Globally, the knowledge of insect distributions is largely insufficient, and that hinders conservation actions against biodiversity loss. Focusing on butterfly diversity, we aimed to fill knowledge gaps and provide new insights into biodiversity conservation in China.
China.
Occurrence records from 1950 to 2023.
Butterflies, Lepidoptera.
We collected butterfly occurrence records from published literature, online databases and our butterfly specimens, and then used either species distribution models or expansion from actual occurrence sites to estimate species distribution ranges in China. We identified key environmental variables that are related to butterfly biodiversity patterns, and delineated priority conservation areas based on butterfly distributions.
We report the first country-wide inventory and mapping of China's 1920 butterfly species. The identified hotspots of species richness are distributed mainly in southwestern, southern and southeastern China. Among variables strongly correlated with species richness, the most important one is actual evapotranspiration. Conservation priority areas under the Convention on Biological Diversity 17% area target overlapped well with the hotspots, but only 29.8% of them are covered by existing nature reserves. When that protection target increases to 30%, the additional areas are located mainly in southern China, with its large cities and intensive agriculture.
We find that some protected butterfly species have a larger area of habitat than most species, implying that the list of protected butterflies in China should be revised. Urban and farmland landscapes may help sustain butterfly diversity and they should be considered in conservation planning.
Information on species' population trends is essential to assess species' conservation status, make informed environmental decisions and ultimately reduce biodiversity loss. Robust population trends require a long-term monitoring programme, often using citizen scientists, that ideally generates representative and unbiased data from the study area. Here we present the dataset of the Breeding Bird Survey, the main scheme for monitoring the population changes of common and widespread breeding birds in the United Kingdom, which achieves this through a randomised sampling scheme and defined field methodology. We also describe the modelling approach used to calculate the population trends, which are the main output of the survey.
The main published dataset contains 7,070,577 records detailing counts of 217 bird species in 7010 grid cells over 30 years. Data for 78 species that are currently regarded as too sensitive to be released at fine resolution are omitted. As an illustration of the main use of this dataset, we provide population change estimates for 119 bird species.
Grid squares (1 × 1 km) are randomly selected using a stratified sampling scheme throughout the United Kingdom, Isle of Man and Channel Islands. Data in a grid square are collected along two 1-km-long transects which are subdivided into 200-m-long sections.
Data have been collected every year since 1994, with two major disruptions in 2001 and 2020, when people's movements were nationally restricted. Grid squares are surveyed twice a year during the main breeding season (April to June). Here we present the data collected from 1994 to 2023.
Bird species.
Data are supplied as comma-separated text files.
Arbuscular mycorrhizas (AM) and ectomycorrhizas (ECM) have different impacts on nutrient cycling, carbon storage, community dynamics and enhancement of photosynthesis by rising CO2. Recent global analyses have concluded that patterns of AM/ECM dominance in forests worldwide are shaped by climate, with soil nutrients contributing negligible additional explanatory power. However, their reliance on nutrient data from GIS surfaces masks important local influences of parent material, topography and soil age on soil nutrient status. We asked if use of site-specific nutrient data reveals a more important role for nutrients.
Present day.
Global dataset comprising 703 sites, encompassing forests, savanna/woodlands, shrublands and deserts on all continents except Antarctica.
Arborescent plants, including angiosperms, gymnosperms and tree ferns.
Generalised Additive Models for Location, Scale and Shape (GAMLSS) to determine the effects of climate variables, soil nitrogen and soil phosphorus on the proportional representation of ECM and of non-mycorrhizal species (NM) in woody vegetation.
GAMLSS showed a strong negative relationship of ECM representation with mean annual temperature (MAT), and a strong negative relationship with soil total nitrogen. NM representation was highest on dry sites and phosphorus-poor sites. Reanalysis showed that GIS-derived soil nutrient data had less explanatory power than site-specific nutrient data, and resulted in poorer model fits.
