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Among one of the key challenges in dairy production is the management of manure in a way that is beneficial for agricultural production, with minimal environmental and public health impacts. Manure management systems (MMS)—the entire system of handling, storage, and application of manure—are diverse in countries with developed dairy industries such as the United States, enabled by a number of different technologies. The ways in which dairy farmers manage manure is driven by varying tradeoffs, including economic, social, and environmental; however, existing research has not examined the relationships between components of MMS. Here we use data from the National Animal Health Monitoring System's Dairy 2014 study to explore the ways in which manure handling, storage, and application are related, using a series of logistic regression models and network associations. We found significant associations between how manure is handled, stored, and applied, especially driven by the consistency of manure. For solid manure, we found highly heterogeneous systems, where farmers may have a suite of alternative manure management strategies available to them, and substitution is viable. Conversely, farms using liquid manure systems have very few substitutes in their MMS, suggesting greater investment in certain infrastructures, which are not easily changed. Such findings have important implications for shifting farmers towards management practices with minimal environmental and public health impacts, demonstrating that not all farm systems are easily changed. We highlight these results in light of current policies, which may not fully capture the relationships across the MMS, and suggest that greater financing may be necessary to shift MMS on some farms. Furthermore, we suggest that different MMS have varying tradeoffs across environmental, social, and economic aspects, which demonstrates that MMS are highly individualized to a given farm's goals and priorities. [ABSTRACT FROM AUTHOR]

Wild pigs (Sus scrofa), also known as wild swine, feral pigs, or feral hogs, are one of the most widespread and successful invasive species around the world. Wild pigs have been linked to extensive and costly agricultural damage and present a serious threat to plant and animal communities due to their rooting behavior and omnivorous diet. We modeled the current distribution of wild pigs in the United States to better understand the physiological and ecological factors that may determine their invasive potential and to guide future study and eradication efforts. Using national-scale wild pig occurrence data reported between 1982 and 2012 by wildlife management professionals, we estimated the probability of wild pig occurrence across the United States using a logistic discrimination function and environmental covariates hypothesized to influence the distribution of the species. Our results suggest the distribution of wild pigs in the U.S. was most strongly limited by cold temperatures and availability of water, and that they were most likely to occur where potential home ranges had higher habitat heterogeneity, providing access to multiple key resources including water, forage, and cover. High probability of occurrence was also associated with frequent high temperatures, up to a high threshold. However, this pattern is driven by pigs’ historic distribution in warm climates of the southern U.S. Further study of pigs’ ability to persist in cold northern climates is needed to better understand whether low temperatures actually limit their distribution. Our model highlights areas at risk of invasion as those with habitat conditions similar to those found in pigs’ current range that are also near current populations. This study provides a macro-scale approach to generalist species distribution modeling that is applicable to other generalist and invasive species. [ABSTRACT FROM AUTHOR]

Concerns regarding the commercial release of genetically engineered (GE) crops include naturalization, introgression to sexually compatible relatives and the transfer of beneficial traits to native and weedy species through hybridization. To date there have been few documented reports of escape leading some researchers to question the environmental risks of biotech products. In this study we conducted a systematic roadside survey of canola (Brassica napus) populations growing outside of cultivation in North Dakota, USA, the dominant canola growing region in the U.S. We document the presence of two escaped, transgenic genotypes, as well as non-GE canola, and provide evidence of novel combinations of transgenic forms in the wild. Our results demonstrate that feral populations are large and widespread. Moreover, flowering times of escaped populations, as well as the fertile condition of the majority of collections suggest that these populations are established and persistent outside of cultivation. [ABSTRACT FROM AUTHOR]

Whereas past wolf management in the United States was restricted to recovery, managers must now contend with publicly contentious post-recovery issues including regulated hunting seasons. Understanding stakeholder concerns associated with hunting can inform stakeholder engagement, communication, and policy development and evaluation. Social identity theory (SIT) has been used to understand how groups interact, why they conflict, and how collaboration may be achieved. Applying SIT to stakeholder conflicts about wolf hunting may help delineate groups according to their concern about, support for or opposition to the policy choice of hunting wolves. Our objective was to assess concerns about hunting as a tool to resolve conflict in Michigan, using SIT as a framework. We used a mixed-modal sampling approach (e.g., paper, Internet) with wolf hunting-related public meeting participants in March 2013. Survey questions focused on 12 concerns previously identified as associated with hunting as a management tool to resolve conflict. Respondents (n  =  666) cared greatly about wolves but were divided over hunting wolves. Wolf conflicts, use of science in policy decisions, and maintaining a wolf population were the highest ranked concerns. Principle components analysis reduced concerns into three factors that explained 50.7% of total variance; concerns crystallized over justifications for hunting. General linear models revealed a lack of geographic influence on care, fear and support for hunting related to wolves. These findings challenge assumptions about regional differences and suggest a strong role for social identity in driving dichotomized public perceptions in wildlife management. [ABSTRACT FROM AUTHOR]

