Measuring size and composition of species pools: a comparison of dark diversity estimates

The influence of landscape characteristics on breeding bird dark diversity

The exploration of factors and processes affecting biodiversity loss is central to nature management and wildlife conservation, but only recently has knowledge about the absence of species been recognized as a valuable asset to understand the current biodiversity crisis. In this paper, we explore the dark diversity (species that belong to a site-specific species pool but that are not locally present) of breeding birds in Denmark assessed through species co-occurrence patterns. We apply a nation-wide atlas survey of breeding birds (with a 5 × 5 km resolution), to investigate how landscape characteristics may influence avian diversity, and whether threatened and near threatened species are more likely to occur in dark diversity than least concern (LC) species. On average, the dark diversity constituted 41% of all species belonging to the site-specific species pools and threatened and near-threatened species had a higher probability of belonging to the dark diversity than least concern species. Habitat heterogeneity was negatively related to dark diversity and the proportional cover of intensive agriculture positively related, implying that homogeneous landscapes dominated by agricultural interests led to more absent avian species. Finally, we found significant effects of human disturbance and distance to the coast, indicating that more breeding bird species were missing when human disturbance was high and in near-coastal areas. Our study provides the first attempt to investigate dark diversity among birds and highlights how important landscape characteristics may shape breeding bird diversity and reveal areas of considerable species impoverishment.

Dark diversity of flea assemblages of small mammalian hosts: effects of environment, host traits and host phylogeny

An assemblage of species in a locality comprises two components, namely (i) species that are present (realised diversity) and (ii) species from the regional pool that may potentially inhabit this locality due to suitable ecological conditions, but that are absent (dark diversity). We investigated factors affecting the dark diversity of component communities of fleas parasitic on small mammals in the northern Palearctic at two scales. First, we considered the dark diversity of flea assemblages of the same host (for 13 host species) across regions and tested for the effects of environmental factors and the number of available host species on the dark diversity of within-region flea assemblages. Second, we considered the dark diversity of fleas across host species within a region (for 20 regions) and asked whether within-host dark diversity is associated with host phylogeny and/or traits. We found that the dark diversity of flea assemblages harboured by small mammals varied substantially (i) within the same host species across space (in 12 of 13 host species) and (ii) between host species within a region (in eight of 20 regions). The size of the dark diversity of flea assemblages of the same host across regions was generally affected by environmental factors (mainly by the amount of green vegetation), whereas the size of the dark diversity of flea assemblages of a host species within a region was affected by host traits (mainly by the degree of host sociality and the structure of its shelter and, to a lesser degree, by its geographic range size) but was not associated with host phylogenetic affinities. We conclude that application of the dark diversity concept to parasite communities across space or hosts allows a better understanding of the factors affecting the species richness and composition of these communities.

Temporal lags in observed and dark diversity in the Anthropocene

Understanding biodiversity changes in the Anthropocene (e.g. due to climate and land-use change) is an urgent ecological issue. This important task is challenging because global change effects and species responses are dependent on the spatial scales considered. Furthermore, responses are often not immediate. However, both scale and time delay issues can be tackled when, at each study site, we consider dynamics in both observed and dark diversity. Dark diversity includes those species in the region that can potentially establish and thrive in the local sites' conditions but are currently locally absent. Effectively, dark diversity connects biodiversity at the study site to the regional scales and defines the site-specific species pool (observed and dark diversity together). With dark diversity, it is possible to decompose species gains and losses into two space-related components: one associated with local dynamics (species moving from observed to dark diversity and vice versa) and another related to gains and losses of site-specific species pool (species moving to and from the pool after regional immigration, regional extinction or change in local ecological conditions). Extinction debt and immigration credit are useful to understand dynamics in observed diversity, but delays might happen in species pool changes as well. In this opinion piece we suggest that considering both observed and dark diversity and their temporal dynamics provides a deeper understanding of biodiversity changes. Considering both observed and dark diversity creates opportunities to improve conservation by allowing to identify species that are likely to go regionally extinct as well as foreseeing which of the species that newly arrive to the region are more likely to colonize local sites. Finally, by considering temporal lags and species gains and losses in observed and dark diversity, we combine phenomena at both spatial and temporal scales, providing a novel tool to examine biodiversity change in the Anthropocene.

