Modeling Spatial Trends in Estimated Species Richness using Breeding Bird Survey Data: A Valuable Tool in Biodiversity Assessment

We used data from the French breeding bird survey to estimate local bird species richness within sampled sites, using capture–recapture models. We investigated the possible effects of habitat structure and composition (landscape fragmentation, habitat cover and diversity) on estimated species richness at a local scale, and used the identified trends to help with modeling species richness at a large spatial scale. We performed geostatistical analyses based on spatial autocorrelation – cokriging models – to interpolate estimated species richness over the entire country, providing an opportunity to predict species-rich areas. We further compared species richness obtained with this method to species and rarity richness obtained using a national atlas of breeding birds. Estimated species richness was higher in species richness hotspots identified by the atlas. Combining informations on rare species from Atlas and species richness estimates from sound sampling based schemes should help with identifying species-rich areas for various taxa and locating biodiversity hotspots to be protected as high conservation value areas, especially in temperate zones where diversity hotspots are likely to match centers of high species richness because of very few centers of true endemicity.     

Raising the bar for the next generation of biological atlases: using existing data to inform the design and implementation of atlas monitoring

Selecting a sampling design to monitor multiple species across a broad geographical region can be a daunting task and often involves tradeoffs between limited resources and the accurate estimation of population abundance and occurrence. Since the 1950s, biological atlases have been implemented in various regions to document the occurrence of plant and animal species. As next‐generation atlases repeat original surveys, investigators often seek to raise the rigour of atlases by incorporating species abundances. We present a repeatable framework that incorporates existing monitoring data, hierarchical modelling and sampling simulations to augment existing atlas occurrence and breeding status maps with a secondary sampling of species abundances. Using existing information on three bird species with varying abundance and detectability, we evaluated several sampling scenarios for the 2nd Wisconsin Breeding Bird Atlas. In general, we found that most sampling schemes produced accurate mean statewide abundance estimates for species with medium to high abundance and detection probability, but estimates varied significantly for species with low abundance and low detection probability. Our approach provided a statewide point‐count sampling design that: provided precise and unbiased abundance estimates for species of varied prevalence and detectability; ensured suitable spatial coverage across the state and its habitats; and reduced spending on total survey costs. Our framework could benefit investigators conducting atlases and other broad‐scale avian surveys that seek to add systematic, multi‐species sampling for estimating density and abundance across broad geographical regions.     

Contribution of rare and common species to richness patterns at local scales

Several studies have recently reported that common species are more important for species richness patterns than rare species. However, most such studies have been based on broad‐scale atlas data. We studied the contribution of different species occupancy, i.e. number of plots occupied, to species richness patterns emerging from species data in 50 by 50 m plots within six 140–200 ha forests in Norway. The study included vascular plants, lichens, bryophytes, and polypore fungi. We addressed the following questions: 1) are common species more correlated with species richness than rare species? 2) How do occupancy classes combine at various levels of species richness? 3) Which occupancy class is best in identifying the overall most species‐rich sites (hotspots) by sampling? The results showed that rare species were better correlated with species richness than common species when the information content was accounted for, that high species richness was associated with a higher proportion of less frequent species, and that the best occupancy class for local hotspot identification was species present in 10–30% of the plots within a forest. We argue that the observed correlations between overall richness and sub‐assembly richness are primarily structured by the combination of the distributions of species richness and species occupancy. Although these distributions result from general ecological processes, they may also be strongly affected by idiosyncratic elements of the individual datasets caused by the specific environmental composition of a study area. Hence, different datasets collected in different areas may lead to different results regarding the relative importance of common versus rare species, and such effects should be expected on both broad and fine spatial scales. Despite these effects, we suggest that infrequent species will tend to be more strongly correlated to species richness at local scales than at broader scales as a result of more right‐skewed species‐occupancy distributions.     

