Desert pastoralists’ negative and positive effects on rare wildlife in the Gobi

In arid regions of the developing world, pastoralists and livestock commonly inhabit protected areas, resulting in human–wildlife conflict. Conflict is inextricably linked to the ecological processes shaping relationships between pastoralists and native herbivores and carnivores. To elucidate relationships underpinning human–wildlife conflict, we synthesized 15 years of ecological and ethnographic data from Ikh Nart Nature Reserve in Mongolia's Gobi steppe. The density of argali (Ovis ammon), the world's largest wild sheep, at Ikh Nart was among the highest in Mongolia, yet livestock were >90% of ungulate biomass and dogs >90% of large‐carnivore biomass. For argali, pastoral activities decreased food availability, increased mortality from dog predation, and potentially increased disease risk. Isotope analyses indicated that livestock accounted for >50% of the diet of the majority of gray wolves (Canis lupus) and up to 90% of diet in 25% of sampled wolves (n = 8). Livestock composed at least 96% of ungulate prey in the single wolf pack for which we collected species‐specific prey data. Interviews with pastoralists indicated that wolves annually killed 1–4% of Ikh Nart's livestock, and pastoralists killed wolves in retribution. Pastoralists reduced wolf survival by killing them, but their livestock were an abundant food source for wolves. Consequently, wolf density appeared to be largely decoupled from argali density, and pastoralists had indirect effects on argali that could be negative if pastoralists increased wolf density (apparent competition) or positive if pastoralists decreased wolf predation (apparent facilitation). Ikh Nart's argali population was stable despite these threats, but livestock are increasingly dominant numerically and functionally relative to argali. To support both native wildlife and pastoral livelihoods, we suggest training dogs to not kill argali, community insurance against livestock losses to wolves, reintroducing key native prey species to hotspots of human–wolf conflict, and developing incentives for pastoralists to reduce livestock density.     

Threats to intact tropical peatlands and opportunities for their conservation

Large, intact areas of tropical peatland are highly threatened at a global scale by the expansion of commercial agriculture and other forms of economic development. Conserving peatlands on a landscape scale, with their hydrology intact, is of international conservation importance to preserve their distinctive biodiversity and ecosystem services and maintain their resilience to future environmental change. We explored threats to and opportunities for conserving remaining intact tropical peatlands; thus, we excluded peatlands of Indonesia and Malaysia, where extensive deforestation, drainage, and conversion to plantations means conservation in this region can protect only small fragments of the original ecosystem. We focused on a case study, the Pastaza‐Marañón Foreland Basin (PMFB) in Peru, which is among the largest known intact tropical peatland landscapes in the world and is representative of peatland vulnerability. Maintenance of the hydrological conditions critical for carbon storage and ecosystem function of peatlands is, in the PMFB, primarily threatened by expansion of commercial agriculture linked to new transport infrastructure that is facilitating access to remote areas. There remain opportunities in the PMFB and elsewhere to develop alternative, more sustainable land‐use practices. Although some of the peatlands in the PMFB fall within existing legally protected areas, this protection does not include the most carbon‐dense (domed pole forest) areas. New carbon‐based conservation instruments (e.g., REDD+, Green Climate Fund), developing markets for sustainable peatland products, transferring land title to local communities, and expanding protected areas offer pathways to increased protection for intact tropical peatlands in Amazonia and elsewhere, such as those in New Guinea and Central Africa which remain, for the moment, broadly beyond the frontier of commercial development.     

Using a Bayesian network to clarify areas requiring research in a host–pathogen system

Bayesian network analyses can be used to interactively change the strength of effect of variables in a model to explore complex relationships in new ways. In doing so, they allow one to identify influential nodes that are not well studied empirically so that future research can be prioritized. We identified relationships in host and pathogen biology to examine disease‐driven declines of amphibians associated with amphibian chytrid fungus (Batrachochytrium dendrobatidis). We constructed a Bayesian network consisting of behavioral, genetic, physiological, and environmental variables that influence disease and used them to predict host population trends. We varied the impacts of specific variables in the model to reveal factors with the most influence on host population trend. The behavior of the nodes (the way in which the variables probabilistically responded to changes in states of the parents, which are the nodes or variables that directly influenced them in the graphical model) was consistent with published results. The frog population had a 49% probability of decline when all states were set at their original values, and this probability increased when body temperatures were cold, the immune system was not suppressing infection, and the ambient environment was conducive to growth of B. dendrobatidis. These findings suggest the construction of our model reflected the complex relationships characteristic of host–pathogen interactions. Changes to climatic variables alone did not strongly influence the probability of population decline, which suggests that climate interacts with other factors such as the capacity of the frog immune system to suppress disease. Changes to the adaptive immune system and disease reservoirs had a large effect on the population trend, but there was little empirical information available for model construction. Our model inputs can be used as a base to examine other systems, and our results show that such analyses are useful tools for reviewing existing literature, identifying links poorly supported by evidence, and understanding complexities in emerging infectious‐disease systems.     

