Exotic species richness and native species endemism increase the impact of exotic species on islands

Aim Exotic species pose one of the most significant threats to biodiversity, especially on islands. The impacts of exotic species vary in severity among islands, yet little is known about what makes some islands more susceptible than others. Here we determine which characteristics of an island influence how severely exotic species affect its native biota. Location We studied 65 islands and archipelagos from around the world, ranging from latitude 65° N to 54° S. Methods We compiled a global database of 10 island characteristics for 65 islands and determined the relative importance of each characteristic in predicting the impact of exotic species using multivariate modelling and hierarchical partitioning. We defined the impact of exotic species as the number of bird, amphibian and mammal (BAM) species listed by the International Union for Conservation of Nature (IUCN) as threatened by exotics, relative to the total number of BAM species on that island. Results We found that the impact of exotic species is more severe on islands with more exotic species and a greater proportion of native species that are endemic. Unexpectedly, the level of anthropogenic disturbance did not influence an island's susceptibility to the impacts of exotic species. Main conclusions By coupling our results with studies on the introduction and establishment of exotic species, we conclude that colonization pressure, or invasion opportunities, influences all stages of the invasion process. However, species endemism, the other important factor determining the impact of exotic species, is not known to contribute to introduction and establishment success on islands. This demonstrates that different factors correlate with the initial stages of the invasion process and the subsequent impacts of those invaders, highlighting the importance of studying the impacts of exotic species directly. Our study helps identify islands that are at risk of impact by exotics and where investment should focus on preventing further invasions.     

In vitro glucocorticoid sensitivity is associated with clinical glucocorticoid therapy outcome in rheumatoid arthritis

Introduction

Genetic and disease-related factors give rise to a wide spectrum of glucocorticoid (GC) sensitivity in rheumatoid arthritis (RA). In clinical practice, GC treatment is not adapted to these differences in GC sensitivity. In vitro assessment of GC sensitivity before the start of therapy could allow more individualized GC therapy. The aim of the study was to investigate the association between in vitro and in vivo GC sensitivity in RA.

Methods

Thirty-eight early and 37 established RA patients were prospectively studied. In vitro GC sensitivity was assessed with dexamethasone-induced effects on interleukin-2 (IL-2) and glucocorticoid-induced leucine zipper (GILZ) messenger RNA expression in peripheral blood mononuclear cells (PBMCs). A whole-cell dexamethasone-binding assay was used to measure number and affinity (1/K_D) of glucocorticoid receptors (GRs).In vivo GC sensitivity was determined by measuring the disease activity score (DAS) and health assessment questionnaire disability index (HAQ-DI) score before and after 2 weeks of standardized GC treatment.

Results

GR number was positively correlated with improvement in DAS. IL-2-EC₅₀ and GILZ-EC₅₀ values both had weak near-significant correlations with clinical improvement in DAS in intramuscularly treated patients only. HAQ responders had lower GILZ-EC₅₀ values and higher GR number and K_D.

Conclusions

Baseline cellular in vitro glucocorticoid sensitivity is modestly associated with in vivo improvement in DAS and HAQ-DI score after GC bridging therapy in RA. Further studies are needed to evaluate whether in vitro GC sensitivity may support the development of tailor-made GC therapy in RA.     

Zero tolerance ecology: improving ecological inference by modelling the source of zero observations

A common feature of ecological data sets is their tendency to contain many zero values. Statistical inference based on such data are likely to be inefficient or wrong unless careful thought is given to how these zeros arose and how best to model them. In this paper, we propose a framework for understanding how zero-inflated data sets originate and deciding how best to model them. We define and classify the different kinds of zeros that occur in ecological data and describe how they arise: either from 'true zero' or 'false zero' observations. After reviewing recent developments in modelling zero-inflated data sets, we use practical examples to demonstrate how failing to account for the source of zero inflation can reduce our ability to detect relationships in ecological data and at worst lead to incorrect inference. The adoption of methods that explicitly model the sources of zero observations will sharpen insights and improve the robustness of ecological analyses.     

