Causes and Consequences of Broad-Scale Changes in the Distribution of Migratory Caribou (Rangifer tarandus) of Southern Hudson Bay

Understanding the factors driving changes in species distributions is fundamental to conservation, but for wide-ranging species this is often complicated by the need for broad-scale observations across space and time. In the last three decades, the location of summer concentrations of migratory caribou (Rangifer tarandus) in southern Hudson Bay (SHB), Canada, has shifted south and east as much as 500 km. We used long-term data (1987 – 2011) to test two hypotheses that could explain the distribution shift: forage depletion and anthropogenic disturbance. Over time and space, we compared the body size of live-captured adult female caribou, dietary quality from fecal nitrogen in July, the location of VHF- and GPS-collared female caribou in July, distribution of all-terrain vehicle (ATV) tracks and caribou tracks in August, and the proximity of collared caribou to sections of the coast with higher ATV activity in spring and summer. The forage depletion hypothesis was supported by greater body size and dietary quality in caribou of the eastern portion of SHB than in western SHB animals in 2009 – 11. The anthropogenic disturbance hypothesis was supported by the negative correlation of the distributions of ATV tracks and caribou tracks on the coast in 2010 and the fact that caribou avoided areas with ATV activity by 10 – 14 km. In 1987, collared caribou were observed largely along the coast in western SHB in mid-July, while in 2009 – 11, they were inland in western SHB and along the coast in eastern SHB. While these locations demonstrate a substantial change in summer distri­bution over three decades, we were unable to differentiate between forage depletion and anthropogenic disturbance as a single causal factor of the distribution shift.La compréhension des facteurs qui influencent les changements caractérisant les distributions des espèces est fondamentale aux efforts de conservation, mais pour les espèces dont l’aire de distribution est étendue, ce principe est souvent compliqué par la nécessité de faire des observations à grande échelle, dans le temps et dans l’espace. Au cours des trois dernières décennies, l’emplacement des concentrations estivales du caribou migrateur (Rangifer tarandus) dans le sud de la baie d’Hudson (SBH), au Canada, s’est déplacé vers le sud et vers l’est dans une mesure de 500 km. Nous nous sommes appuyés sur des données de longue haleine (1987–2011) pour mettre à l’épreuve deux hypothèses susceptibles d’expliquer ce changement en matière de distribution, soit l’appauvrissement du fourrage et la perturbation anthropique. Au fil du temps et de l’espace, nous avons comparé la taille du corps des caribous femelles adultes capturées vivantes, la qualité de leur alimentation à partir de l’azote fécal en juillet, l’emplacement des femelles portant un collier de type VHF ou GPS en juillet, la répartition des traces de véhicules tout terrain (VTT) et des pistes de caribou en août de même que la proximité des caribous portant un collier aux tronçons de la côte où la présence de VTT est plus grande au printemps et à l’été. L’hypothèse de l’appauvrissement du fourrage a été étayée par la plus grande taille du corps et la qualité de l’alimentation du caribou de la zone est du SBH comparativement à celles du caribou de l’ouest du SBH entre 2009 et 2011. Pour sa part, l’hypothèse perturbation anthropique a été appuyée par la corrélation négative caractérisant la répartition des pistes de VTT et des traces de caribou sur la côte en 2010 et par le fait que les caribous sont restés à l’écart des zones fréquentées par les VTT dans une mesure de 10 à 14 km. En 1987, des caribous portant un collier ont été observés en grand nombre le long de la côte ouest du SBH à la mi-juillet, tandis que de 2009 à 2011, ils ont été repérés à l’intérieur des terres dans l’ouest du SBH et le long de la côte est du SBH. Bien que ces emplacements indiquent un important changement en matière de distribution estivale au cours de trois décennies, nous n’avons pas été en mesure de faire une distinction entre l’appauvrissement du fourrage et la perturbation anthropique en tant que facteur causal unique du changement de distribution

Characterizing K2 Candidate Planetary Systems Orbiting Low-Mass Stars II: Planetary Systems Observed During Campaigns 1-7

