population decline of both managed and wild bees. Several bee parasites are transmitted by the shared use of flowers, turning floral resources into potential disease hotspots. However, we know little about how floral morphology and floral species identity affect different steps of the transmission process.

Pathogen transport amplifies or dilutes disease transmission depending on the host dose-response relationship.

Pathogen transport by biotic or abiotic processes (e.g. mechanical vectors, wind, rain) can increase disease transmission by creating more opportunities for host exposure.

Eristalis flower flies can be mechanical vectors of the common trypanosome bee parasite, Crithidia bombi.

Flowers can be transmission platforms for parasites that impact bee health, yet bees share floral resources with other pollinator taxa, such as flies, that may be hosts or non-host vectors (i.e., mechanical vectors) of parasites.

Big bees spread disease: body size mediates transmission of a bumble bee pathogen.

Trait variation can have important consequences for the outcomes of species interactions. Even though some traits vary as much within species as across related species, models and empirical studies typically do not consider the role of intraspecific trait variation for processes such as disease transmission. For example, many pollinator species are in decline because of a variety of stressors including pathogens, but the role of intraspecific trait variation in mediating disease dynamics is rarely considered.

Dominant bee species and floral abundance drive parasite temporal dynamics in plant-pollinator communities.

Pollinator reductions can leave communities less diverse and potentially at increased risk of infectious diseases. Species-rich plant and bee communities have high species turnover, making the study of disease dynamics challenging. To address how temporal dynamics shape parasite prevalence in plant and bee communities, we screened >5,000 bees and flowers over an entire growing season for five common bee microparasites (Nosema ceranae, Nosema bombi, Crithidia bombi, Crithidia expoeki and neogregarines).

Individual Specialization and Multihost Epidemics: Disease Spread in Plant-Pollinator Networks.

Many parasites infect multiple species and persist through a combination of within- and between-species transmission. Multispecies transmission networks are typically constructed at the species level, linking two species if any individuals of those species interact. However, generalist species often consist of specialized individuals that prefer different subsets of available resources, so individual- and species-level contact networks can differ systematically.

Landscape simplification shapes pathogen prevalence in plant-pollinator networks.

Species interaction networks, which play an important role in determining pathogen transmission and spread in ecological communities, can shift in response to agricultural landscape simplification. However, we know surprisingly little about how landscape simplification-driven changes in network structure impact epidemiological patterns. Here, we combine mathematical modelling and data from eleven bipartite plant-pollinator networks observed along a landscape simplification gradient to elucidate how changes in network structure shape disease dynamics.

Codecaying Dark Matter.

We propose a new mechanism for thermal dark matter freeze-out, called codecaying dark matter. Multicomponent dark sectors with degenerate particles and out-of-equilibrium decays can codecay to obtain the observed relic density. The dark matter density is exponentially depleted through the decay of nearly degenerate particles rather than from Boltzmann suppression.