Predictable shorebird departure patterns from a staging site can inform collision risks and mitigation of wind energy developments

High-quality staging sites are critical for long-distance migratory shorebirds to rest and refuel but are under threat from human development, including expansion of wind energy projects. However, predicting migration timing and movements in relation to weather conditions at staging sites can increase our understanding and mitigate effects of wind turbine collisions. Here we assessed northward migration timing and orientation in relation to environmental conditions at an inland staging area in Saskatchewan, Canada, with active and proposed wind energy developments. The area is known to host ~25% of North America's Sanderling Calidris alba population and 16 other Arctic-breeding migrant shorebird species. We quantified arrival and departure time of day in relation to weather using data from 140 of 237 Sanderlings radiotagged locally and at a southern staging site in the Gulf of Mexico with the Motus Wildlife Tracking System (April–June, 2015–2017). Although Sanderling arrival times were not related to time of day or weather, departures were more likely at sunset in winds blowing towards the northwest at intermediate speeds (<22 km/h). Departure flights were also primarily oriented north-northwest in the direction of a proposed wind energy development site at a mean ground speed of 21.4 m/s. Based on published climb rates and flight speed data, we estimated that shorebirds needed between 2 and 14 km setback distance to clear maximum turbine heights of 165 m. Given that departure events were predictable in time and space, adaptive mitigation may be useful for planning wind energy developments while reducing risk for staging Arctic-breeding shorebirds.     

Geographic and ecologic heterogeneity in elimination thresholds for the major vector-borne helminthic disease,lymphatic filariasis

Background

Large-scale intervention programmes to control or eliminate several infectious diseases are currently underway worldwide. However, a major unresolved question remains: what are reasonable stopping points for these programmes? Recent theoretical work has highlighted how the ecological complexity and heterogeneity inherent in the transmission dynamics of macroparasites can result in elimination thresholds that vary between local communities. Here, we examine the empirical evidence for this hypothesis and its implications for the global elimination of the major macroparasitic disease, lymphatic filariasis, by applying a novel Bayesian computer simulation procedure to fit a dynamic model of the transmission of this parasitic disease to field data from nine villages with different ecological and geographical characteristics. Baseline lymphatic filariasis microfilarial age-prevalence data from three geographically distinct endemic regions, across which the major vector populations implicated in parasite transmission also differed, were used to fit and calibrate the relevant vector-specific filariasis transmission models. Ensembles of parasite elimination thresholds, generated using the Bayesian fitting procedure, were then examined in order to evaluate site-specific heterogeneity in the values of these thresholds and investigate the ecological factors that may underlie such variability

Results

We show that parameters of density-dependent functions relating to immunity, parasite establishment, as well as parasite aggregation, varied significantly between the nine different settings, contributing to locally varying filarial elimination thresholds. Parasite elimination thresholds predicted for the settings in which the mosquito vector is anopheline were, however, found to be higher than those in which the mosquito is culicine, substantiating our previous theoretical findings. The results also indicate that the probability that the parasite will be eliminated following six rounds of Mass Drug Administration with diethylcarbamazine and albendazole decreases markedly but non-linearly as the annual biting rate and parasite reproduction number increases.

Conclusions

This paper shows that specific ecological conditions in a community can lead to significant local differences in population dynamics and, consequently, elimination threshold estimates for lymphatic filariasis. These findings, and the difficulty of measuring the key local parameters (infection aggregation and acquired immunity) governing differences in transmission thresholds between communities, mean that it is necessary for us to rethink the utility of the current anticipatory approaches for achieving the elimination of filariasis both locally and globally.

     

Spatiotemporal Clustering of Mycobacterium tuberculosis Complex Genotypes in Florida: Genetic Diversity Segregated by Country of Birth

BackgroundTuberculosis (TB) is caused by members of the Mycobacterium tuberculosis complex (MTBC). Although the MTBC is highly clonal, between-strain genetic diversity has been observed. In low TB incidence settings, immigration may facilitate the importation of MTBC strains with a potential to complicate TB control efforts.MethodsWe investigated the genetic diversity and spatiotemporal clustering of 2,510 MTBC strains isolated in Florida, United States, between 2009 and 2013 and genotyped using spoligotyping and 24-locus MIRU-VNTR. We mapped the genetic diversity to the centroid of patient residential zip codes using a geographic information system (GIS). We assessed transmission dynamics and the influence of immigration on genotype clustering using space-time permutation models adjusted for foreign-born population density and county-level HIV risk and multinomial models stratified by country of birth and timing of immigration in SaTScan.Conclusions/SignificanceAlmost five percent of TB cases reported in Florida during 2009–2013 were potentially due to recent transmission. Improvements to TB screening practices among the prison population and recent immigrants are likely to impact TB control. Due to the monomorphic nature of available markers, whole genome sequencing is needed to conclusively delineate recent transmission events between U.S. and foreign-born persons.     