Qualitative health data are rarely shared in the United States (U.S.). This is unfortunate because gathering qualitative data is labor and time-intensive, and data sharing enables secondary research, training, and transparency. A new U.S. federal policy mandates data sharing by 2023, and is agnostic to data type. We surveyed U.S. qualitative researchers (N = 425) on the barriers and facilitators of sharing qualitative health or sensitive research data. Most researchers (96%) have never shared qualitative data in a repository. Primary concerns were lack of participant permission to share data, data sensitivity, and breaching trust. Researcher willingness to share would increase if participants agreed and if sharing increased the societal impact of their research. Key resources to increase willingness to share were funding, guidance, and de-identification assistance. Public health and biomedical researchers were most willing to share. Qualitative researchers need to prepare for this new reality as sharing qualitative data requires unique considerations. [ABSTRACT FROM AUTHOR]

Background: The level of body-mass index (BMI) associated with the lowest risk of death remains unclear. Although differences in muscle mass limit the utility of BMI as a measure of adiposity, no study has directly examined the effect of muscle mass on the BMI-mortality relationship. Methods: Body composition was measured by dual-energy x-ray absorptiometry in 11,687 participants of the National Health and Nutrition Examination Survey 1999–2004. Low muscle mass was defined using sex-specific thresholds of the appendicular skeletal muscle mass index (ASMI). Proportional hazards models were created to model associations with all-cause mortality. Results: At any level of BMI ≥22, participants with low muscle mass had higher body fat percentage (%TBF), an increased likelihood of diabetes, and higher adjusted mortality than other participants. Increases in %TBF manifested as 30–40% smaller changes in BMI than were observed in participants with preserved muscle mass. Excluding participants with low muscle mass or adjustment for ASMI attenuated the risk associated with low BMI, magnified the risk associated with high BMI, and shifted downward the level of BMI associated with the lowest risk of death. Higher ASMI was independently associated with lower mortality. Effects were similar in never-smokers and ever-smokers. Additional adjustment for waist circumference eliminated the risk associated with higher BMI. Results were unchanged after excluding unintentional weight loss, chronic illness, early mortality, and participants performing muscle-strengthening exercises or recommended levels of physical activity. Conclusions: Muscle mass mediates associations of BMI with adiposity and mortality and is inversely associated with the risk of death. After accounting for muscle mass, the BMI associated with the greatest survival shifts downward toward the normal range. These results provide a concrete explanation for the obesity paradox. [ABSTRACT FROM AUTHOR]

Conservation scientists emphasize the importance of maintaining a connected network of protected areas to prevent ecosystems and populations from becoming isolated, reduce the risk of extinction, and ultimately sustain biodiversity. Keeping protected areas connected in a network is increasingly recognized as a conservation priority in the current era of rapid climate change. Models that identify suitable linkages between core areas have been used to prioritize potentially important corridors for maintaining functional connectivity. Here, we identify the most “natural” (i.e., least human-modified) corridors between large protected areas in the contiguous Unites States. We aggregated results from multiple connectivity models to develop a composite map of corridors reflecting agreement of models run under different assumptions about how human modification of land may influence connectivity. To identify which land units are most important for sustaining structural connectivity, we used the composite map of corridors to evaluate connectivity priorities in two ways: (1) among land units outside of our pool of large core protected areas and (2) among units administratively protected as Inventoried Roadless (IRAs) or Wilderness Study Areas (WSAs). Corridor values varied substantially among classes of “unprotected” non-core land units, and land units of high connectivity value and priority represent diverse ownerships and existing levels of protections. We provide a ranking of IRAs and WSAs that should be prioritized for additional protection to maintain minimal human modification. Our results provide a coarse-scale assessment of connectivity priorities for maintaining a connected network of protected areas. [ABSTRACT FROM AUTHOR]

Background: Individuals of African descent in the United States suffer disproportionately from diseases with a metabolic etiology (obesity, metabolic syndrome, and diabetes), and from the pathological consequences of these disorders (hypertension and cardiovascular disease). Methodology/Principal Findings: Using a combination of genetic/genomic and bioinformatics approaches, we identified a large number of genes that were both differentially expressed between American subjects self-identified to be of either African or European ancestry and that also contained single nucleotide polymorphisms that distinguish distantly related ancestral populations. Several of these genes control the metabolism of simple carbohydrates and are direct targets for the SREBP1, a metabolic transcription factor also differentially expressed between our study populations. Conclusions/Significance: These data support the concept of stable patterns of gene transcription unique to a geographic ancestral lineage. Differences in expression of several carbohydrate metabolism genes suggest both genetic and transcriptional mechanisms contribute to these patterns and may play a role in exacerbating the disproportionate levels of obesity, diabetes, and cardiovascular disease observed in Americans with African ancestry. [ABSTRACT FROM AUTHOR]