A comparison of estimates of relative abundance from a weakly structured mass‐participation bird atlas survey and a robustly designed monitoring scheme

Estimates of population size are frequently used in conservation. Volunteer‐conducted surveys are often the only source of information available, but their reliability is unclear. We compare data from a weakly structured national bird atlas collected by volunteer surveyors free to choose where and when to visit with data from an independent suite of monitoring surveys that used a stratified sampling design. We focus on the Mount Lofty Ranges, South Australia, a region that has lost most of its native vegetation. Both datasets comprise several thousand 20‐min 2‐ha searches carried out between 1999 and 2007. The atlas dataset reported more species, and covered habitats more comprehensively, but showed greater variability in the temporal and spatial distribution of survey effort. However, after we restricted the atlas dataset to native eucalypt woodlands, reporting rates from the two schemes were very strongly correlated. The structured surveys tended to record more species that are normally detected by call and the unstructured surveys recorded more species using edges and open habitats. Minimum population estimates from the two datasets agreed very well. The strength of concordance depended on whether overflying birds were included, highlighting the importance of distinguishing such records in future surveys. We conclude that appropriate calibration using selected regional surveys, including surveys to estimate absolute densities, can enable volunteer‐collected and weakly structured atlas data to be used to generate robust occupancy and minimum population estimates for many species at a regional scale.     

Using the first European Breeding Bird Atlas for science and perspectives for the new Atlas

Capsule: The first European Bird Census Council (EBCC) Atlas of European Breeding Birds has been widely used in scientific publications.

Aims: To quantify how scientific publications have used data from the first European Bird Census Council (EBCC) Atlas of European Breeding Birds, what the topics of these studies have been, and to identify key aspects in which a second European Breeding Bird Atlas will provide new opportunities for basic and applied science.

Methods: We searched Google Scholar to find papers published in scientific journals that cited the first atlas. We analysed the contents of a random selection of 100 papers citing this atlas and described the way these papers used information from it.

Results: The first atlas has been cited in 3150 scientific publications, and can be regarded as a fundamental reference for studies about birds in Europe. It was extensively used as a key reference for the studied bird species. A substantial number of papers re-analysed atlas data to derive new information on species distribution, ecological traits and population sizes. Distribution and ecology were the most frequent topics of studies referring to the atlas, but this source of information was used in a diverse range of studies. In this context, climate change, impact of agriculture and habitat loss were, by order, the most frequently studied environmental pressures. Constraints in the atlas, such as the poor coverage in the east of Europe, the lack of information on distribution change and the coarse resolution were identified as issues limiting the use of the atlas for some purposes.

Conclusions: This study demonstrates the scientific value of European-wide breeding bird atlases. A second atlas, with its almost complete coverage across Europe, the incorporation of changes in distribution between the two atlases and the inclusion of modelled maps at a resolution of 10?×?10?km will certainly become a key data source and reference for researchers in the near future.     

Climate and landscape explain richness patterns depending on the type of species’ distribution data

Understanding the patterns of species richness and their environmental drivers, remains a central theme in ecological research and especially in the continental scales where many conservation decisions are made. Here, we analyzed the patterns of species richness from amphibians, reptiles and mammals at the EU level. We used two different data sources for each taxon: expert-drawn species range maps, and presence/absence atlases. As environmental drivers, we considered climate and land cover. Land cover is increasingly the focus of research, but there still is no consensus on how to classify land cover to distinct habitat classes, so we analyzed the CORINE land cover data with three different levels of thematic resolution (resolution of classification scheme ˗ less to more detailed). We found that the two types of species richness data explored in this study yielded different richness maps. Although, we expected expert-drawn range based estimates of species richness to exceed those from atlas data (due to the assumption that species are present in all locations throughout their region), we found that in many cases the opposite is true (the extreme case is the reptiles where more than half of the atlas based estimates were greater than the expert-drawn range based estimates). Also, we detected contrasting information on the richness drivers of biodiversity patterns depending on the dataset used. For atlas based richness estimates, landscape attributes played more important role than climate while for expert-drawn range based richness estimates climatic variables were more important (for the ectothermic amphibians and reptiles). Finally we found that the thematic resolution of the land cover classification scheme, also played a role in quantifying the effect of land cover diversity, with more detailed thematic resolution increasing the relative contribution of landscape attributes in predicting species richness.     