Dark diversity reveals importance of biotic resources and competition for plant diversity across habitats

Species richness is the most commonly used metric to quantify biodiversity. However, examining dark diversity, the group of missing species which can potentially inhabit a site, can provide a more thorough understanding of the processes influencing observed biodiversity and help evaluate the restoration potential of local habitats. So far, dark diversity has mainly been studied for specific habitats or large-scale landscapes, while less attention has been given to variation across broad environmental gradients or as a result of local conditions and biotic interactions. In this study, we investigate the importance of local environmental conditions in determining dark diversity and observed richness in plant communities across broad environmental gradients. Using the ecospace concept, we investigate how these biodiversity measures relate to abiotic gradients (defined as position), availability of biotic resources (defined as expansion), spatiotemporal extent of habitats (defined as continuity), and species interactions through competition. Position variables were important for both observed diversity and dark diversity, some with quadratic relationships, for example, plant richness showing a unimodal response to soil fertility corresponding to the intermediate productivity hypothesis. Interspecific competition represented by community mean Grime C had a negative effect on plant species richness. Besides position-related variables, organic carbon was the most important variable for dark diversity, indicating that in late-succession habitats such as forests and shrubs, dark diversity is generally low. The importance of highly competitive species indicates that intermediate disturbance, such as grazing, may facilitate higher species richness and lower dark diversity.

Throwing light on dark diversity of vascular plants in China: predicting the distribution of dark and threatened species under global climate change

Background

As global climate change accelerates, ecologists and conservationists are increasingly investigating changes in biodiversity and predicting species distribution based on species observed at sites, but rarely consider those plant species that could potentially inhabit but are absent from these areas (i.e., the dark diversity and its distribution). Here, we estimated the dark diversity of vascular plants in China and picked up threatened dark species from the result, and applied maximum entropy (MaxEnt) model to project current and future distributions of those dark species in their potential regions (those regions that have these dark species).

Methods

We used the Beals probability index to estimate dark diversity in China based on available species distribution information and explored which environmental variables had significant impacts on dark diversity by incorporating bioclimatic data into the random forest (RF) model. We collected occurrence data of threatened dark species (Eucommia ulmoides, Liriodendron chinense, Phoebe bournei, Fagus longipetiolata, Amentotaxus argotaenia, and Cathaya argyrophylla) and related bioclimatic information that can be used to predict their distributions. In addition, we used MaxEnt modeling to project their distributions in suitable areas under future (2050 and 2070) climate change scenarios.

Results

We found that every study region’s dark diversity was lower than its observed species richness. In these areas, their numbers of dark species are ranging from 0 to 215, with a generally increasing trend from western regions to the east. RF results showed that temperature variables had a more significant effect on dark diversity than those associated with precipitation. The results of MaxEnt modeling showed that most threatened dark species were climatically suitable in their potential regions from current to 2070.

Discussions

The results of this study provide the first ever dark diversity patterns concentrated in China, even though it was estimated at the provincial scale. A combination of dark diversity and MaxEnt modeling is an effective way to shed light on the species that make up the dark diversity, such as projecting the distribution of specific dark species under global climate change. Besides, the combination of dark diversity and species distribution models (SDMs) may also be of value for ex situ conservation, ecological restoration, and species invasion prevention in the future.

Shifts in the importance of the species pool and environmental controls of epiphytic bryophyte richness across multiple scales

Species richness is influenced by a nested set of environmental factors, but how do these factors interact across several scales? Our main aim is to disentangle the relative importance of environmental filters and the species pool on the richness of epiphytic bryophytes across spatial scales. To do so, we sampled epiphytic bryophytes in 43 oak forests across the northwest of the Iberian Peninsula. As predictors we used climate, descriptors of forest structure and micro-environment. We applied structural equation modeling to relate these variables with richness and cover at three scales: locality (forest), stand (three stands per forest), and sample (a quadrate in a tree). We assumed top-down relationships, so that large-scale variables influenced lower scale variables, and in which cover directly influenced richness. Richness at the next larger scale (locality to stand and stand to sample) is considered a surrogate of the species pool and included as a predictor of richness at the next smaller scale. Environmental variables explain locality richness, but as we decrease the spatial scale, its importance decreases and the dependence on species pool increases. In addition, we found unexpected bottom-up relationships (between micro-scale environment to locality richness). Our results point to the scale dependence of niche vs. neutral processes: niche processes are important at the locality (forest) scale, while neutral processes are significant at the small (sample) scale. We propose a modified conceptualization of the factors influencing biodiversity at different spatial scales by adding links across different scales (between micro-environment and locality-scale richness in our study).

