Antibiotic resistance genes (ARGs) have accelerated microbial threats to human health in the last decade. Many genes can confer resistance, but evaluating the relative health risks of ARGs is ...complex. Factors such as the abundance, propensity for lateral transmission and ability of ARGs to be expressed in pathogens are all important. Here, an analysis at the metagenomic level from various habitats (6 types of habitats, 4572 samples) detects 2561 ARGs that collectively conferred resistance to 24 classes of antibiotics. We quantitatively evaluate the health risk to humans, defined as the risk that ARGs will confound the clinical treatment for pathogens, of these 2561 ARGs by integrating human accessibility, mobility, pathogenicity and clinical availability. Our results demonstrate that 23.78% of the ARGs pose a health risk, especially those which confer multidrug resistance. We also calculate the antibiotic resistance risks of all samples in four main habitats, and with machine learning, successfully map the antibiotic resistance threats in global marine habitats with over 75% accuracy. Our novel method for quantitatively surveilling the health risk of ARGs will help to manage one of the most important threats to human and animal health.
In the light of the “Biological Diversity” concept, habitats are cardinal pieces for biodiversity quantitative estimation at a local and global scale. In Europe EUNIS (European Nature Information ...System) is a system tool for habitat identification and assessment. Earth Observation (EO) data, which are acquired by satellite sensors, offer new opportunities for environmental sciences and they are revolutionizing the methodologies applied. These are providing unprecedented insights for habitat monitoring and for evaluating the Sustainable Development Goals (SDGs) indicators. This paper shows the results of a novel approach for a spatially explicit habitat mapping in Italy at a national scale, using a supervised machine learning model (SMLM), through the combination of vegetation plot database (as response variable), and both spectral and environmental predictors. The procedure integrates forest habitat data in Italy from the European Vegetation Archive (EVA), with Sentinel-2 imagery processing (vegetation indices time series, spectral indices, and single bands spectral signals) and environmental data variables (i.e., climatic and topographic), to parameterize a Random Forests (RF) classifier. The obtained results classify 24 forest habitats according to the EUNIS III level: 12 broadleaved deciduous (T1), 4 broadleaved evergreen (T2) and eight needleleaved forest habitats (T3), and achieved an overall accuracy of 87% at the EUNIS II level classes (T1, T2, T3), and an overall accuracy of 76.14% at the EUNIS III level. The highest overall accuracy value was obtained for the broadleaved evergreen forest equal to 91%, followed by 76% and 68% for needleleaved and broadleaved deciduous habitat forests, respectively. The results of the proposed methodology open the way to increase the EUNIS habitat categories to be mapped together with their geographical extent, and to test different semi-supervised machine learning algorithms and ensemble modelling methods.
Intertidal habitats (i.e. marine habitats that are (partially) exposed during low tide) have traditionally been studied from a shorebird‐centred perspective. We show that these habitats are ...accessible and important to marine predators such as elasmobranchs (i.e. sharks and rays). Our synthesis shows that at least 43 shark and 45 ray species, of which 54.5% are currently threatened, use intertidal habitats. Elasmobranchs use intertidal habitats mostly for feeding and as refugia, but also for parturition and thermoregulation. However, the motivation of intertidal habitat use remains unclear due to limitations to observe elasmobranch behaviour in these dynamic habitats. We argue that elasmobranch predators can play an important role in intertidal food webs by feeding on shared resources during high tide (i.e. ‘high‐tide predators’), which are accessible and also consumed by terrestrial or avian predators during low tide (i.e. ‘low‐tide predators’). In addition, elasmobranchs are able to change the bio‐geomorphology of intertidal habitats by increasing habitat heterogeneity due to feeding activities and may also alter resource availability for other consumers. We discuss how the ecological role of elasmobranchs in intertidal habitats is being affected by the continued overexploitation of these species, and conversely, how the global loss of intertidal areas poses an additional threat to an already vulnerable taxonomic group. We conclude that studies on intertidal ecology should include both low‐tide (e.g. shorebirds) and high‐tide (e.g. elasmobranchs) predatory guilds and their ecological interactions. The global loss of elasmobranch predatory species and intertidal habitat provides additional compelling arguments for the conservation of these areas.