Atlas versus range maps: robustness of chorological relationships to distribution data types in European mammals

Aim Chorological relationships describe the patterns of distributional overlap among species. In addition to revealing biogeographical structure, the resulting clusters of species with similar geographical distributions can serve as natural units in conservation planning. Here, we assess the extent to which temporal, methodological and taxonomical differences in the source of species’ distribution data can affect the relationships that are found. Location Western Europe. Methods We used two data sets – the Atlas of European mammals and polygon range maps from the IUCN Global Mammal Assessment – both as presence–absence data for UTM 50 km × 50 km squares. We performed pairwise comparisons among 156 species for each data set to build matrices of the similarity in distribution across species, using both Jaccard’s and Baroni‐Urbani & Buser’s indices. We then compared these similarity matrices (chorological relationships), as well as the species richness and occurrence patterns from the two data sets. Results As expected, range maps increased both the mean prevalence per species and mean species richness per grid cell in comparison to atlas data, reflecting the general view that these data types respectively over‐ and underestimate species occurrence. However, species richness and occurrence patterns in atlas and range map data were positively associated and, most importantly, the chorological relationships underlying the two data sets were highly similar. Main conclusions Despite many methodological, temporal and taxonomical differences between atlas data and range maps, the chorological relationships encountered between species were similar for both data sets. Chorological analyses can thus be robust to the data source used and provide a solid basis for analytical biogeographical studies, even over broad spatial scales.     

Threat spots and environmental determinants of red-listed plant,butterfly and bird species in boreal agricultural environments

The aims of this study were (1) to examine the geographic distribution of red-listed species of agricultural environments and identify their national threat spots (areas with high diversity of threatened species) in Finland and (2) to determine the main environmental variables related to the richness and occurrence patterns of red-listed species. Atlas data of 21 plant, 17 butterfly and 11 bird species recorded using 10 km grid squares were employed in the study. Generalized additive models (GAMs) were constructed separately for species richness and occurrence of individual species of the three species groups using climate and land cover predictor variables. The predictive accuracy of models, as measured using correlation between the observed and predicted values and AUC statistics, was generally good. Temperature-related variables were the most important determinants of species richness and occurrence of all three taxa. In addition, land cover variables had a strong effect on the distribution of species. Plants and butterflies were positively related to the cover of grasslands and birds to small-scale agricultural mosaic as well as to arable land. Spatial coincidence of threat spots of plants, butterflies and birds was limited, which emphasizes the importance of considering the potentially contrasting environmental requirements of different taxa in conservation planning. Further, it is obvious that the maintenance of various non-crop habitats and heterogeneous agricultural landscapes has an essential role in the preservation of red-listed species of boreal rural environments.     

Within‐taxon niche structure: niche conservatism,divergence and predicted effects of climate change

Several studies have observed that taxa below the level of species can vary in the degree to which they differ from one another in the environmental space they occupy. These patterns of within‐species niche variation raise the question of whether these differences should be considered when developing models for predicting the potential effects of climate change on species distributions. We address this question with two divergent datasets, one on sister species and subspecies from the European herpetofauna, the other on subspecies of breeding birds in North America. Atlas and observation data come from the Atlas of Amphibians and Reptiles in Europe and the North American Breeding Bird Survey, respectively. We develop boosted regression tree models of climate–distribution relationships and project the predicted geographic range of each taxon using interpolated weather station data and modeled climate for the year 2080. We find differences between models that distinguish the contributions of subtaxa and those that do not, in terms of prediction of both current and future distributions. In comparison to models that ignore sub‐taxon structure, models that incorporate this structure generally predict larger areas of suitable conditions, consistently perform better, if only marginally, as measured by cross‐validated AUC, and can reveal divergent potential effects of climate change on subtaxa. Differences in niche occupancy and predicted distribution appear between closely related taxa regardless of their phylogenetic distinctness. For these reasons, information on subtaxon membership and phylogeographic structure should be included in modeling exercises when available, in order to identify both the contribution of these units to the niche occupancy of species and the potentially distinct responses of subtaxa to climate change.     

