Offshore wind farms are widely adopted by coastal countries to obtain clean and green energy; their environmental impact has gained an increasing amount of attention. Although offshore wind farm datasets are commercially available via energy industries, records of the exact spatial distribution of individual wind turbines and their construction trajectories are rather incomplete, especially at the global level. Here, we construct a global remote sensing-based offshore wind turbine (OWT) database derived from Sentinel-1 synthetic aperture radar (SAR) time-series images from 2015 to 2019. We developed a percentile-based yearly SAR image collection reduction and autoadaptive threshold algorithm in the Google Earth Engine platform to identify the spatiotemporal distribution of global OWTs. By 2019, 6,924 wind turbines were constructed in 14 coastal nations. An algorithm performance analysis and validation were performed, and the extraction accuracies exceeded 99% using an independent validation dataset. This dataset could further our understanding of the environmental impact of OWTs and support effective marine spatial planning for sustainable development.

A large number of highly pathogenic avian influenza (HPAI) H5N1 outbreaks in poultry and wild birds have been reported in Europe since 2005. Distinct spatial patterns in poultry and wild birds suggest that different environmental drivers and potentially different spread mechanisms are operating. However, previous studies found no difference between these two outbreak types when only the effect of physical environmental factors was analysed. The influence of physical and anthropogenic environmental variables and interactions between the two has only been investigated for wild bird outbreaks. We therefore tested the effect of these environmental factors on HPAI H5N1 outbreaks in poultry, and the potential spread mechanism, and discussed how these differ from those observed in wild birds. Logistic regression analyses were used to quantify the relationship between HPAI H5N1 outbreaks in poultry and environmental factors. Poultry outbreaks increased with an increasing human population density combined with close proximity to lakes or wetlands, increased temperatures and reduced precipitation during the cold season. A risk map was generated based on the identified key factors. In wild birds, outbreaks were strongly associated with an increased Normalized Difference Vegetation Index (NDVI) and lower elevation, though they were similarly affected by climatic conditions as poultry outbreaks. This is the first study that analyses the differences in environmental drivers and spread mechanisms between poultry and wild bird outbreaks. Outbreaks in poultry mostly occurred in areas where the location of farms or trade areas overlapped with habitats for wild birds, whereas outbreaks in wild birds were mainly found in areas where food and shelters are available. The different environmental drivers suggest that different spread mechanisms might be involved: HPAI H5N1 spread to poultry via both poultry and wild birds, whereas contact with wild birds alone seems to drive the outbreaks in wild birds.

Spatio-temporal dynamics of global H5N1 outbreaks match bird migration patterns

Migratory birds rely on a habitat network along their migration routes by temporarily occupying stopover sites between breeding and non‐breeding grounds. Removal or degradation of stopover sites in a network might impede movement and thereby reduce migration success and survival. The extent to which the breakdown of migration networks, due to changes in land use, impacts the population sizes of migratory birds is poorly understood. We measured the functional connectivity of migration networks of waterfowl species that migrate over the East Asian‐Australasian Flyway from 1992 to 2015. We analysed the relationship between changes in non‐breeding population sizes and changes in functional connectivity, while taking into account other commonly considered species traits, using a phylogenetic linear mixed model. We found that population sizes significantly declined with a reduction in the functional connectivity of migration networks; no other variables were important. We conclude that the current decrease in functional connectivity, due to habitat loss and degradation in migration networks, can negatively and crucially impact population sizes of migratory birds. Our findings provide new insights into the underlying mechanisms that affect population trends of migratory birds under environmental changes. Establishment of international agreements leading to the creation of systematic conservation networks associated with migratory species’ distributions and stopover sites may safeguard migratory bird populations.

Land use/land cover change is a continuing research focus, not only because of its ecological and environmental effects but also because of the difficulties with accurate change detection and analysis uncertainty. The principal difficulty is the lack of a long time series of annual global land cover maps at a fine resolution. A new global long-term time series of annual datasets called the European Space Agency (ESA) Climate Change Initiative Land Cover (CCI-LC) has been published, making it possible to detect the global land cover changes. Using this ESA CCI-LC product from 1992–2015, we quantified the annual transitions of land cover change globally with the trajectory analysis method, analyzed the changes patterns and identified the land cover change hotspots. The total land cover change area for the world was 5.99 million km², amounting to only 3.36% of the total continental area. Most changes happened in forest and cropland, accounting 32% of all the land cover changes. Most land cover changes happened in tropical ecoregions. Grassland changes were mainly distributed in the temperate ecoregions, while cropland expansion occurred mainly in the tropical or subtropical ecoregions. The hotspots identified in this paper could provide target areas for further research.