Investigating the link between $$\hbox {PM}_{2.5}$$ and atmospheric profile variables via penalized functional quantile regression

Fine particulate matter (\(\hbox {PM}_{2.5}\)) events negatively affect the health of numerous persons globally each year. Previous works have described the association between air pollution and surface-level meteorological conditions; however, there has been less focus on the task of linking air pollution events with meteorological conditions at higher levels of the atmosphere. Working within the functional data framework, we develop a penalized functional quantile regression (PFQR) procedure to model conditional quantiles of a continuous response based on a functional covariate, with the ability to penalize selected derivatives of the estimated coefficient function. Our aim is to investigate the relationship between atmospheric profile variables (APVs), assumed to be functional, and key quantiles of the conditional distribution of surface-level \(\hbox {PM}_{2.5}\). Via a simulation study, we find that the performance of our PFQR procedure compares favorably to other related approaches. We conclude with an analysis of \(\hbox {PM}_{2.5}\) data at two Southeastern US locations, Columbia, SC and Tampa, FL, where we estimate the coefficient functions for the APVs corresponding to both ‘typical’ and ‘high’ \(\hbox {PM}_{2.5}\) events. As we believe that the true coefficient functions are smooth and may be exactly zero over subsets of their domains, we impose penalties on the 0th and 2nd derivatives. Our analysis indicates that the corresponding atmospheric conditions differ between the two locations, and that the conditions differ seasonally within location.     

Atrazine contamination in agricultural soils from the Yangtze River Delta of China and associated health risks

Atrazine is one of the most widely applied and persistent herbicides in the world. In view of limited information on the regional contamination of atrazine in soils in China, this study investigated the spatial distribution and environmental impacts of atrazine in agricultural soils collected from the Yangtze River Delta (YRD) as an illustrative analysis of rapidly developing regions in the country. The results showed that the concentrations of atrazine in the YRD agricultural soils ranged from <1.0 to 113 ng/g dry weight, with a mean of 5.7 ng/g, and a detection rate of 57.7 % in soils. Pesticide factory might be a major source for the elevated levels of atrazine in Zhejiang Province. The contamination of atrazine was closely associated with land use types. The concentrations and detection rates of atrazine were higher in corn fields and mulberry fields than in rice paddy fields. There was no significant difference in compositions of soil microbial phospholipids fatty acids among the areas with different atrazine levels. Positive relationship (R = 0.417, p < 0.05, n = 30) was observed between atrazine and total microbial biomass. However, other factors, such as soil type and land management practice, might have stronger influences on soil microbial communities. Human health risks via exposure to atrazine in soils were estimated according to the methods recommended by the US EPA. Atrazine by itself in all the soil samples imposed very low carcinogenic risks (<10^?6) and minimal non-cancer risks (hazard index <1) to adults and children.     

Bacterial toxicity testing and antibacterial activity of parabens

Parabens are used because of their antimicrobial effects, yet they have multiple adverse effects. The aim of this work was to evaluate the bactericidal activity and bacterial toxicity of the most common parabens: methylparaben, ethylparaben, propylparaben, isopropylparaben, butylparaben, isobutylparaben and phenylparaben. The bactericidal action was evaluated by means of the dilution-neutralization method against Escherichia coli and Staphylococcus aureus, and the biotest of inhibition of growth of E. coli was applied for the bacterial toxicity assay. Bactericidal concentrations were reached only for propylparaben, butylparaben and isobutylparaben. The toxicity study showed methylparaben to be the least toxic, whereas the most toxic one was phenylparaben. It can be concluded that the disinfectant activity of the parabens studied is insignificant against S. aureus and E. coli. Acute toxicity is very low, and the inhibitory effect is weak. Our results provide information about the risk–benefit balance of parabens use.     

Fine‐resolution conservation planning with limited climate‐change information

Climate‐change induced uncertainties in future spatial patterns of conservation‐related outcomes make it difficult to implement standard conservation‐planning paradigms. A recent study translates Markowitz's risk‐diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate‐change scenarios for carrying out fine‐resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk‐return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate‐change information and full climate‐change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate‐change forecasts such that the best possible risk‐return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate‐change information could be reduced by 17% relative to other iterative approaches.     

Inaction levels for the red imported fire ant, Solenopsis invicta (hym.: formicidae): A predator of the boll weevil, Anthonomus grandis (col.: curculionidae)

The density of red imported fire ants, Solenopsis invicta Buren (Hymenoptera: Formicidae), necessary to limit boll weevil abundance, Anthonomus grandis Boheman (Coleoptera: Curculionidae), below the action level was determined. An inaction level of 0.4 fire ants per shake bucket sample (i.e., four ants per 10 plant terminals) will provide boll weevil control approximately 90% of the time. A dynamic inaction level is also provided. Total mortality of boll weevil developmental stages including eggs through teneral adults averaged 97.9%. Of 100 boll weevil eggs deposited in cotton squares (flower buds), an average of two adults survive of which about half are female. Thus, the net replacement rate per generation (R_o is 1.0 which, in this case, indicates a stable boll weevil population.