Assessing the Relative Sensitivity of Aquatic Organisms to Divalent Metals and Their Representation in Toxicity Datasets Compared to Natural Aquatic Communities

We compared the composition and richness of acute and chronic toxicity datasets for Cd, Cu, Ni, Pb, and Zn to several natural aquatic communities. The richness of acute datasets was reasonably representative, with the largest toxicity datasets containing a higher number of genera than some natural aquatic communities. Acute datasets also had a reasonably diverse composition compared to natural aquatic communities, although insects were under-represented and cladocerans over-represented. Given this robustness, we suggest manipulation of large acute datasets (Cd, Cu, Zn) to account for site-specific differences in aquatic community composition can be accomplished with confidence and that this will not result in under-protection of sensitive taxa. In contrast, the chronic datasets were not representative of natural aquatic communities in terms of composition or richness. Chronic dataset richness is an order of magnitude less than natural aquatic communities. Chronic datasets have minimal representation of insects, whereas cladocera and salmonids are grossly over-represented in some cases. Further, no real patterns in the relative sensitivity of genera groups can be discerned with such limited data. As a result, we conclude there is considerable uncertainty regarding how biases in genera representation may lead to under- or over-protection of aquatic communities on a chronic basis. Given this, manipulation of chronic datasets to better reflect site-specific aquatic communities is not recommended without additional chronic testing using a wider diversity of aquatic genera.     

Climate and the range dynamics of species with imperfect detection

Reliable predictions for species range changes require a mechanistic understanding of range dynamics in relation to environmental variation. One obstacle is that most current models are static and confound occurrence with the probability of detecting a species if it occurs at a site. Here we draw attention to recently developed occupancy models, which can be used to examine colonization and local extinction or changes in occupancy over time. These models further account for detection probabilities, which are likely to vary spatially and temporally in many datasets. Occupancy models require repeated presence/absence surveys, for example checklists used in bird atlas projects. As an example, we examine the recent range expansion of hadeda ibises (Bostrychia hagedash) in South African protected areas. Colonization exceeded local extinction in most biomes, and the probability of occurrence was related to local climate. Extensions of the basic occupancy models can estimate abundance or species richness. Occupancy models are an appealing additional tool for studying species' responses to global change.     

Assessing the impacts of imperfect detection on estimates of diversity and community structure through multispecies occupancy modeling

Detecting all species in a given survey is challenging, regardless of sampling effort. This issue, more commonly known as imperfect detection, can have negative impacts on data quality and interpretation, most notably leading to false absences for rare or difficult‐to‐detect species. It is important that this issue be addressed, as estimates of species richness are critical to many areas of ecological research and management. In this study, we set out to determine the impacts of imperfect detection, and decisions about thresholds for inclusion in occupancy, on estimates of species richness and community structure. We collected data from a stream fish assemblage in Algonquin Provincial Park to be used as a representation of ecological communities. We then used multispecies occupancy modeling to estimate species‐specific occurrence probabilities while accounting for imperfect detection, thus creating a more informed dataset. This dataset was then compared to the original to see where differences occurred. In our analyses, we demonstrated that imperfect detection can lead to large changes in estimates of species richness at the site level and summarized differences in the community structure and sampling locations, represented through correspondence analyses.     

Effort d’échantillonnage et atlas floristiques – exhaustivité des mailles et caractérisation des lacunes dans la connaissance

Floristic atlases have an important input to flora conservation planning even though their data quality varied greatly across countries. This study aimed to assess survey completeness of cells of floristic atlases. Then, a surveying guide is designed to overcome as efficiently as possible sampling biases. A review and analyses on a wide dataset were carried out to select an estimator of the true species richness of surveyed cells. The Jackknife 1, a non-parametric estimator, appeared as the best compromise for regional floristic atlases. The number of records in each cell was used as an estimator of sampling effort. The ratio between the observed species richness and the estimated species richness measures the completeness of inventories in each surveyed cell. Eighteen variables were selected to describe current inventories and design new surveys. These variables highlight locations, periods and species to be given priority in future studies.     

A random process may control the number of endemic species

The richness of endemic species is often recognized as an indication of the distinctiveness of certain local faunas and is used for the definition of conservation hotspots as well. Faunas of different animal taxa were considered in sets of contiguous geographical units. Comparing the faunas of different units in one set, we found an exponential increase in the number of endemics when plotted against the number of non-endemics. A model of independent stochastic population dynamics under the control of environmental oscillations produces random fluctuations in the ranges of species. Ranges of endemic species are supposedly narrower than ranges of co-occurring non-endemic species. In such a case, the flow of a random process leads to an exponential relationship between numbers of co-occurring endemic and non-endemic species. This process also produces an apparent positive correlation between total species number and the percentage of endemics.     

