Mikhail Menzbier

Understanding the status and abundance of species is essential for effective conservation decision-making. However, the availability of species data varies across space, taxonomic groups and data types. A case study was therefore conducted in a high biodiversity region—East Africa—to evaluate data biases, the factors influencing data availability, and the consequences for conservation. In each of the eleven target countries, priority animal species were identified as threatened species that are protected by national governments, international conventions or conservation NGOs. We assessed data gaps and biases in the IUCN Red List of Threatened Species, the Global Biodiversity Information Facility and the Living Planet Index. A survey of practitioners and decision makers was conducted to confirm and assess consequences of these biases on biodiversity conservation efforts. Our results showed data on species occurrence and population trends were available for a significantly higher proportion of vertebrates than invertebrates. We observed a geographical bias, with higher tourism income countries having more priority species and more species with data than lower tourism income countries. Conservationists surveyed felt that, of the 40 types of data investigated, those data that are most important to conservation projects are the most difficult to access. The main challenges to data accessibility are excessive expense, technological challenges, and a lack of resources to process and analyse data. With this information, practitioners and decision makers can prioritise how and where to fill gaps to improve data availability and use, and ensure biodiversity monitoring is improved and conservation impacts enhanced.

Previous studies and efforts to prevent and to manage avian influenza (AI) outbreaks have mainly focused on the wintering season. However, outbreaks of AI have been reported in the summer, including the breeding season of waterfowl. Additionally, the spatial distribution of waterfowl can easily change during the annual cycle due to their life‐cycle traits and the presence of both migrants and residents in the population. Thus, we assessed the spatiotemporal variation in AI exposure risk in poultry due to spatial distribution changes in three duck species included in both major residents and wintering migrants in South Korea, the mandarin, mallard, and spot‐billed duck, during wintering (October‐March), breeding (April‐June), and whole annual seasons. To estimate seasonal ecological niche variations among the three duck species, we applied pairwise ecological niche analysis using the Pianka index. Subsequently, seasonal distribution models were projected by overlaying the monthly ranges estimated by the maximum entropy model. Finally, we overlaid each seasonal distribution range onto a poultry distribution map of South Korea. We found that the mandarin had less niche overlap with the mallard and spot‐billed duck during the wintering season than during the breeding season, whereas the mallard had less niche overlap with the mandarin and spot‐billed duck during the breeding season than during the wintering season. Breeding and annual distribution ranges of the mandarin and spot‐billed duck, but not the mallard, were similar or even wider than their wintering ranges. Similarly, the mandarin and spot‐billed duck showed more extensive overlap proportions between poultry and their distributional ranges during both breeding and annual seasons than during wintering season. These results suggest that potential AI exposure in poultry can occur more widely in the summer than in winter, depending on sympatry with the host duck species. Future studies considering their population density and variable pathogenicity of avian influenza are required.

Communities of vertebrates tend to appear together under similar ranges of environmental features. This study explores whether an explicit combination of vertebrates and their contact rates with a tick vector might constitute an indicator of the prevalence of a pathogen in the quest for ticks at the…

Species distribution models (SDM) have been proposed as valuable first screening tools for predicting species responses to new environmental conditions. SDMs are usually conducted at the species level, assuming that species-environment relationships are a species-specific feature that do not evolve …

Southeast Asia has arguably the highest biodiversity loss due to the high deforestation rate and hunting pressure. In the region, 55 species of the family Phasianidae can be found in all available land habitats from lowland plains up to high-elevation mountainous areas. As ground-dwelling birds, the…

During the Quaternary, large climate oscillations impacted the distribution and demography of species globally. Two approaches have played a major role in reconstructing changes through time: Bayesian Skyline Plots (BSPs), which reconstruct population fluctuations based on genetic data, and Species …

The unusually high floral and faunal similarity between the different regions of the Afromontane archipelago has been noted by biogeographers since the late 1800s. A possible explanation for this similarity is the spread of montane habitat into the intervening lowlands during the glacial periods of …

Alpine ecosystems are particularly vulnerable to climate change. For widely distributed alpine specialists, rear-edge populations are disproportionately important; it is expected that climate change will reduce their occupancy ranges due to the loss of suitable habitats and connectivity among them. …

Elevational migration can be defined as roundtrip seasonal movement that involves upward and downward shifts in elevation. These shifts incur physiological challenges that are proportional to the degree of elevational change. Larger shifts in elevation correspond to larger shifts in partial pressure…

Accurate species distribution data across remote and extensive geographic areas are difficult to obtain. Here, we use bioclimatic envelope models to determine climatic constraints on the distribution of the migratory Saker Falcon Falco cherrug to identify areas in data‐deficient regions that may con…