•Traditional low-intensity land use favours Orthoptera diversity and abundance.•Orthoptera diversity and abundance peak in young grassland fallows.•Habitat heterogeneity increases Orthoptera ...diversity in calcareous grasslands.•Habitat connectivity is less important for Orthoptera diversity.•Conservation should focus on improving habitat heterogeneity and habitat quality.
Due to the transition from traditional land use to modern agriculture throughout Europe, semi-natural grasslands are subject to severe environmental changes. Both agricultural intensification and abandonment have caused degradation, loss and fragmentation of semi-natural grasslands with adverse effects on biodiversity.
We analysed the effects of landscape and habitat quality on Orthoptera in pre-alpine calcareous grasslands of the Northern Limestone Alps. At the landscape level, we focused on the effects of functional connectivity, patch size and habitat heterogeneity on Orthoptera species richness of 13 randomly selected grassland patches. At the habitat level, we studied the effects of land use on vegetation structure and microclimate as well as on Orthoptera species richness and abundance on 50 randomly chosen plots within these patches.
At the landscape level, the number of Orthoptera species in well-connected pre-alpine calcareous grasslands increased with habitat heterogeneity, which was inter-related with patch size. Functional connectivity, however, had no effect on species richness. At the habitat level, species richness and abundance of Orthoptera were driven by land use together with vegetation structure and microclimate. In general, the explanatory power of our abundance models was at least twice as high as those of the species richness models. Based on the results of our study, conservation management of grassland Orthoptera should primarily focus on improving habitat heterogeneity and habitat quality within patches.
The family of orchids involves a number of critically endangered species. Understanding of drivers of their landscape distribution could provide a valuable insight into their decline. Our objectives ...were to develop models predicting distribution of selected orchid species—four co-occurring forest orchid species, Cephalanthera rubra, Epipactis atrorubens, E. helleborine, and Neottia nidus-avis—at a landscape scale using a wide range of habitat characteristics. Subsequently, we compared the model predictions with species occurrence and the results of the field germination experiment while considering two germination stages—asymbiotic (early stage) and symbiotic. And finally, we attempted to identify possible drivers of species’ landscape distribution (i.e., dispersal, availability of habitat patches, or fungal associates). We have discovered that different habitat characteristics determined the distribution of different orchids. The species also differed in terms of availability of suitable habitat patches and patch occupancy (the highest being E. atrorubens with 80%). Landscape distribution of the species was primarily restricted by the availability of fungal associates (the most important factor for C. rubra) and by the availability of suitable habitat patches (the most important in case of N. nidus-avis). Despite expected easy dispersal of spores, orchid distribution seems to be limited by the availability of fungal associates in the landscape. In contrast, the availability of orchid seeds does not seem to limit their distribution. These results can provide useful guidelines for conservation of the studied species.
Habitat loss and fragmentation have drastically altered the availability and quality of tropical forest habitats, but information on how such changes influence local biodiversity is still ...insufficient. Here, we examine the effects of both patch and landscape metrics on fruit-feeding butterfly assemblages in a fragmented landscape of the Brazilian Atlantic Forest. Our study was carried out in three habitat types: eight fragments (ranging from 8 to 126 ha), eight areas of forest edge (50 m from forest border), and eight areas of forest interior (>200 m from forest border) of the largest remnant (3500 ha) of the Atlantic Forest of northeast Brazil. Our results demonstrated that fragment area is negatively correlated with observed and estimated richness and abundance of butterflies, whereas habitat type is correlated with estimated richness and abundance of butterflies. Species composition responded to habitat type, fragment area, and distance between sample units. These findings illustrated (i) fruit-feeding butterfly sensitivity to habitat loss and fragmentation, (ii) that species composition and abundance are adequate parameters to access the responses of fruit-feeding butterflies to habitat loss and fragmentation, and (iii) the relevance of a heterogeneous and connected landscape for conservation of butterflies, where small fragments are important for generalist or open-habitat specialists and large remnants are key for disturbance-sensitive and threatened taxa.