Our results support the long-held belief that soil nutrients as well as climate influence the relative fitness of different mycorrhizal syndromes worldwide, and demonstrate the value of using site-specific nutrient data. Soil nutrients should be considered when predicting the impact of climate change on the mycorrhizal composition of vegetation and resulting shifts in ecosystem processes.
The goal of this work was to investigate whether the community of avian nest predators shifts from nocturnal to diurnal with changes in latitude. This hypothesis was formulated 70 years ago, under the rationale that longer day length during the bird breeding season at high latitudes increases opportunities for visual predators. Based on other studies investigating the identity of nest predators, we also considered variation in the habitat and nest height.
Global.
1994–2020.
Birds and their nest predators.
We reviewed studies that report the results of nest monitoring by video or photograph camera and collected data on the identity of nest predators. We then used the activity pattern of the predator species as a proxy to estimate whether predation events were nocturnal or diurnal. We used multivariate logistic and ordinal regressions to investigate whether the probability that nest predators are nocturnal changes with latitude and habitat.
We found that both habitat and latitude explain variation in the circadian type of nest predators. In open habitats, nest predation was more often due to diurnal predators at high latitudes and nocturnal predators near the equator. In forests, on the other hand, nocturnal predator activity patterns were more common closer to the poles.
Using meta-analytical methods, we show that predator activity varies across habitats and latitude leading to markedly different consequences of predation for prey. These findings suggest that small-scale environmental factors such as habitat type can strongly affect and even neutralise larger-scale, ecological patterns. We speculate that day length might act along with other biotic and abiotic factors to shape the timing of nest predation in birds.
SPECTRE is an open-source database containing standardised spatial data on global environmental and anthropogenic variables that are potential threats to terrestrial species and ecosystems. Its goal is to allow users to swiftly access spatial data on multiple threats at a resolution of 30-arc seconds for all terrestrial areas. Following the standard set by Worldclim, these data allow full comparability and ease of use under common statistical frameworks for global change studies, species distribution modelling, threat assessments, quantification of ecosystem services and disturbance, among multiple other uses. A web user interface, a persistent online repository and an accompanying R package with functions for downloading and manipulating data are provided.
SPECTRE is a GIS product, currently with 21 geoTiff raster layers with an approximate 1 × 1 km resolution.
Global (longitude −180–180, latitude −60–90) terrestrial database with a resolution of 30-arc seconds (approximately 1 × 1 km at the equator), converted from global sources of different original spatial grain, from 0.03 × 0.03to 10 × 10 km.
The known time period for all sources present in SPECTRE varies from 1976 to 2020 (all but three after 1990), with a minimum temporal grain of 1 year.
Non-taxa-specific.
geoTiff and R.
The influences of environmental and spatial processes on species composition have been at the center of metacommunity ecology. Conversely, the relative importance of these processes for species co-occurrences and taxonomic similarity has remained poorly understood. We hypothesised that at a subcontinental scale, shared environmental preference would be the major driver of co-occurrences across species groups. In contrast, co-occurrences due to shared dispersal history were more likely in dispersal-limited taxa. Finally, we tested whether taxa co-occurring due to similar responses to environmental and spatial processes were more taxonomically similar than expected by chance.
The conterminous United States.
1993–2019.
Stream diatoms, insects and fish.
We generated co-occurrence networks and developed methodology to determine the proportions of nodes and edges explained by pure environment alone (after accounting for space), pure space alone (after accounting for the environment), pure environment and pure space together, and spatially structured environment. Taxonomic similarity of taxa co-occurring because of environmental and/or spatial controls or because of unmeasured processes was compared to that of a null model.
Pure environment alone, spatially structured environment, and pure environment and pure space together explained the greatest proportion of nodes and edges in the co-occurrence networks of diatom species and genera, and insect genera. Conversely, pure environment and pure space together best explained the nodes and edges in the co-occurrence network of fish species and genera. Co-occurring taxa were more closely related than the random expectation in all comparisons.
The environment controlled co-occurrences in all groups, while the influence of space was the strongest in fish, the most dispersal-limited group in our study. All co-occurring taxa were more taxonomically related than expected by chance due to environmental or spatial overlap or unaccounted factors.
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