Dengue in Java,Indonesia: Relevance of Mosquito Indices as Risk Predictors

BackgroundNo vaccine is currently available for dengue virus (DENV), therefore control programmes usually focus on managing mosquito vector populations. Entomological surveys provide the most common means of characterising vector populations and predicting the risk of local dengue virus transmission. Despite Indonesia being a country strongly affected by DENV, only limited information is available on the local factors affecting DENV transmission and the suitability of available survey methods for assessing risk.Conclusions/significanceOur data suggested that the utility of traditional larvae indices, which continue to be used in many dengue endemic countries, should be re-evaluated locally. The results highlight the need for validation of risk indicators and control strategies across DENV affected areas here and perhaps elsewhere in SE Asia.     

Seroepidemiology of Crimean-Congo Haemorrhagic Fever among cattle in Cameroon: Implications from a One Health perspective

BackgroundCrimean-Congo Haemorrhagic Fever (CCHF) is a tick-borne viral zoonotic disease distributed across several continents and recognized as an ongoing health threat. In humans, the infection can progress to a severe disease with high fatality, raising public health concerns due to the limited prophylactic and therapeutic options available. Animal species, clinically unaffected by the virus, serve as viral reservoirs and amplifier hosts, and can be a valuable tool for surveillance. Little is known about the occurrence and prevalence of Crimean-Congo Haemorrhagic Fever Virus (CCHFV) in Cameroon. Knowledge on CCHFV exposure and the factors associated with its presence in sentinel species are a valuable resource to better understand transmission dynamics and assess local risks for zoonotic disease emergence.Methods and findingsWe conducted a CCHFV serological survey and risk factor analysis for animal level seropositivity in pastoral and dairy cattle in the North West Region (NWR) and the Vina Division (VD) of the Adamawa Region in Cameroon. Seroprevalence estimates were adjusted for sampling design-effects and test performance. In addition, explanatory multivariable logistic regression mixed-effects models were fit to estimate the effect of animal characteristics, husbandry practices, risk contacts and ecological features on the serological status of pastoral cattle. The overall seroprevalence was 56.0% (95% CI 53.5–58.6) and 6.7% (95% CI 2.6–16.1) among pastoral and dairy cattle, respectively. Animals going on transhumance had twice the odds of being seropositive (OR 2.0, 95% CI 1.1–3.8), indicating that animal movements could be implicated in disease expansion. From an ecological perspective, absolute humidity (OR 0.6, 95% CI 0.4–0.9) and shrub density (OR 2.1, 95% CI 1.4–3.2) were associated with seropositivity, which suggests an underlying viral dynamic connecting vertebrate host and ticks in a complex transmission network.ConclusionsThis study demonstrated high seroprevalence levels of CCHFV antibodies in cattle in Cameroon indicating a potential risk to human populations. However, current understanding of the underlying dynamics of CCHFV locally and the real risk for human populations is incomplete. Further studies designed using a One Health approach are required to improve local knowledge of the disease, host interactions and environmental risk factors. This information is crucial to better project the risks for human populations located in CCHFV-suitable ecological niches.     

Spatiotemporal distribution of cutaneous leishmaniasis in Sri Lanka and future case burden estimates

