Environmental drivers of seasonal shifts in abundance of wild pigs (Sus scrofa) in a tropical island environment

Four raster datasets are included that were developed using data derived from game camera traps. These data were used as inputs in a species distribution modeling approach using environmental correlates (please find more detailed information in the referenced publication). The resulting raster datasets are a relative abundance index (0 - 100) of feral pigs on Maui using seasonal (Fall and Spring) and combined annual data as well as an averaged ensemble model using seasonal outputs. For those interested in a single model that best represents average pig distribution please use the averaged ensemble model (Maui_pig_ensemble_distribution.tif). *Please note: Additional raster datasets for feral goat (Maui_feralgoats_distribution.tif) and Axis deer (Maui_axisdeer_distribution.tif) distributions are included but are currently unpublished data. Please reach out should you have any questions.Background: Non-native wild pigs (Sus scrofa) threaten sensitive flora and fauna, cost billions of dollars in economic damage, and pose a significant human–wildlife conflict risk. Despite growing interest in wild pig research, basic life history information is often lacking throughout their introduced range and particularly in tropical environments. Similar to other large terrestrial mammals, pigs possess the ability to shift their range based on local climatic conditions or resource availability, further complicating management decisions. The objectives of this study were to (i) model the distribution and abundance of wild pigs across two seasons within a single calendar year; (ii) determine the most important environmental variables driving changes in pig distribution and abundance; and (iii) highlight key differences between seasonal models and their potential management implications. These study objectives were achieved using zero-inflated models constructed from abundance data obtained from extensive field surveys and remotely sensed environmental variables. Results: Our models demonstrate a considerable change in distribution and abundance of wild pigs throughout a single calendar year. Rainfall and vegetation height were among the most influential variables for pig distribution during the spring, and distance to adjacent forest and vegetation density were among the most significant for the fall. Further, our seasonal models show that areas of high conservation value may be more vulnerable to threats from wild pigs at certain times throughout the year, which was not captured by more traditional modeling approaches using aggregated data. Conclusions: Our results suggest that (i) wild pigs can considerably shift their range throughout the calendar year, even in tropical environments; (ii) pigs prefer dense forested areas in the presence of either hunting pressure or an abundance of frugivorous plants, but may shift to adjacent areas in the absence of either of these conditions; and (iii) seasonal models provide valuable biological information that would otherwise be missed by common modeling approaches that use aggregated data over many years. These findings highlight the importance of considering biologically relevant time scales that provide key information to better inform management strategies, particularly for species whose ranges inc

A comparison of abundance and distribution model outputs using camera traps and sign surveys for feral pigs

Two raster datasets are included that were developed using data derived from game camera traps (Oahu_pigcam_distribution.tif) and visual sign surveys (Oahu_pigsign_distribution.tif). These data were used as inputs in a species distribution modeling approach using environmental correlates (please find more detailed information in the referenced publication). The resulting raster datasets are a relative abundance index (0 - 100) of feral pigs on Oʻahu.Species distribution models play a central role in informing wildlife management. For models to be useful, they must be based on data that best represent the presence or abundance of the species. Data used as inputs in the development of these models can be obtained through numerous methods, each subject to different biases and limitations but, to date, few studies have examined whether these biases result in different predictive spatial models, potentially influencing conservation decisions. In this study, we compare distribution model predictions of feral pig (Sus scrofa) relative abundance using the two most common monitoring methods: detections from camera traps and visual surveys of pig sign. These data were collected during the same period using standardised methods at survey sites generated using a random stratified sampling design. We found that although site-level observed sign data were only loosely correlated with observed camera detections (R2 ¼ 0.32–0.45), predicted sign and camera counts from zero-inflated models were well correlated (R2 ¼ 0.78–0.88). In this study we show one example in which fitting two different forms of abundance data using environmental covariates explains most of the variance between datasets. We conclude that, as long as outputs are produced through appropriate modelling techniques, these two common methods of obtaining abundance data may be used interchangeably to produce comparable distribution maps for decision-making purposes. However, for monitoring purposes, sign and camera trap data may not be used interchangeably at the site level