Temporally robust occupancy frequency distributions in riverine metacommunities explained by local biodiversity regulation

Aim

The mechanisms determining the distribution of the number of sites species occupy, the occupancy frequency distribution (OFD), remain incompletely understood despite decades of research. To explore the dominant mechanisms responsible for the shape and temporal dynamics of empirical OFD, we develop a simple patch occupancy framework with intrinsically regulated local richness and fit the model to a highly replicated dataset describing macroinvertebrate, macrophyte and diatom occupancy.

Location

England.

Time period

Up to $30$ years between 1990 and 2020.

Major taxa studied

Macroinvertebrates, macrophytes and diatoms.

Methods

We study the OFD in a highly replicated dataset of freshwater metacommunities in England across time. We consider temporal change in species richness, composition, and in the shape of the OFD. Goodness-of-fit of the steady state of a simple patch occupancy model—which predicts a log-series OFD—to the empirical observations is assessed. Additionally, we test the capacity of the model to predict metacommunity-scale processes.

Results

Our model provides a consistently good fit to empirical OFDs. It can additionally be used to predict metacommunity-scale species turnover.

Main conclusions

Our results support the view that metacommunity structure reflects a dynamic steady state controlled by local limits to coexistence.     

Observed and dark diversity of alien plant species in Europe: estimating future invasion risk

Invasion by alien species is a growing concern for nature conservation. We estimated the level of invasion by alien plant species and future invasion risks at the European scale. We used a pan-European atlas and eight regional plant atlases to determine the distribution of alien and native plant richness. In addition, we estimated alien and native dark diversity (species currently absent from a site but present in the surrounding region and able to colonize the site). We used relative diversity metrics to indicate current and future risks by alien species: relative alien richness (compared to native species), alien and native completeness (log-ratio of observed to dark diversity) and completeness difference between alien and native species. Observed and relative richness of alien species were greatest in NW Europe; this suggests that sites in NW Europe could be more disturbed. Observed alien and native species richness show clear regional hotspots; the distribution of completeness values is dispersed, indicating local hotspots. Northern Europe has relatively lower alien completeness, likely because potential invaders inhabit the region but have not yet reached many localities, thereby suggesting a risk of future invasion. A greater number of potential alien species in the region increases the probability that some alien species could have detrimental impacts. Both alien richness and completeness are positively correlated with native richness and completeness, respectively, indicating that both groups share similar distribution patterns. Alien species diversity metrics in Europe are related positively to human population density and agricultural land-use. We suggest that the dark diversity concept can broaden our understanding of alien species diversity and future invasion risks.     

A consistent occupancy–climate relationship across birds and mammals of the Americas

At broad spatial scales, species richness is strongly related to climate. Yet, few ecological studies attempt to identify regularities in the individual species distributions that make up this pattern. Models used to describe species distributions typically model very complex responses to climate. Here, we test whether the variability in the distributions of birds and mammals of the Americas relates to mean annual temperature and precipitation in a simple, consistent way. Specifically, we test if simple mathematical models can predict, as a first approximation, the geographical variation in individual species’ probability of occupancy for 3277 non‐migratory bird and 1659 mammal species. We find a Gaussian model, where the probability of occupancy of a 10⁴ km² quadrat decreases symmetrically and gradually around a species ‘optimal’ temperature and precipitation, was generally the best model, explaining an average of 35% of the deviance in probability of occupancy. The inclusion of additional terms had very small and idiosyncratic effects across species. The Gaussian occupancy–climate relationship appears general among species and taxa and explains nearly as much deviance as complex models including many more parameters. Therefore, we propose that hypotheses aiming to explain the broad‐scale distribution of species or species richness must also predict generally Gaussian occupancy–climate relationships. Synthesis Science aims to identify regularities in a complex natural world. General patterns should be identified before one searches for potential mechanisms and contingencies. However, species geographic distributions are often modelled as complex (sometimes black box), species‐specific, functions of their environment. We asked whether a simple model could account for as much of the geographic variation in a species' probability of occupancy, and be widely applicable across thousands of species. As a first approximation, we found that a simple Gaussian occupancy‐climate relationship is very common in Nature, whether it be causal or not.     