BackgroundLeishmaniasis is a neglected tropical vector-borne disease, which is on the rise in Sri Lanka. Spatiotemporal and risk factor analyses are useful for understanding transmission dynamics, spatial clustering and predicting future disease distribution and trends to facilitate effective infection control.MethodsThe nationwide clinically confirmed cutaneous leishmaniasis and climatic data were collected from 2001 to 2019. Hierarchical clustering and spatiotemporal cross-correlation analysis were used to measure the region-wide and local (between neighboring districts) synchrony of transmission. A mixed spatiotemporal regression-autoregression model was built to study the effects of climatic, neighboring-district dispersal, and infection carryover variables on leishmaniasis dynamics and spatial distribution. Same model without climatic variables was used to predict the future distribution and trends of leishmaniasis cases in Sri Lanka.ResultsA total of 19,361 clinically confirmed leishmaniasis cases have been reported in Sri Lanka from 2001–2019. There were three phases identified: low-transmission phase (2001–2010), parasite population buildup phase (2011–2017), and outbreak phase (2018–2019). Spatially, the districts were divided into three groups based on similarity in temporal dynamics. The global mean correlation among district incidence dynamics was 0.30 (95% CI 0.25–0.35), and the localized mean correlation between neighboring districts was 0.58 (95% CI 0.42–0.73). Risk analysis for the seven districts with the highest incidence rates indicated that precipitation, neighboring-district effect, and infection carryover effect exhibited significant correlation with district-level incidence dynamics. Model-predicted incidence dynamics and case distribution matched well with observed results, except for the outbreak in 2018. The model-predicted 2020 case number is about 5,400 cases, with intensified transmission and expansion of high-transmission area. The predicted case number will be 9115 in 2022 and 19212 in 2025.ConclusionsThe drastic upsurge in leishmaniasis cases in Sri Lanka in the last few year was unprecedented and it was strongly linked to precipitation, high burden of localized infections and inter-district dispersal. Targeted interventions are urgently needed to arrest an uncontrollable disease spread.     

Impact of Birth Seasonality on Dynamics of Acute Immunizing Infections in Sub-Saharan Africa

We analyze the impact of birth seasonality (seasonal oscillations in the birth rate) on the dynamics of acute, immunizing childhood infectious diseases. Previous research has explored the effect of human birth seasonality on infectious disease dynamics using parameters appropriate for the developed world. We build on this work by including in our analysis an extended range of baseline birth rates and amplitudes, which correspond to developing world settings. Additionally, our analysis accounts for seasonal forcing both in births and contact rates. We focus in particular on the dynamics of measles. In the absence of seasonal transmission rates or stochastic forcing, for typical measles epidemiological parameters, birth seasonality induces either annual or biennial epidemics. Changes in the magnitude of the birth fluctuations (birth amplitude) can induce significant changes in the size of the epidemic peaks, but have little impact on timing of disease epidemics within the year. In contrast, changes to the birth seasonality phase (location of the peak in birth amplitude within the year) significantly influence the timing of the epidemics. In the presence of seasonality in contact rates, at relatively low birth rates (20 per 1000), birth amplitude has little impact on the dynamics but does have an impact on the magnitude and timing of the epidemics. However, as the mean birth rate increases, both birth amplitude and phase play an important role in driving the dynamics of the epidemic. There are stronger effects at higher birth rates.     

Modelling Parasite Transmission in a Grazing System: The Importance of Host Behaviour and Immunity

Parasitic helminths present one of the most pervasive challenges to grazing herbivores. Many macro-parasite transmission models focus on host physiological defence strategies, omitting more complex interactions between hosts and their environments. This work represents the first model that integrates both the behavioural and physiological elements of gastro-intestinal nematode transmission dynamics in a managed grazing system. A spatially explicit, individual-based, stochastic model is developed, that incorporates both the hosts’ immunological responses to parasitism, and key grazing behaviours including faecal avoidance. The results demonstrate that grazing behaviour affects both the timing and intensity of parasite outbreaks, through generating spatial heterogeneity in parasite risk and nutritional resources, and changing the timing of exposure to the parasites’ free-living stages. The influence of grazing behaviour varies with the host-parasite combination, dependent on the development times of different parasite species and variations in host immune response. Our outputs include the counterintuitive finding that under certain conditions perceived parasite avoidance behaviours (faecal avoidance) can increase parasite risk, for certain host-parasite combinations. Through incorporating the two-way interaction between infection dynamics and grazing behaviour, the potential benefits of parasite-induced anorexia are also demonstrated. Hosts with phenotypic plasticity in grazing behaviour, that make grazing decisions dependent on current parasite burden, can reduce infection with minimal loss of intake over the grazing season. This paper explores how both host behaviours and immunity influence macro-parasite transmission in a spatially and temporally heterogeneous environment. The magnitude and timing of parasite outbreaks is influenced by host immunity and behaviour, and the interactions between them; the incorporation of both regulatory processes is required to fully understand transmission dynamics. Understanding of both physiological and behavioural defence strategies will aid the development of novel approaches for control.     