Maunalua Bay Outreach Interactive Map

This project addressed how to disseminate past, present, and future information to a wide array of bay users in the most effective format. We developed an interactive map as a community outreach tool to be embedded within Malama Maunalua’s (MM) website. The map contains spatial information, links to relevant publications, and recreation information including rules, regulations, and “points of interest.” Our final products are intended to share knowledge of the bay leading to a more efficient and effective management of the entire ecosystem. Our products include: a Google data entry form and its guidelines, a database, a presentation, a flyer with links to available resources, and a “Read Me” document. NOTE: The map and its supplementary materials are living documents with a collection of past and current information. Thus, for the most up-to-date materials visit MM’s website

Redox Processes of Manganese Oxide in Catalyzing Oxygen Evolution and Reduction: An

Manganese oxides with rich redox chemistry have been widely used in (electro)catalysis in applications of energy and environmental consequence. While they are ubiquitous in catalyzing the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR), redox processes occurring on the surface of manganese oxides are poorly understood. We report valence changes at OER- and ORR-relevant voltages of a layered manganese oxide film prepared by electrodeposition. X-ray absorption spectra were collected in situ in O[subscript 2]-saturated 0.1 M KOH using inverse partial fluorescence yield (IPFY) at the Mn L[subscript 3,2]-edges and partial fluorescence yield (PFY) at the O K-edge. Overall, we found reversible yet hysteretic Mn redox and qualitatively reproducible spectral changes by Mn L[subscript 3,2]IPFY XAS. Oxidation to a mixed Mn[superscript 3+/4+] valence preceded the oxygen evolution at 1.65 V vs RHE, while manganese reduced below Mn[superscript 3+] and contained tetrahedral Mn[superscript 2+] during oxygen reduction at 0.5 V vs RHE. Analysis of the pre-edge in O K-edge XAS provided the Mn-O hybridization, which was highest for Mn[superscript 3+](e[subscript g][superscript 1]). Our study demonstrates that combined in situ experiments at the metal L- and oxygen K-edges are indispensable to identify both the active valence during catalysis and the hybridization with oxygen adsorbates, critical to the rational design of active catalysts for oxygen electrocatalysis.National Science Foundation (U.S.) (Grant DGE-1122374

Reversibility of Ferri-/Ferrocyanide Redox during Operando Soft X-ray Spectroscopy

The ferri-/ferrocyanide redox couple is ubiquitous in many fields of physical chemistry. We studied its photochemical response to intense synchrotron radiation by in situ X-ray absorption spectroscopy (XAS). For photon flux densities equal to and above 2 × 1011 s–1 mm–2, precipitation of ferric (hydr)oxide from both ferricyanide and ferrocyanide solutions was clearly detectable, despite flowing fast enough to replace the solution in the flow cell every 0.4 s (flow rate 1.5 mL/min). During cyclic voltammetry, precipitation of ferric (hydr)oxide was promoted at reducing voltages and observed below 1011 s–1 mm–2. This was accompanied by inhibition of the ferri-/ferrocyanide redox, which we probed by time-resolved operando XAS. Our study highlights the importance of considering both electrochemical and spectroscopic conditions when designing in situ experiments

Exome sequencing in bipolar disorder identifies AKAP11 as a risk gene shared with schizophrenia

We report results from the Bipolar Exome (BipEx) collaboration analysis of whole-exome sequencing of 13,933 patients with bipolar disorder (BD) matched with 14,422 controls. We find an excess of ultra-rare protein-truncating variants (PTVs) in patients with BD among genes under strong evolutionary constraint in both major BD subtypes. We find enrichment of ultra-rare PTVs within genes implicated from a recent schizophrenia exome meta-analysis (SCHEMA; 24,248 cases and 97,322 controls) and among binding targets of CHD8. Genes implicated from genome-wide association studies (GWASs) of BD, however, are not significantly enriched for ultra-rare PTVs. Combining gene-level results with SCHEMA, AKAP11 emerges as a definitive risk gene (odds ratio (OR) = 7.06, P = 2.83 × 10-9). At the protein level, AKAP-11 interacts with GSK3B, the hypothesized target of lithium, a primary treatment for BD. Our results lend support to BD's polygenicity, demonstrating a role for rare coding variation as a significant risk factor in BD etiology

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death. Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups. To further define the genetic basis of atrial fibrillation, we performed large-scale, trans-ancestry meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillation and 115,142 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,346 cases and 132,086 referents. We identified 12 new genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate the identification of new potential targets for drug discovery