Species-specific features affect the ability of census-derived models to map winter avian distribution

We identify autoecological traits of bird species that influence the accuracy of predictive models of species distribution based on census data obtained from stratified sampling. These models would serve as a complementary approach to the development of regional bird atlases. We model the winter bird abundance of 64 terrestrial bird species in 77 census plots in Central Spain (Madrid province), using regression tree analyses. The predicted distribution of species density derived from statistical models (birds/10 ha) was compared with the published relative abundances depicted by a very accurate regional atlas of wintering birds (birds observed per 10 h). Statistical models explained an average of 41.7% of the original deviance observed in the local bird distribution (range 19.6–79.3%). Significant associations between observed relative abundances (atlas data) and predicted average densities in 1×1 km squares within 10×10 km UTMs were attained for 44 out of 64 species. Interspecific discrepancies between predicted and observed distribution maps decreased with between-year constancy in regional bird distribution and the degree of ecological specialization of species. Therefore, statistical modeling using census localities allowed us to depict geographical variations in bird abundance that were similar to those in the quantitative atlas maps. Nevertheless, bird distributions derived from statistical models are less reproducible in some species than in others, depending on their autoecological traits.     

Applying the dark diversity concept to plants at the European scale

Large‐scale biodiversity maps are essential to macroecology. However, between‐region comparisons can be more useful if patterns of observed species richness are supplemented by variations in dark diversity – the absent portion of the species pool. We aim to quantify and map plant diversity across Europe by using a measure that accounts for both observed and dark diversity. To do this we need to delimit suitable species pools, and evaluate the potential and limitation of a large‐scale dataset. We used Atlas Florae Europaeae (ca 20% of European plant species mapped within 50 × 50 km grid cells) and defined for each grid cell several species pools by applying various geographical and environmental filters: geographic species pool (number of species within 500 km radius), biogeographic species pool (additionally incorporating species distribution patterns, i.e. dispersion fields), site‐specific species pool (additionally integrating environmental preferences of species based on species co‐occurrence). We integrated dark diversity and observed diversity at a relative scale to calculate the completeness of site diversity: logistic expression of observed and dark diversity. We tested whether our results are robust against regional variation in data availability. We used independent regional databases to test if Atlas Florae Europaeae is a representative subset of total species richness. Environmental filtering was the most influential determinant of species pool size with more species filtered out in southern Europe. Both observed and dark diversity adhered to the well‐known latitudinal gradient, but completeness of site diversity varied throughout Europe with no latitudinal trend. Dark diversity patterns were fairly insensitive to variations in regional sampling intensity. Atlas Florae Europaeae represented well the total variation in plant diversity. In summary, dark diversity and completeness of site diversity add valuable information to broad‐scale diversity patterns since observed diversity is expressed at a relative scale.     

Predicting the constraint effect of environmental characteristics on macroinvertebrate density and diversity using quantile regression mixed model

Various factors, such as habitat availability, competition for space, predation, temperature, nutrient supplies, presence of waterfalls, flow variability and water quality, control the abundance, distribution and productivity of stream-dwelling organisms. Each of these factors can influence the response of the density of organisms to a specific environmental gradient, inflating variability and making difficult to understand the possible causal relationship. In our study, we used quantile regression mixed models and Akaike’s information criterion as an indicator of goodness to examine two different datasets, one belonging to Italy and one belonging to Finland, and to detect the limiting action of selected environmental variables. In the Italian dataset, we studied the relationships among five macroinvertebrate families and three physical habitat characteristics (water velocity, depth and substratum size); in the Finnish dataset the relationships between taxa richness and 16 environmental characteristics (chemical and physical). We found limiting relationships in both datasets and validated all of them on different datasets. These relationships are quantitative and can be used to predict the range of macroinvertebrate densities or taxa richness as a function of environmental characteristics. They can be a tool for management purposes, providing the basis for habitat-based models and for the development of ecological indices.