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010–2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.     

Landscape-Level Phenology of a Threatened Butterfly: A GIS-Based Modeling Approach

Phenology of organismal development varies between growing seasons according to the weather and also varies within growing seasons across topoclimatic gradients. Combining these factors is necessary to predict landscape-level patterns of phenology and their consequences for population dynamics. We developed a model on a Geographic Information System (GIS) that predicts phenology of adult emergence of the threatened Bay checkerspot butterfly across complex terrain under variable weather. Physiological time was modeled by accumulated slope-specific direct insolation. Insolation sums through growing seasons were calculated for each cell of a digital terrain model (skipping over cloudy days) until a threshold for adult emergence was reached. Emergence times of adult butterflies for a given year were then mapped out across a 100-ha area. To generate predicted emergence curves for the population in a given year, these maps ofemergence times were then modified by incorporating microdistributions of postdiapause larvae. Different larval microdistributions changed both the magnitude and shape of emergence curves under the same yearly weather and could change mean population-wide emergence dates by 11 days. Reproductive success in this butterfly is strongly dependent on the timing of adult emergence, and these models provide insights into the effects of weather, topography, and population history on population dynamics. Because adult emergence phenology is often a key component of reproductive success for insects, understanding the components of phenological variation in space and time in complex terrain may provide insights into population dynamics for management of pests and conservation of rare species. Received 2 December 1997; accepted 24 March 1998.     

A unified evolutionary framework for understanding parasite infection and host migratory behaviour

Animal migration impacts organismal health and parasite transmission: migrants are simultaneously exposed to parasites and able to reduce infection for both individuals and populations. However, these dynamics are difficult to study; empirical studies reveal disparate results while existing theory makes assumptions that simplify natural complexity. Here, we systematically review empirical studies of migration and infection across taxa, highlighting key gaps in our understanding. Next, we develop a unified evolutionary framework incorporating different selective pressures of parasite–migration interactions while accounting for ecological complexity that goes beyond previous theory. Our framework generates diverse migration–infection patterns paralleling those seen in empirical systems, including partial and differential migration. Finally, we generate predictions about which mechanisms dominate which empirical systems to guide future studies. Our framework provides an overarching understanding of selective pressures shaping migration patterns in the context of animal health and disease, which is critical for predicting how environmental change may threaten migration.     

Malaria, danger, and risk perceptions among the Yao in rural Malawi

Findings from a study designed to discover how local understanding of malaria among Yao in Malawi relate to pregnancy risk definitions reveal that malaria in pregnancy is not perceived as a major risk. Using extended ethnographic field research and multiple methods, we argue a shift from narrow single-disease approaches to malaria during pregnancy is required and document women's concerns about exposure to multiple vulnerabilities during pregnancy, including witchcraft, extramarital affairs, and multiple dangerous illnesses. Four dimensions are implicated in Yao perceptions of risk: perceived adverse consequences in pregnancy; ease of treatment and cure; transmission and agency to control; and type of risk (social-medical). We discuss implications and consider malaria program features needed to address the complexity of perceived vulnerabilities and living conditions in resource-poor settings.     

Sequential Modelling of the Effects of Mass Drug Treatments on Anopheline-Mediated Lymphatic Filariasis Infection in Papua New Guinea

Background

Lymphatic filariasis (LF) has been targeted by the WHO for global eradication leading to the implementation of large scale intervention programs based on annual mass drug administrations (MDA) worldwide. Recent work has indicated that locality-specific bio-ecological complexities affecting parasite transmission may complicate the prediction of LF extinction endpoints, casting uncertainty on the achievement of this initiative. One source of difficulty is the limited quantity and quality of data used to parameterize models of parasite transmission, implying the important need to update initially-derived parameter values. Sequential analysis of longitudinal data following annual MDAs will also be important to gaining new understanding of the persistence dynamics of LF. Here, we apply a Bayesian statistical-dynamical modelling framework that enables assimilation of information in human infection data recorded from communities in Papua New Guinea that underwent annual MDAs, into our previously developed model of parasite transmission, in order to examine these questions in LF ecology and control.

Results

Biological parameters underlying transmission obtained by fitting the model to longitudinal data remained stable throughout the study period. This enabled us to reliably reconstruct the observed baseline data in each community. Endpoint estimates also showed little variation. However, the updating procedure showed a shift towards higher and less variable values for worm kill but not for any other drug-related parameters. An intriguing finding is that the stability in key biological parameters could be disrupted by a significant reduction in the vector biting rate prevailing in a locality.