Projections of polar bear (Ursus maritimus) sea ice habitat distribution in the polar basin during the 21st century were developed to understand the consequences of anticipated sea ice reductions on ...polar bear populations. We used location data from satellite-collared polar bears and environmental data (e.g., bathymetry, distance to coastlines, and sea ice) collected from 1985 to 1995 to build resource selection functions (RSFs). RSFs described habitats that polar bears preferred in summer, autumn, winter, and spring. When applied to independent data from 1996 to 2006, the RSFs consistently identified habitats most frequently used by polar bears. We applied the RSFs to monthly maps of 21st-century sea ice concentration projected by 10 general circulation models (GCMs) used in the Intergovernmental Panel of Climate Change Fourth Assessment Report, under the A1B greenhouse gas forcing scenario. Despite variation in their projections, all GCMs indicated habitat losses in the polar basin during the 21st century. Losses in the highest-valued RSF habitat (optimal habitat) were greatest in the southern seas of the polar basin, especially the Chukchi and Barents seas, and least along the Arctic Ocean shores of Banks Island to northern Greenland. Mean loss of optimal polar bear habitat was greatest during summer; from an observed 1.0 million km2 in 1985—1995 (baseline) to a projected multi-model mean of 0.32 million km2 in 2090—2099 (-68% change). Projected winter losses of polar bear habitat were less: from 1.7 million km2 in 1985—1995 to 1.4 million km2 in 2090—2099 (-17% change). Habitat losses based on GCM multi-model means may be conservative; simulated rates of habitat loss during 1985—2006 from many GCMs were less than the actual observed rates of loss. Although a reduction in the total amount of optimal habitat will likely reduce polar bear populations, exact relationships between habitat losses and population demographics remain unknown. Density and energetic effects may become important as polar bears make long-distance annual migrations from traditional winter ranges to remnant high-latitude summer sea ice. These impacts will likely affect specific sex and age groups differently and may ultimately preclude bears from seasonally returning to their traditional ranges.
The Dry Chaco has one of the highest deforestation rates of the world. The chacoan peccary (
Catagonus wagneri
; ChP) is endemic to the forests of this region and faces a high risk of extinction. ...However, we lack sufficient information about this species to develop effective conservation actions. This is the first study to determine the relevance of primary and secondary forest as habitat for the species and to address opportunities for conservation. We used occupancy modelling to study habitat selection. Using additional information on the species and the region, we then estimated the time left before the ChP’s habitat outside of protected areas is completely lost, and the number of ChP generations likely to exist before this happens. Finally, we identified protected areas that can sustain viable populations, and estimated the number of individuals that can survive within them. We found that the ChP occupies both primary forests and secondary forests. Also, that if deforestation rates remain consistent, the habitat for the ChP outside protected areas will have disappeared before 2051 (< 6 peccary generations). Furthermore, we found that most protected areas are too small and isolated to sustain viable populations. Our results have great management implications. Well-managed forests may allow the conservation of the ChP. Initiatives focused on forest conservation should increase, alongside the restoration of degraded and deforested areas. We also recommend the creation of new protected areas and wildlife corridors, and working horizontally with local communities.
Discerning the foraging habitat requirements of wildlife is key to providing for their conservation and management, especially with rare species. Sea turtles are slow-growing, late-maturing species ...that undertake wide-ranging migrations, making them especially susceptible to changes and disruptions in their environment. To protect and successfully manage these imperiled populations, an understanding of their spatial ecology is required; thus, characterizing critical habitats, identifying high-density areas, and identifying foraging regions is essential. We captured 30 loggerhead sea turtles Caretta caretta (male and female; juvenile and adult) in the estuarine waters of North Carolina (USA) and tracked them in western North Atlantic neritic (nearshore and offshore) waters. Using a combination of satellite telemetry and spatial modeling techniques, we characterized their movements and identified foraging and overwintering sites. Average core-use areas in the north had greater net primary production (NPP) and were smaller than those in the south, indicating more abundant marine resources in northern foraging regions. In summer, loggerheads migrated to both northern and southern foraging grounds, but most (53%) resided within North Carolina neritic waters. Likewise, the majority of loggerheads (67%) we tracked in winter remained in North Carolina neritic waters, underscoring the importance of this area as year-round foraging habitat, and lending to its consideration as potential critical habitat for both juvenile and adult loggerheads. The change to foraging behavior mode was significantly influenced by day of the year, geographic location, and NPP; however, individual-specific factors influenced switching probabilities relative to other covariates. Data highlighting ‘hotspots’ or densely used areas by foraging sea turtles can thus be used by conservation managers to make informed decisions concerning sea turtle conservation measures.
PDF