We recently used near-infrared spectroscopy to improve the characterization of 76 low-mass stars around which K2 had detected 79 candidate transiting planets. 29 of these worlds were new discoveries that had not previously been published. We calculate the false positive probabilities that the transit-like signals are actually caused by non-planetary astrophysical phenomena and reject five new transit-like events and three previously reported events as false positives. We also statistically validate 17 planets (7 of which were previously unpublished), confirm the earlier validation of 22 planets, and announce 17 newly discovered planet candidates. Revising the properties of the associated planet candidates based on the updated host star characteristics and refitting the transit photometry, we find that our sample contains 21 planets or planet candidates with radii smaller than 1.25 R⊕, 18 super-Earths (1.25–2 R⊕), 21 small Neptunes (2–4 R⊕), three large Neptunes (4–6 R⊕), and eight giant planets (>6 R⊕). Most of these planets are highly irradiated, but EPIC 206209135.04 (K2-72e, 1.29^(+0.14)_(-0.13) R⊕), EPIC 211988320.01 (R_p = 2.86^(+0.16)_(-0.15) R⊕), and EPIC 212690867.01 (2.20^(+0.19)_(-0.18) R⊕) orbit within optimistic habitable zone boundaries set by the "recent Venus" inner limit and the "early Mars" outer limit. In total, our planet sample includes eight moderately irradiated 1.5–3 R⊕ planet candidates (F_p ≾ 20 F⊕) orbiting brighter stars (Ks < 11) that are well-suited for atmospheric investigations with the Hubble, Spitzer, and/or James Webb Space Telescopes. Five validated planets orbit relatively bright stars (Kp < 12.5) and are expected to yield radial velocity semi-amplitudes of at least 2 m s^(−1). Accordingly, they are possible targets for radial velocity mass measurement with current facilities or the upcoming generation of red optical and near-infrared high-precision RV spectrographs

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

Motion-activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the “species model,” and one that determines if an image is empty or if it contains an animal, the “empty-animal model.” Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%–91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%–94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths

Average Household Exposure to Newspaper Coverage about the Harmful Effects of Hormone Therapy and Population-Based Declines in Hormone Therapy Use

BACKGROUND: The news media facilitated the rapid dissemination of the findings from the estrogen plus progestin therapy arm of the Women’s Health Initiative (EPT-WHI). OBJECTIVE: To examine the relationship between the potential exposure to newspaper coverage and subsequent hormone therapy (HT) use. DESIGN/POPULATION: Population-based cohort of women receiving mammography at 7 sites (327,144 postmenopausal women). MEASUREMENTS: The outcome was the monthly prevalence of self-reported HT use. Circulation data for local, regional, and national newspapers was used to create zip-code level measures of the estimated average household exposure to newspaper coverage that reported the harmful effects of HT in July 2002. RESULTS: Women had an average potential household exposure of 1.4 articles. There was substantial variation in the level of average household exposure to newspaper coverage; women from rural sites received less than women from urban sites. Use of HT declined for all average potential exposure groups after the publication of the EPT-WHI. HT prevalence among women who lived in areas where there was an average household exposure of at least 3 articles declined significantly more (45 to 27%) compared to women who lived in areas with <1 article (43 to 31%) during each of the subsequent 5 months (relative risks 0.86–0.92; p < .006 for all). CONCLUSIONS: Greater average household exposure to newspaper coverage about the harms associated with HT was associated with a large population-based decline in HT use. Further studies should examine whether media coverage directly influences the health behavior of individual women

Moderators of Exercise Effects on Cancer-related Fatigue:A Meta-analysis of Individual Patient Data

PURPOSE: Fatigue is a common and potentially disabling symptom in patients with cancer. It can often be effectively reduced by exercise. Yet, effects of exercise interventions might differ across subgroups. We conducted a meta-analysis using individual patient data of randomized controlled trials (RCT) to investigate moderators of exercise intervention effects on cancer-related fatigue. METHODS: We used individual patient data from 31 exercise RCT worldwide, representing 4366 patients, of whom 3846 had complete fatigue data. We performed a one-step individual patient data meta-analysis, using linear mixed-effect models to analyze the effects of exercise interventions on fatigue (z score) and to identify demographic, clinical, intervention- and exercise-related moderators. Models were adjusted for baseline fatigue and included a random intercept on study level to account for clustering of patients within studies. We identified potential moderators by testing their interaction with group allocation, using a likelihood ratio test. RESULTS: Exercise interventions had statistically significant beneficial effects on fatigue (β = -0.17; 95% confidence interval [CI], -0.22 to -0.12). There was no evidence of moderation by demographic or clinical characteristics. Supervised exercise interventions had significantly larger effects on fatigue than unsupervised exercise interventions (βdifference = -0.18; 95% CI -0.28 to -0.08). Supervised interventions with a duration ≤12 wk showed larger effects on fatigue (β = -0.29; 95% CI, -0.39 to -0.20) than supervised interventions with a longer duration. CONCLUSIONS: In this individual patient data meta-analysis, we found statistically significant beneficial effects of exercise interventions on fatigue, irrespective of demographic and clinical characteristics. These findings support a role for exercise, preferably supervised exercise interventions, in clinical practice. Reasons for differential effects in duration require further exploration