Conclusions

Temporal invariance of biological parameters in the face of intervention perturbations indicates a robust adaptation of LF transmission to local ecological conditions. The results imply that understanding the mechanisms that underlie locally adapted transmission dynamics will be integral to identifying points of system fragility, and thus countermeasures to reliably facilitate LF extinction both locally and globally.     

Sources and sinks: revisiting the criteria for identifying reservoirs for American cutaneous leishmaniasis

Molecular-based approaches might be misleading for assessing the 'potential importance' of possible reservoirs for parasites unless used in conjunction with population dynamics and ecological studies that provide an understanding of the linkages between the enzootic transmission cycle (in wild animals) and that in domestic animals. Better understanding of ecological constraints on Leishmania transmission is needed to assess fully the passage of the parasite between its sandfly vector and different mammalian host species. We use a straightforward mathematical framework to illustrate that misuse of association patterns, as guidance for implementation of control measures, can in fact increase the endemism of leishmaniasis.     

Investigating general and specific links from adolescents’ perceptions of ecological assets to their civic actions

Civic engagement is an important marker of thriving among adolescents, and more research is needed that clarifies the ecological assets (positive supports across settings) that foster youth civic engagement. Simultaneously modeling associations between multiple ecological assets and civic behaviors can provide a nuanced view of the way adolescents’ ecological assets relate to distinct forms of civic engagement. To advance positive youth development theory, we used a bifactor modeling approach to examine general and specific ecological asset factors in relation to volunteering, conventional political, online political, and informal helping behaviors. In a large ethnically diverse sample of adolescents, the general ecological asset factor was positively associated with informal helping only. Classroom civic learning opportunities were positively associated with volunteering, conventional, and online political behaviors. Family political discussions were positively associated with conventional and online political behaviors. Our study suggests that civic engagement should be understood multidimensionally and that broad and specific ways of conceptualizing ecological assets have merit for understanding different types of youth civic engagement.     

Understanding and predicting effects of modified interactions through a qualitative analysis of community structure

Models of ecological communities are traditionally based on relationships between pairs of species, where the strengths of per capita interactions are fixed and independent of population abundance. A growing body of literature, however; describes interactions whose strength is modified by the density of either a third species or by one of the species involved in a pairwise interaction. These modified interactions have been treated as indirect effects, and the terminology addressing them is diverse and overlapping. In this paper we develop a general analytical framework based on a qualitative analysis of community structure to account for the consequence of modified interactions in complex ecological communities. Modified interactions are found to create both direct and indirect effects between species. The sign of a direct effect can change in some instances depending on the magnitude of a key variable or parameter, which leads to a threshold change in system structure and dynamics. By considering alternative structures of a community, we extend our ability to model perturbations that move the system far from a previous equilibrium. Using specific examples, we reinterpret existing results, develop hypotheses to guide experiments or management interventions, and explore the role of modified interactions and positive feedback in creating and maintaining alternative stable states. Through a qualitative analysis of community structure, system feedback is demonstrated as being key in understanding and predicting the dynamics of complex ecological communities.     

Relationships between ecological interaction modifications and diffuse coevolution: similarities, differences, and causal links

A major empirical approach in community ecology is to describe the dynamics of a community by examining small subsets of species. Unfortunately, interaction modifications, which cause pair-wise interaction coefficients to depend on the presence or absence of additional species, can make it difficult to predict the overall dynamics of species within a community from experiments with pairs of species. In a similar fashion, one of the major approaches in evolutionary ecology has been to describe the likely evolutionary dynamics of a single species by focusing on the selection imposed by a limited number of other species within the community. However, recent work on diffuse coevolution indicates that selection pressures due to one species can change in the presence of other species. The magnitude of the difficulty that interaction modifications and diffuse coevolution present for predicting ecological and evolutionary dynamics is an unresolved question. Here we outline the similarities and differences between the two topics, discuss experimental and statistical approaches to studying them, and make predictions about when ecological interaction modifications are likely to cause diffuse coevolution. Since the currencies for interaction modifications are usually fitness components such as growth, fecundity, or survival, is it likely that these will translate into corresponding differences in the relative fitness of individuals or genotypes, and thus in general these two phenomena will occur together. We argue that community ecologists and evolutionary ecologists will both benefit from experiments that test for the effects of interaction modifications, and that studies of the mechanisms driving interaction modifications and diffuse coevolution (e.g., changes in behavior, nonlinear effects on shared resources, genetic covariances) will aid our progress in understanding the ecological and evolutionary dynamics of communities.     