The role of landscape-dependent disturbance and dispersal in metapopulation persistence

The fundamental processes that influence metapopulation dynamics (extinction and recolonization) will often depend on landscape structure. Disturbances that increase patch extinction rates will frequently be landscape dependent such that they are spatially aggregated and have an increased likelihood of occurring in some areas. Similarly, landscape structure can influence organism movement, producing asymmetric dispersal between patches. Using a stochastic, spatially explicit model, we examine how landscape-dependent correlations between dispersal and disturbance rates influence metapopulation dynamics. Habitat patches that are situated in areas where the likelihood of disturbance is low will experience lower extinction rates and will function as partial refuges. We discovered that the presence of partial refuges increases metapopulation viability and that the value of partial refuges was contingent on whether dispersal was also landscape dependent. Somewhat counterintuitively, metapopulation viability was reduced when individuals had a preponderance to disperse away from refuges and was highest when there was biased dispersal toward refuges. Our work demonstrates that landscape structure needs to be incorporated into metapopulation models when there is either empirical data or ecological rationale for extinction and/or dispersal rates being landscape dependent.     

A theory for optimal monitoring of marine reserves

Monitoring of marine reserves has traditionally focused on the task of rejecting the null hypothesis that marine reserves have no impact on the population and community structure of harvested populations. We consider the role of monitoring of marine reserves to gain information needed for management decisions. In particular we use a decision theoretic framework to answer the question: how long should we monitor the recovery of an over‐fished stock to determine the fraction of that stock to reserve? This exposes a natural tension between the cost (in terms of time and money) of additional monitoring, and the benefit of more accurately parameterizing a population model for the stock, that in turn leads to a better decision about the optimal size for the reserve with respect to harvesting. We found that the optimal monitoring time frame is rarely more than 5 years. A higher economic discount rate decreased the optimal monitoring time frame, making the expected benefit of more certainty about parameters in the system negligible compared with the expected gain from earlier exploitation.     

Type I interferon is required for T helper (Th) 2 induction by dendritic cells

Type 2 inflammation is a defining feature of infection with parasitic worms (helminths), as well as being responsible for widespread suffering in allergies. However, the precise mechanisms involved in T helper (Th) 2 polarization by dendritic cells (DCs) are currently unclear. We have identified a previously unrecognized role for type I IFN (IFN‐I) in enabling this process. An IFN‐I signature was evident in DCs responding to the helminth Schistosoma mansoni or the allergen house dust mite (HDM). Further, IFN‐I signaling was required for optimal DC phenotypic activation in response to helminth antigen (Ag), and efficient migration to, and localization with, T cells in the draining lymph node (dLN). Importantly, DCs generated from Ifnar1^?/? mice were incapable of initiating Th2 responses in vivo. These data demonstrate for the first time that the influence of IFN‐I is not limited to antiviral or bacterial settings but also has a central role to play in DC initiation of Th2 responses.     

Incorporating climate change into ecosystem service assessments and decisions: a review

Climate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer‐reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation.     

Protecting biodiversity when money matters: maximizing return on investment

Background

Conventional wisdom identifies biodiversity hotspots as priorities for conservation investment because they capture dense concentrations of species. However, density of species does not necessarily imply conservation ‘efficiency’. Here we explicitly consider conservation efficiency in terms of species protected per dollar invested.

Methodology/Principal Findings

We apply a dynamic return on investment approach to a global biome and compare it with three alternate priority setting approaches and a random allocation of funding. After twenty years of acquiring habitat, the return on investment approach protects between 32% and 69% more species compared to the other priority setting approaches. To correct for potential inefficiencies of protecting the same species multiple times we account for the complementarity of species, protecting up to three times more distinct vertebrate species than alternate approaches.

Conclusions/Significance

Incorporating costs in a return on investment framework expands priorities to include areas not traditionally highlighted as priorities based on conventional irreplaceability and vulnerability approaches.     

Optimal Dynamic Allocation of Conservation Funding Among Priority Regions

The optimal allocation of conservation resources between biodiverse conservation regions has generally been calculated using stochastic dynamic programming, or using myopic heuristics. These solutions are hard to interpret and may not be optimal. To overcome these two limitations, this paper approaches the optimal conservation resource allocation problem using optimal control theory. A solution using Pontryagin’s maximum principle provides novel insight into the general properties of efficient conservation resource allocation strategies, and allows more extensive testing of the performance of myopic heuristics. We confirmed that a proposed heuristic (minimize short-term loss) yields near-optimal results in complex allocation situations, and found that a qualitative allocation feature observed in previous analyses (bang-bang allocation) is a general property of the optimal allocation strategy.