Ecological risk assessment (ERA) is the process used to evaluate the safety of manufactured chemicals to the environment. Here we review the pros and cons of ERA across levels of biological organization, including suborganismal (e.g., biomarkers), individual, population, community, ecosystem and landscapes levels. Our review revealed that level of biological organization is often related negatively with ease at assessing cause-effect relationships, ease of high-throughput screening of large numbers of chemicals (it is especially easier for suborganismal endpoints), and uncertainty of the ERA because low levels of biological organization tend to have a large distance between their measurement (what is quantified) and assessment endpoints (what is to be protected). In contrast, level of biological organization is often related positively with sensitivity to important negative and positive feedbacks and context dependencies within biological systems, and ease at capturing recovery from adverse contaminant effects. Some endpoints did not show obvious trends across levels of biological organization, such as the use of vertebrate animals in chemical testing and ease at screening large numbers of species, and other factors lacked sufficient data across levels of biological organization, such as repeatability, variability, cost per study and cost per species of effects assessment, the latter of which might be a more defensible way to compare costs of ERAs than cost per study. To compensate for weaknesses of ERA at any particular level of biological organization, we also review mathematical modeling approaches commonly used to extrapolate effects across levels of organization. Finally, we provide recommendations for next generation ERA, submitting that if there is an ideal level of biological organization to conduct ERA, it will only emerge if ERA is approached simultaneously from the bottom of biological organization up as well as from the top down, all while employing mathematical modeling approaches where possible to enhance ERA. Because top-down ERA is unconventional, we also offer some suggestions for how it might be implemented efficaciously. We hope this review helps researchers in the field of ERA fill key information gaps and helps risk assessors identify the best levels of biological organization to conduct ERAs with differing goals.

The manner in which parasite intensity and aggregation varies with host age can provide insights into parasite dynamics and help identify potential means of controlling infections in humans and wildlife. A significant challenge is to distinguish among competing mechanistic hypotheses for the relationship between age and parasite intensity or aggregation. Because different mechanisms can generate similar relationships, testing among competing hypotheses can be difficult, particularly in wildlife hosts, and often requires a combination of experimental and model fitting approaches. We used field data, experiments, and model fitting to distinguish among ten plausible drivers of a curvilinear age-intensity relationship and increasing aggregation with host age for echinostome trematode infections of green frogs. We found little support for most of these proposed drivers but did find that the parsimonious explanation for the observed age-intensity relationship was seasonal exposure to echinostomes. The parsimonious explanation for the aggregated distribution of parasites in this host population was heterogeneity in exposure. A predictive model incorporating seasonal exposure indicated that tadpoles hatching early or late in the breeding season should have lower trematode burdens at metamorphosis, particularly with simulated warmer climates. Application of this multi-pronged approach (field surveys, lab experiments, and modeling) to additional parasite-host systems could lead to discovery of general patterns in the drivers of parasite age-intensity and age-distribution relationships.

Background

Agrochemical pollution of surface waters is a growing global environmental challenge, especially in areas where agriculture is rapidly expanding and intensifying. Agrochemicals might affect schistosomiasis transmission through direct and indirect effects on Schistosoma parasites, their intermediate snail hosts, snail predators, and snail algal resources. We aimed to review and summarise the effects of these agrochemicals on schistosomiasis transmission dynamics.

Methods

We did a systematic review of agrochemical effects on the lifecycle of Schistosoma spp and fitted dose-response models to data regarding the association between components of the lifecycle and agrochemical concentrations. We incorporated these dose-response functions and environmentally relevant concentrations of agrochemicals into a mathematical model to estimate agrochemical effects on schistosomiasis transmission. Dose-response functions were used to estimate individual agrochemical effects on estimates of the agrochemically influenced basic reproduction number, R₀, for Schistosoma haematobium. We incorporated time series of environmentally relevant agrochemical concentrations into the model and simulated mass drug administration control efforts in the presence of agrochemicals.

