Extinction risk modeling predicts range-wide differences of climate change impact on Karner blue butterfly (Lycaeides melissa samuelis).

The Karner blue butterfly (Lycaeides melissa samuelis, or Kbb), a federally endangered species under the U.S. Endangered Species Act in decline due to habitat loss, can be further threatened by climate change. Evaluating how climate shapes the population trend of the Kbb can help in the development of adaptive management plans. Current demographic models for the Kbb incorporate in either a density-dependent or density-independent manner. We instead created mixed density-dependent and -independent (hereafter "endo-exogenous") models for Kbbs based on long-term count data of five isolated populations in the upper Midwest, United States during two flight periods (May to June and July to August) to understand how the growth rates were related to previous population densities and abiotic environmental conditions, including various macro- and micro-climatic variables. Our endo-exogenous extinction risk models showed that both density-dependent and -independent components were vital drivers of the historical population trends. However, climate change impacts were not always detrimental to Kbbs. Despite the decrease of population growth rate with higher overwinter temperatures and spring precipitations in the first generation, the growth rate increased with higher summer temperatures and precipitations in the second generation. We concluded that finer spatiotemporally scaled models could be more rewarding in guiding the decision-making process of Kbb restoration under climate change.

Feature selection and association rule learning identify risk factors of malnutrition among Ethiopian schoolchildren.

Introduction: Previous studies have sought to identify risk factors for malnutrition in populations of schoolchildren, depending on traditional logistic regression methods. However, holistic machine learning (ML) approaches are emerging that may provide a more comprehensive analysis of risk factors. Methods: This study employed feature selection and association rule learning ML methods in conjunction with logistic regression on epidemiological survey data from 1,036 Ethiopian school children. Our first analysis used the entire dataset and then we reran this analysis on age, residence, and sex population subsets. Results: Both logistic regression and ML methods identified older childhood age as a significant risk factor, while females and vaccinated individuals showed reduced odds of stunting. Our machine learning analyses provided additional insights into the data, as feature selection identified that age, school latrine cleanliness, large family size, and nail trimming habits were significant risk factors for stunting, underweight, and thinness. Association rule learning revealed an association between co-occurring hygiene and socio-economical variables with malnutrition that was otherwise missed using traditional statistical methods. Discussion: Our analysis supports the benefit of integrating feature selection methods, association rules learning techniques, and logistic regression to identify comprehensive risk factors associated with malnutrition in young children.

Physical integrity: the missing link in biological monitoring and TMDLs.

The Clean Water Act mandates that the chemical, physical, and biological integrity of our nation's waters be maintained and restored. Physical integrity has often been defined as physical habitat integrity, and as such, data collected during biological monitoring programs focus primarily on habitat quality. However, we argue that channel stability is a more appropriate measure of physical integrity and that channel stability is a foundational element of physical habitat integrity in low-gradient alluvial streams. We highlight assessment tools that could supplement stream assessments and the Total Maximum Daily Load stressor identification process: field surveys of bankfull cross-sections; longitudinal thalweg profiles; particle size distribution; and regionally calibrated, visual, stream stability assessments. Benefits of measuring channel stability include a more informed selection of reference or best attainable stream condition for an Index of Biotic Integrity, establishment of a baseline for monitoring changes in present and future condition, and indication of channel stability for investigations of chemical and biological impairments associated with sediment discontinuity and loss of habitat quality.

Road effects on abundance and fitness of Galápagos lava lizards (Microlophus albemarlensis).

Vehicle collisions with wildlife have the potential to negatively impact species everywhere roads divide natural habitats; this is especially true in areas where roads are a recent addition to the landscape (e.g., in the last decade) and/or where expansion of a road network is underway. This study addresses the impact of traffic fatalities on lava lizards, Microlophus albemarlensis, on the island of Santa Cruz, Galápagos. The main road bisecting the island north to south was added to the island beginning in 1974 but not fully paved until 2000. We assessed impacts occurring due to traffic and vehicle speeds on the island. This study adds impacts to lizard populations to those conducted on birds on Santa Cruz, providing a means to create multi-species recommendations. To quantify impacts to lizard populations, we assessed lizards on randomly chosen transects perpendicular to the road. We used Poisson regression to analyze those data and found a 30% increase in lizard abundance per 100 m distance from the road across vegetation zones. We compared incidence of prior tail loss of road-killed lizards and live animals to comment on additional energetic costs of occupying near-road territories. Tail condition could not be assessed in some road-killed lizards; among those that we could assess, 29% showed evidence of prior tail loss. That rate declined to apparent baseline conditions of only 1% beyond 200 m from the road. By traveling the length of the 40-km road, we identified hot spots for fatalities of both lizards and birds to provide necessary information for developing management and remediation strategies. We offer guidance on Best Management Practices, such as testing overpasses, fencing and underpasses, which might reduce vehicle impacts to lizards from drivers on the current road. This information is essential because of a planned increase in the Santa Cruz road network in areas where lava lizards are most abundant.