Historical biome distribution and recent human disturbance shape the diversity of arbuscular mycorrhizal fungi

The availability of global microbial diversity data, collected using standardized metabarcoding techniques, makes microorganisms promising models for investigating the role of regional and local factors in driving biodiversity. Here we modelled the global diversity of symbiotic arbuscular mycorrhizal (AM) fungi using currently available data on AM fungal molecular diversity (small subunit (SSU) ribosomal RNA (rRNA) gene sequences) in field samples. To differentiate between regional and local effects, we estimated species pools (sets of potentially suitable taxa) for each site, which are expected to reflect regional processes. We then calculated community completeness, an index showing the fraction of the species pool present, which is expected to reflect local processes. We found significant spatial variation, globally in species pool size, as well as in local and dark diversity (absent members of the species pool). Species pool size was larger close to areas containing tropical grasslands during the last glacial maximum, which are possible centres of diversification. Community completeness was greater in regions of high wilderness (remoteness from human disturbance). Local diversity was correlated with wilderness and current connectivity to mountain grasslands. Applying the species pool concept to symbiotic fungi facilitated a better understanding of how biodiversity can be jointly shaped by large-scale historical processes and recent human disturbance.

Predicting species establishment using absent species and functional neighborhoods

Species establishment within a community depends on their interactions with the local environment and resident community. Such environmental and biotic filtering is frequently inferred from functional trait and phylogenetic patterns within communities; these patterns may also predict which additional species can establish. However, differentiating between environmental and biotic filtering can be challenging, which may complicate establishment predictions. Creating a habitat‐specific species pool by identifying which absent species within the region can establish in the focal habitat allows us to isolate biotic filtering by modeling dissimilarity between the observed and biotically excluded species able to pass environmental filters. Similarly, modeling the dissimilarity between the habitat‐specific species pool and the environmentally excluded species within the region can isolate local environmental filters. Combined, these models identify potentially successful phenotypes and why certain phenotypes were unsuccessful. Here, we present a framework that uses the functional dissimilarity among these groups in logistic models to predict establishment of additional species. This approach can use multivariate trait distances and phylogenetic information, but is most powerful when using individual traits and their interactions. It also requires an appropriate distance‐based dissimilarity measure, yet the two most commonly used indices, nearest neighbor (one species) and mean pairwise (all species) distances, may inaccurately predict establishment. By iteratively increasing the number of species used to measure dissimilarity, a functional neighborhood can be chosen that maximizes the detection of underlying trait patterns. We tested this framework using two seed addition experiments in calcareous grasslands. Although the functional neighborhood size that best fits the community's trait structure depended on the type of filtering considered, selecting these functional neighborhood sizes allowed our framework to predict up to 50% of the variation in actual establishment from seed. These results indicate that the proposed framework may be a powerful tool for studying and predicting species establishment.

Large-scale dark diversity estimates: new perspectives with combined methods

Large‐scale biodiversity studies can be more informative if observed diversity in a study site is accompanied by dark diversity, the set of absent although ecologically suitable species. Dark diversity methodology is still being developed and a comparison of different approaches is needed. We used plant data at two different scales (European and seven large regions) and compared dark diversity estimates from two mathematical methods: species co‐occurrence (SCO) and species distribution modeling (SDM). We used plant distribution data from the Atlas Florae Europaeae (50 × 50 km grid cells) and seven different European regions (10 × 10 km grid cells). Dark diversity was estimated by SCO and SDM for both datasets. We examined the relationship between the dark diversity sizes (type II regression) and the overlap in species composition (overlap coefficient). We tested the overlap probability according to the hypergeometric distribution. We combined the estimates of the two methods to determine consensus dark diversity and composite dark diversity. We tested whether dark diversity and completeness of site diversity (log ratio of observed and dark diversity) are related to various natural and anthropogenic factors differently than simple observed diversity. Both methods provided similar dark diversity sizes and distribution patterns; dark diversity is greater in southern Europe. The regression line, however, deviated from a 1:1 relationship. The species composition overlap of two methods was about 75%, which is much greater than expected by chance. Both consensus and composite dark diversity estimates showed similar distribution patterns. Both dark diversity and completeness measures exhibit relationships to natural and anthropogenic factors different than those exhibited by observed richness. In summary, dark diversity revealed new biodiversity patterns which were not evident when only observed diversity was examined. A new perspective in dark diversity studies can incorporate a combination of methods.