Synthesising 30 Years of Mathematical Modelling of Echinococcus Transmission

Background

Echinococcosis is a complex zoonosis that has domestic and sylvatic lifecycles, and a range of different intermediate and definitive host species. The complexities of its transmission and the sparse evidence on the effectiveness of control strategies in diverse settings provide significant challenges for the design of effective public health policy against this disease. Mathematical modelling is a useful tool for simulating control packages under locally specific transmission conditions to inform optimal timing and frequency of phased interventions for cost-effective control of echinococcosis. The aims of this review of 30 years of Echinococcus modelling were to discern the epidemiological mechanisms underpinning models of Echinococcus granulosus and E. multilocularis transmission and to establish the need to include a human transmission component in such models.

Methodology/Principal Findings

A search was conducted of all relevant articles published up until July 2012, identified from the PubMED, Web of Knowledge and Medline databases and review of bibliographies of selected papers. Papers eligible for inclusion were those describing the design of a new model, or modification of an existing mathematical model of E. granulosus or E. multilocularis transmission. A total of 13 eligible papers were identified, five of which described mathematical models of E. granulosus and eight that described E. multilocularis transmission. These models varied primarily on the basis of six key mechanisms that all have the capacity to modulate model dynamics, qualitatively affecting projections. These are: 1) the inclusion of a ‘latent’ class and/or time delay from host exposure to infectiousness; 2) an age structure for animal hosts; 3) the presence of density-dependent constraints; 4) accounting for seasonality; 5) stochastic parameters; and 6) inclusion of spatial and risk structures.

Conclusions/Significance

This review discusses the conditions under which these mechanisms may be important for inclusion in models of Echinococcus transmission and proposes recommendations for the design of dynamic human models of transmission. Accounting for the dynamic behaviour of the Echinococcus parasites in humans will be key to predicting changes in the disease burden over time and to simulate control strategies that optimise public health impact.     

Sympatric inhibition and niche differentiation suggest alternative coevolutionary trajectories among Streptomycetes

Soil bacteria produce a diverse array of antibiotics, yet our understanding of the specific roles of antibiotics in the ecological and evolutionary dynamics of microbial interactions in natural habitats remains limited. Here, we show a significant role for antibiotics in mediating antagonistic interactions and nutrient competition among locally coexisting Streptomycete populations from soil. We found that antibiotic inhibition is significantly more intense among sympatric than allopatric Streptomycete populations, indicating local selection for inhibitory phenotypes. For sympatric but not allopatric populations, antibiotic inhibition is significantly positively correlated with niche overlap, indicating that inhibition is targeted toward bacteria that pose the greatest competitive threat. Our results support the hypothesis that antibiotics serve as weapons in mediating local microbial interactions in soil and suggest that coevolutionary niche displacement may reduce the likelihood of an antibiotic arms race. Further insight into the diverse roles of antibiotics in microbial ecology and evolution has significant implications for understanding the persistence of antibiotic inhibitory and resistance phenotypes in environmental microbes, optimizing antibiotic drug discovery and developing strategies for managing microbial coevolutionary dynamics to enhance inhibitory phenotypes.     

Hispanic Farmers and Farmworkers: Social Networks, Institutional Exclusion, and Climate Vulnerability in Southeastern Arizona

ABSTRACT   In the U.S. Southwest, prolonged drought may force those most dependent on water to abandon their livelihoods. By focusing on Hispanic farmers and farmworkers, in this article I examine how ethnicity and other factors compound risk and create highly vulnerable groups. I use the concept of "social capital" to understand how the critically vulnerable access resources embedded in informal social networks of mutual aid to reduce their vulnerability. By contrasting their situation to that of Anglo farmers, I explore how social networks emerge as a result of diverse socioeconomic and ethnic contexts. Under a more permanent scenario of increased aridity, a better understanding of the risk management mechanisms deployed by vulnerable groups sheds light on how collective approaches build resilience and on the role of policy in promoting or inhibiting these approaches. I seek to contribute to discussions about the importance of sociocultural dynamics and policy decisions to improving society's adaptive capacity.