Findings

We derived 120 dose-response functions describing the effects of agrochemicals on schistosome lifecycle components. The median estimate of the basic reproduction number under agrochemical-free conditions, was 1·65 (IQR 1·47-1·79). Agrochemical effects on estimates of R₀ for S haematobium ranged from a median three-times increase (R₀ 5·05, IQR 4·06-5·97) to transmission elimination (R₀ 0). Simulations of transmission dynamics subject to interacting annual mass drug administration and agrochemical pollution yielded a median estimate of 64·82 disability-adjusted life-years (DALYs) lost per 100 000 people per year (IQR 62·52-67·68) attributable to atrazine use. In areas where aquatic arthropod predators of intermediate host snails suppress transmission, the insecticides chlorpyrifos (6·82 DALYs lost per 100 000 people per year, IQR 4·13-8·69) and profenofos (103·06 DALYs lost per 100 000 people per year, IQR 89·63-104·90) might also increase the disability burden through their toxic effects on arthropods.

Interpretation

Expected environmental concentrations of agrochemicals alter schistosomiasis transmission through direct and indirect effects on intermediate host and parasite densities. As industrial agricultural practices expand in areas where schistosomiasis is endemic, strategies to prevent increases in transmission due to agrochemical pollution should be developed and pursued.

Funding

National Science Foundation, National Institutes of Health.

The potential benefits of physiology for conservation are well established and include greater specificity of management techniques, determination of cause-effect relationships, increased sensitivity of health and disturbance monitoring and greater capacity for predicting future change. While descriptions of the specific avenues in which conservation and physiology can be integrated are readily available and important to the continuing expansion of the discipline of 'conservation physiology', to date there has been no assessment of how the field has specifically contributed to conservation success. However, the goal of conservation physiology is to foster conservation solutions and it is therefore important to assess whether physiological approaches contribute to downstream conservation outcomes and management decisions. Here, we present eight areas of conservation concern, ranging from chemical contamination to invasive species to ecotourism, where physiological approaches have led to beneficial changes in human behaviour, management or policy. We also discuss the shared characteristics of these successes, identifying emerging themes in the discipline. Specifically, we conclude that conservation physiology: (i) goes beyond documenting change to provide solutions; (ii) offers a diversity of physiological metrics beyond glucocorticoids (stress hormones); (iii) includes approaches that are transferable among species, locations and times; (iv) simultaneously allows for human use and benefits to wildlife; and (v) is characterized by successes that can be difficult to find in the primary literature. Overall, we submit that the field of conservation physiology has a strong foundation of achievements characterized by a diversity of conservation issues, taxa, physiological traits, ecosystem types and spatial scales. We hope that these concrete successes will encourage the continued evolution and use of physiological tools within conservation-based research and management plans.

Infectious diseases are emerging globally at an unprecedented rate while global food demand is projected to increase sharply by 2100. Here, we synthesize the pathways by which projected agricultural expansion and intensification will influence human infectious diseases and how human infectious diseases might likewise affect food production and distribution. Feeding 11 billion people will require substantial increases in crop and animal production that will expand agricultural use of antibiotics, water, pesticides and fertilizer, and contact rates between humans and both wild and domestic animals, all with consequences for the emergence and spread of infectious agents. Indeed, our synthesis of the literature suggests that, since 1940, agricultural drivers were associated with >25% of all - and >50% of zoonotic - infectious diseases that emerged in humans, proportions that will likely increase as agriculture expands and intensifies. We identify agricultural and disease management and policy actions, and additional research, needed to address the public health challenge posed by feeding 11 billion people.