Dropout from exercise trials among cancer survivors—An individual patient data meta-analysis from the POLARIS study

Introduction: The number of randomized controlled trials (RCTs) investigating the effects of exercise among cancer survivors has increased in recent years; however, participants dropping out of the trials are rarely described. The objective of the present study was to assess which combinations of participant and exercise program characteristics were associated with dropout from the exercise arms of RCTs among cancer survivors. Methods: This study used data collected in the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) study, an international database of RCTs investigating the effects of exercise among cancer survivors. Thirty-four exercise trials, with a total of 2467 patients without metastatic disease randomized to an exercise arm were included. Harmonized studies included a pre and a posttest, and participants were classified as dropouts when missing all assessments at the post-intervention test. Subgroups were identified with a conditional inference tree. Results: Overall, 9.6% of the participants dropped out. Five subgroups were identified in the conditional inference tree based on four significant associations with dropout. Most dropout was observed for participants with BMI &gt;28.4 kg/m2, performing supervised resistance or unsupervised mixed exercise (19.8% dropout) or had low-medium education and performed aerobic or supervised mixed exercise (13.5%). The lowest dropout was found for participants with BMI &gt;28.4 kg/m2 and high education performing aerobic or supervised mixed exercise (5.1%), and participants with BMI ≤28.4 kg/m2 exercising during (5.2%) or post (9.5%) treatment. Conclusions: There are several systematic differences between cancer survivors completing and dropping out from exercise trials, possibly affecting the external validity of exercise effects.</p

Targeting exercise interventions to patients with cancer in need:An individual patient data meta-analysis

Background: Exercise effects in cancer patients often appear modest, possibly because interventions rarely target patients most in need. This study investigated the moderator effects of baseline values on the exercise outcomes of fatigue, aerobic fitness, muscle strength, quality of life (QoL), and self-reported physical function (PF) in cancer patients during and post-treatment. Methods: Individual patient data from 34 randomized exercise trials (n = 4519) were pooled. Linear mixed-effect models were used to study moderator effects of baseline values on exercise intervention outcomes and to determine whether these moderator effects differed by intervention timing (during vs post-treatment). All statistical tests were two-sided. Results: Moderator effects of baseline fatigue and PF were consistent across intervention timing, with greater effects in patients with worse fatigue (Pinteraction = .05) and worse PF (Pinteraction = .003). Moderator effects of baseline aerobic fitness, muscle strength, and QoL differed by intervention timing. During treatment, effects on aerobic fitness were greater for patients with better baseline aerobic fitness (Pinteraction = .002). Post-treatment, effects on upper (Pinteraction &lt; .001) and lower (Pinteraction = .01) body muscle strength and QoL (Pinteraction &lt; .001) were greater in patients with worse baseline values. Conclusion: Although exercise should be encouraged for most cancer patients during and post-treatments, targeting specific subgroups may be especially beneficial and cost effective. For fatigue and PF, interventions during and post-treatment should target patients with high fatigue and low PF. During treatment, patients experience benefit for muscle strength and QoL regardless of baseline values; however, only patients with low baseline values benefit post-treatment. For aerobic fitness, patients with low baseline values do not appear to benefit from exercise during treatment

Unravelling Soil Fungal Communities from Different Mediterranean Land-Use Backgrounds

Fungi strongly influence ecosystem structure and functioning, playing a key role in many ecological services as decomposers, plant mutualists and pathogens. The Mediterranean area is a biodiversity hotspot that is increasingly threatened by intense land use. Therefore, to achieve a balance between conservation and human development, a better understanding of the impact of land use on the underlying fungal communities is needed.We used parallel pyrosequencing of the nuclear ribosomal ITS regions to characterize the fungal communities in five soils subjected to different anthropogenic impact in a typical Mediterranean landscape: a natural cork-oak forest, a pasture, a managed meadow, and two vineyards. Marked differences in the distribution of taxon assemblages among the different sites and communities were found. Data analyses consistently indicated a sharp distinction of the fungal community of the cork oak forest soil from those described in the other soils. Each soil showed features of the fungal assemblages retrieved which can be easily related to the above-ground settings: ectomycorrhizal phylotypes were numerous in natural sites covered by trees, but were nearly completely missing from the anthropogenic and grass-covered sites; similarly, coprophilous fungi were common in grazed sites.Data suggest that investigation on the below-ground fungal community may provide useful elements on the above-ground features such as vegetation coverage and agronomic procedures, allowing to assess the cost of anthropogenic land use to hidden diversity in soil. Datasets provided in this study may contribute to future searches for fungal bio-indicators as biodiversity markers of a specific site or a land-use degree

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe