Mechanistic models project bird invasions with accuracy.

Invasive species pose a major threat to biodiversity and inflict massive economic costs. Effective management of bio-invasions depends on reliable predictions of areas at risk of invasion, as they allow early invader detection and rapid responses. Yet, considerable uncertainty remains as to how to predict best potential invasive distribution ranges. Using a set of mainly (sub)tropical birds introduced to Europe, we show that the true extent of the geographical area at risk of invasion can accurately be determined by using ecophysiological mechanistic models that quantify species' fundamental thermal niches. Potential invasive ranges are primarily constrained by functional traits related to body allometry and body temperature, metabolic rates, and feather insulation. Given their capacity to identify tolerable climates outside of contemporary realized species niches, mechanistic predictions are well suited for informing effective policy and management aimed at preventing the escalating impacts of invasive species.

A checklist recipe: making species data open and FAIR.

Species checklists are a crucial source of information for research and policy. Unfortunately, many traditional species checklists vary wildly in their content, format, availability and maintenance. The fact that these are not open, findable, accessible, interoperable and reusable (FAIR) severely hampers fast and efficient information flow to policy and decision-making that are required to tackle the current biodiversity crisis. Here, we propose a reproducible, semi-automated workflow to transform traditional checklist data into a FAIR and open species registry. We showcase our workflow by applying it to the publication of the Manual of Alien Plants, a species checklist specifically developed for the Tracking Invasive Alien Species (TrIAS) project. Our approach combines source data management, reproducible data transformation to Darwin Core using R, version control, data documentation and publication to the Global Biodiversity Information Facility (GBIF). This checklist publication workflow is openly available for data holders and applicable to species registries varying in thematic, taxonomic or geographical scope and could serve as an important tool to open up research and strengthen environmental decision-making.

Associations between types of greenery along neighborhood roads and weight status in different climates.

Obesity is a major international health concern. Neighborhood greenery has been identified as a critical factor for promoting health in urban areas, due in part to its apparent role in facilitating healthy weight by promoting physical activity. However, studies have used diverse greenery measures and spatial analysis units to ascertain this relationship. This study examined associations between street greenery and weight status at the residential address level across 500 to 2000m buffers in two climatically distinct communities, Phoenix, AZ, and Portland, OR. Greenery was measured using one-meter landcover data. Street greenery measures were designed to quantify the pedestrian environment along a gradient of suitability for promoting physical exercise. Weight status was defined by body mass index (BMI) calculated from weight and height information on driver's license records. BMI values were dichotomized at 25 into overweight or obese vs. neither. Approximately 500,000 BMI values in Phoenix and 225,000 in Portland were modelled by community using logistic regression. Street tree cover was consistently protective for healthy weight status across all buffer sizes after adjusting for potential confounders. Herbaceous street cover showed protective associations in Phoenix but harmful associations in Portland. Every 10% increase in street tree cover within 2000m was associated with 18% lower odds of being overweight or obese (adjusted odds ratio [AOR]: 0.82, 95% CI: 0.81 - 0.84 in Phoenix; 0.82, 95% CI: 0.81 - 0.83 in Portland). When compared to residents with less than 10% street tree cover within 2000m, those with greater than 10% tree cover had at least 13% (AOR for Portland: 0.87, 95% CI: 0.81 - 0.92) lower odds of being overweight or obese. Findings support the importance of urban street trees in very different climates for facilitating healthy weight status. They can inform greenery management to prioritize vegetation type and allocation decisions in limited urban spaces.

Assessing threats of non-native species to native freshwater biodiversity: Conservation priorities for the United States.

Non-native species pose one of the greatest threats to native biodiversity, and can have severe negative impacts in freshwater ecosystems. Identifying regions of spatial overlap between high freshwater biodiversity and high invasion pressure may thus better inform the prioritization of freshwater conservation efforts. We employ geospatial analysis of species distribution data to investigate the potential threat of non-native species to aquatic animal taxa across the continental United States. We mapped non-native aquatic plant and animal species richness and cumulative invasion pressure to estimate overall negative impact associated with species introductions. These distributions were compared to distributions of native aquatic animal taxa derived from the International Union for the Conservation of Nature (IUCN) database. To identify hotspots of native biodiversity we mapped total species richness, number of threatened and endangered species, and a community index of species rarity calculated at the watershed scale. An overall priority index allowed identification of watersheds experiencing high pressure from non-native species and also exhibiting high native biodiversity conservation value. While priority regions are roughly consistent with previously reported prioritization maps for the US, we also recognize novel priority areas characterized by moderate-to-high native diversity but extremely high invasion pressure. We further compared priority areas with existing conservation protections as well as projected future threats associated with land use change. Our findings suggest that many regions of elevated freshwater biodiversity value are compromised by high invasion pressure, and are poorly safeguarded by existing conservation mechanisms and are likely to experience significant additional stresses in the future.

Trends in nonindigenous aquatic species richness in the United States reveal shifting spatial and temporal patterns of species introductions.

Understanding the spatial and temporal dynamics underlying the introduction and spread of nonindigenous aquatic species (NAS) can provide important insights into the historical drivers of biological invasions and aid in forecasting future patterns of nonindigenous species arrival and spread. Increasingly, public databases of species observation records are being used to quantify changes in NAS distributions across space and time, and are becoming an important resource for researchers, managers, and policy-makers. Here we use publicly available data to describe trends in NAS introduction and spread across the conterminous United States over more than two centuries of observation records. Available data on first records of NAS reveal significant shifts in dominance of particular introduction patterns over time, both in terms of recipient regions and likely sources. These spatiotemporal trends at the continental scale may be subject to biases associated with regional variation in sampling effort, reporting, and data curation. We therefore also examined two additional metrics, the number of individual records and the spatial coverage of those records, which are likely to be more closely associated with sampling effort. Our results suggest that broad-scale patterns may mask considerable variation across regions, time periods, and even entities contributing to NAS sampling. In some cases, observed temporal shifts in species discovery may be influenced by dramatic fluctuations in the number and spatial extent of individual observations, reflecting the possibility that shifts in sampling effort may obscure underlying rates of NAS introduction.