Infectious diseases are emerging globally at an unprecedented rate while global food demand is projected to increase sharply by 2100. Here, we synthesize the pathways by which projected agricultural expansion and intensification will influence human infectious diseases and how human infectious diseases might likewise affect food production and distribution. Feeding 11 billion people will require substantial increases in crop and animal production that will expand agricultural use of antibiotics, water, pesticides and fertilizer, and contact rates between humans and both wild and domestic animals, all with consequences for the emergence and spread of infectious agents. Indeed, our synthesis of the literature suggests that, since 1940, agricultural drivers were associated with >25% of all - and >50% of zoonotic - infectious diseases that emerged in humans, proportions that will likely increase as agriculture expands and intensifies. We identify agricultural and disease management and policy actions, and additional research, needed to address the public health challenge posed by feeding 11 billion people.

Mosquito-borne diseases cause a major burden of disease worldwide. The vital rates of these ectothermic vectors and parasites respond strongly and nonlinearly to temperature and therefore to climate change. Here, we review how trait-based approaches can synthesise and mechanistically predict the temperature dependence of transmission across vectors, pathogens, and environments. We present 11 pathogens transmitted by 15 different mosquito species - including globally important diseases like malaria, dengue, and Zika - synthesised from previously published studies. Transmission varied strongly and unimodally with temperature, peaking at 23-29ºC and declining to zero below 9-23ºC and above 32-38ºC. Different traits restricted transmission at low versus high temperatures, and temperature effects on transmission varied by both mosquito and parasite species. Temperate pathogens exhibit broader thermal ranges and cooler thermal minima and optima than tropical pathogens. Among tropical pathogens, malaria and Ross River virus had lower thermal optima (25-26ºC) while dengue and Zika viruses had the highest (29ºC) thermal optima. We expect warming to increase transmission below thermal optima but decrease transmission above optima. Key directions for future work include linking mechanistic models to field transmission, combining temperature effects with control measures, incorporating trait variation and temperature variation, and investigating climate adaptation and migration.

Temperature is widely known to influence the spatio-temporal dynamics of vector-borne disease transmission, particularly as temperatures vary across critical thermal thresholds. When temperature conditions exhibit such 'transcritical variation', abrupt spatial or temporal discontinuities may result, generating sharp geographical or seasonal boundaries in transmission. Here, we develop a spatio-temporal machine learning algorithm to examine the implications of transcritical variation for West Nile virus (WNV) transmission in the Los Angeles metropolitan area (LA). Analysing a large vector and WNV surveillance dataset spanning 2006-2016, we found that mean temperatures in the previous month strongly predicted the probability of WNV presence in pools of Culex quinquefasciatus mosquitoes, forming distinctive inhibitory (10.0-21.0°C) and favourable (22.7-30.2°C) mean temperature ranges that bound a narrow 1.7°C transitional zone (21-22.7°C). Temperatures during the most intense months of WNV transmission (August/September) were more strongly associated with infection probability in Cx. quinquefasciatus pools in coastal LA, where temperature variation more frequently traversed the narrow transitional temperature range compared to warmer inland locations. This contributed to a pronounced expansion in the geographical distribution of human cases near the coast during warmer-than-average periods. Our findings suggest that transcritical variation may influence the sensitivity of transmission to climate warming, and that especially vulnerable locations may occur where present climatic fluctuations traverse critical temperature thresholds.

Recent epidemics of Zika, dengue, and chikungunya have heightened the need to understand the seasonal and geographic range of transmission by Aedes aegypti and Ae. albopictus mosquitoes. We use mechanistic transmission models to derive predictions for how the probability and magnitude of transmission for Zika, chikungunya, and dengue change with mean temperature, and we show that these predictions are well matched by human case data. Across all three viruses, models and human case data both show that transmission occurs between 18-34°C with maximal transmission occurring in a range from 26-29°C. Controlling for population size and two socioeconomic factors, temperature-dependent transmission based on our mechanistic model is an important predictor of human transmission occurrence and incidence. Risk maps indicate that tropical and subtropical regions are suitable for extended seasonal or year-round transmission, but transmission in temperate areas is limited to at most three months per year even if vectors are present. Such brief transmission windows limit the likelihood of major epidemics following disease introduction in temperate zones.