Recreation Effects on Wildlife: A Review of Potential Quantitative Thresholds

Outdoor recreation is increasingly recognised for its deleterious effects on wildlife individuals and populations. However, planners and natural resource managers lack robust scientific recommendations for the design of recreation infrastructure and management of recreation activities. We reviewed 38 years of research on the effect of non-consumptive recreation on wildlife to attempt to identify effect thresholds or the point at which recreation begins to exhibit behavioural or physiological change to wildlife. We found that 53 of 330 articles identified a quantitative threshold. The majority of threshold articles focused on bird or mammal species and measured the distance to people or to a trail. Threshold distances varied substantially within and amongst taxonomic groups. Threshold distances for wading and passerine birds were generally less than 100 m, whereas they were greater than 400 m for hawks and eagles. Mammal threshold distances varied widely from 50 m for small rodents to 1,000 m for large ungulates. We did not find a significant difference between threshold distances of different recreation activity groups, likely based in part on low sample size. There were large gaps in scientific literature regarding several recreation variables and taxonomic groups including amphibians, invertebrates and reptiles. Our findings exhibit the need for studies to measure continuous variables of recreation extent and magnitude, not only to detect effects of recreation on wildlife, but also to identify effect thresholds when and where recreation begins or ceases to affect wildlife. Such considerations in studies of recreation ecology could provide robust scientific recommendations for planners and natural resource managers for the design of recreation infrastructure and management of recreation activities

An applied ecology of fear framework: linking theory to conservation practice

Research on the ecology of fear has highlighted the importance of perceived risk from predators and humans in shaping animal behavior and physiology, with potential demographic and ecosystem-wide consequences. Despite recent conceptual advances and potential management implications of the ecology of fear, theory and conservation practices have rarely been linked. Many challenges in animal conservation may be alleviated by actively harnessing or compensating for risk perception and risk avoidance behavior in wild animal populations. Integration of the ecology of fear into conservation and management practice can contribute to the recovery of threatened populations, human–wildlife conflict mitigation, invasive species management, maintenance of sustainable harvest and species reintroduction plans. Here, we present an applied framework that links conservation interventions to desired outcomes by manipulating ecology of fear dynamics. We discuss how to reduce or amplify fear in wild animals by manipulating habitat structure, sensory stimuli, animal experience (previous exposure to risk) and food safety trade-offs to achieve management objectives. Changing the optimal decision-making of individuals in managed populations can then further conservation goals by shaping the spatiotemporal distribution of animals, changing predation rates and altering risk effects that scale up to demographic consequences. We also outline future directions for applied research on fear ecology that will better inform conservation practices. Our framework can help scientists and practitioners anticipate and mitigate unintended consequences of management decisions, and highlight new levers for multi-species conservation strategies that promote human–wildlife coexistence

Recombinant Interleukin-2 in Patients Aged Younger Than 60 Years With Acute Myeloid Leukemia in First Complete Remission: Results From Cancer and Leukemia Group B 19808

Recombinant interleukin-2 (rIL-2) induces cellular cytotoxicity against leukemia blasts. Patients with acute myeloid leukemia (AML) in first complete remission (CR) may harbor minimal residual disease that is susceptible to rIL-2–activated effector cells

Assessment of Brain Age in Posttraumatic Stress Disorder: Findings from the ENIGMA PTSD and Brain Age Working Groups

Background Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies

Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships

Developing an agenda for research about policies to improve access to healthy foods in rural communities: a concept mapping study

Background Policies that improve access to healthy, affordable foods may improve population health and reduce health disparities. In the United States most food access policy research focuses on urban communities even though residents of rural communities face disproportionately higher risk for nutrition-related chronic diseases compared to residents of urban communities. The purpose of this study was to (1) identify the factors associated with access to healthy, affordable food in rural communities in the United States; and (2) prioritize a meaningful and feasible rural food policy research agenda. Methods This study was conducted by the Rural Food Access Workgroup (RFAWG), a workgroup facilitated by the Nutrition and Obesity Policy Research and Evaluation Network. A national sample of academic and non-academic researchers, public health and cooperative extension practitioners, and other experts who focus on rural food access and economic development was invited to complete a concept mapping process that included brainstorming the factors that are associated with rural food access, sorting and organizing the factors into similar domains, and rating the importance of policies and research to address these factors. As a last step, RFAWG members convened to interpret the data and establish research recommendations. Results Seventy-five participants in the brainstorming exercise represented the following sectors: non-extension research (n = 27), non-extension program administration (n = 18), “other� (n = 14), policy advocacy (n = 10), and cooperative extension service (n = 6). The brainstorming exercise generated 90 distinct statements about factors associated with rural food access in the United States; these were sorted into 5 clusters. Go Zones were established for the factors that were rated highly as both a priority policy target and a priority for research. The highest ranked policy and research priorities include strategies designed to build economic viability in rural communities, improve access to federal food and nutrition assistance programs, improve food retail systems, and increase the personal food production capacity of rural residents. Respondents also prioritized the development of valid and reliable research methodologies to measure variables associated with rural food access. Conclusions This collaborative, trans-disciplinary, participatory process, created a map to guide and prioritize research about polices to improve healthy, affordable food access in rural communities

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR &lt; 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.</p

Effects of Intermittent IL-2 Alone or with Peri-Cycle Antiretroviral Therapy in Early HIV Infection: The STALWART Study

The Study of Aldesleukin with and without antiretroviral therapy (STALWART) evaluated whether intermittent interleukin-2 (IL-2) alone or with antiretroviral therapy (ART) around IL-2 cycles increased CD4+ counts compared to no therapy

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants’ demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LME INT), (2) LME that models both site-specific random intercepts and age-related random slopes (LME INT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2–81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3–85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ 2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ 2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ 2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects