Reliable estimates of beta diversity with incomplete sampling

Late Miocene transformation of Mediterranean Sea biodiversity

Understanding deep-time marine biodiversity change under the combined effects of climate and connectivity changes is fundamental for predicting the impacts of modern climate change in semi-enclosed seas. We quantify the Late Miocene-Early Pliocene [11.63 to 3.6 million years (Ma)] taxonomic diversity of the Mediterranean Sea for calcareous nannoplankton, dinocysts, foraminifera, ostracods, corals, molluscs, bryozoans, echinoids, fishes, and marine mammals. During this time, marine biota was affected by global climate cooling and the restriction of the Mediterranean's connection to the Atlantic Ocean that peaked with the Messinian salinity crisis. Although the net change in species richness from the Tortonian to the Zanclean varies by group, species turnover is greater than 30% in all cases, reflecting a high degree of reorganization of the marine ecosystem after the crisis. The results show a clear perturbation already in the pre-evaporitic Messinian (7.25 to 5.97 Ma), with patterns differing among groups and subbasins.

The marine biodiversity impact of the Late Miocene Mediterranean salinity crisis

Massive salt accumulations, or salt giants, have formed in highly restricted marine basins throughout geological history, but their impact on biodiversity has been only patchily studied. The salt giant in the Mediterranean Sea formed as a result of the restriction of its gateway to the Atlantic during the Messinian Salinity Crisis (MSC) 5.97 to 5.33 million years ago. Here, we quantify the biodiversity changes associated with the MSC based on a compilation of the Mediterranean fossil record. We conclude that 86 endemic species of the 2006 pre-MSC marine species survived the crisis, and that the present eastward-decreasing richness gradient in the Mediterranean was established after the MSC.

Accounting for imperfect detection when estimating species-area relationships and beta-diversity

Ecologists have historically quantified fundamental biodiversity patterns, including species-area relationships (SARs) and beta diversity, using observed species counts. However, imperfect detection may often bias derived community metrics and subsequent community models. Although several statistical methods claim to correct for imperfect detection, their performance in species-area and β-diversity research remains unproven. We examine inaccuracies in the estimation of SARs and β-diversity parameters that emerge from imperfect detection, and whether such errors can be mitigated using a non-parametric diversity estimator (iNEXT.3D) and Multi-Species Occupancy Models (MSOMs). We simulated 28,350 sampling regimes of 2835 fragmented communities, varying the mean and standard deviation of species detection probabilities, and the number of sampling repetitions. We then quantified the bias, accuracy, and precision of derived estimates of model coefficients for SARs and the effects of patch area on β-diversity (pairwise Sørensen similarity). Imperfect detection biased estimates of all evaluated parameters, particularly when mean detection probabilities were low, and there were few sampling repetitions. Observed counts consistently underestimated species richness and SAR z-values, and overestimated SAR c-values; iNEXT.3D and MSOMs only partially resolved these biases. iNEXT.3D provided the best estimates of SAR z-values, although MSOM estimates were generally comparable. All three methods accurately estimated pairwise Sørensen similarity in most circumstances, but only MSOMs provided unbiased estimates of the coefficients of models examining covariate effects on β-diversity. Even when using iNEXT.3D or MSOMs, imperfect detection consistently caused biases in SAR coefficient estimates, calling into question the robustness of previous SAR studies. Furthermore, the inability of observed counts and iNEXT.3D to estimate β-diversity model coefficients resulted from a systematic, area-related bias in Sørensen similarity estimates. Importantly, MSOMs corrected for these biases in β-diversity assessments, even in suboptimal scenarios. Nonetheless, as estimator performance consistently improved with increasing sampling repetitions, the importance of appropriate sampling effort cannot be understated.

Nitrogen and water addition alters species diversity and interspecific relationship in a desert grassland

Water and nitrogen (N) often affect plant species diversity and interspecific relationship among plant populations in global terrestrial ecosystems. However, the effects of water and N addition on plant diversity and interspecific relationship remain poorly understood. In the study, we designed a three-year field experiment in a desert grassland to assess the effect of increased water (natural +50 %) and N addition (10 g·N·m-2·a-1) on plant diversity and interspecific relationship. Our results showed that the alpha diversity was significantly changed under increased water (W), N addition (N), and water plus N addition (WN). The species richness was decreased significantly on year scales (10 %-27 %), whereas the Pielou index first increased and then decreased over three years and was significantly affected by the interaction between increased water and N addition. The total and pairwise beta diversity were significantly increased by N addition, the community was mainly caused by the turnover component after N addition, especially in 2019 and 2020 (16.6 % and 9 %, respectively). There were significant negative associations among overall populations and dominant populations under N addition, especially Stipa bungeana and Gypsophila davurica, Gypsophila davurica and Oxytropis acemose, Artemisia dalai-lamae, and Haplophyllum dauricum. Our findings suggested that plant community structure and composition changes may be due to competition for resources among dominant populations and the turnover component under increased water and N addition, which should be considered in ecosystem management.

Beyond samples: A metric revealing more connections of gut microbiota between individuals

Studies of gut microbiota explore their complicated connections between individuals of different characteristics by applying different metrics to abundance data obtained from fecal samples. Although classic metrics are capable to quantify differences between samples, the microbiome of fecal sample is not a good surrogate for the gut microbiome of individuals because the microbial populations of the distal colon does not adequately represent that of the entire gastrointestinal tract. To overcome the deficiency of classic metrics in which the differences can be measured between the samples analyzed, but not the corresponding populations, we propose a metric for representing composition differences in the gut microbiota of individuals. Our investigation shows this metric outperforms traditional measures for multiple scenarios. For gut microbiota in diverse geographic populations, this metric presents more explainable data variance than others, not only in regular variance analysis but also in principle component analysis and partition analysis of biologic characteristics. With time-series data, the metric further presents a strong correlation with the time interval of serial sampling. Our findings suggest that the metric is robust and powerfully detects the intrinsic variations in gut microbiota. The metric holds promise for revealing more relations between gut microbiota and human health.

The preservation potential of terrestrial biogeographic patterns

Extinction events in the geological past are similar to the present-day biodiversity crisis in that they have a pronounced biogeography, producing dramatic changes in the spatial distributions of species. Reconstructing palaeobiogeographic patterns from fossils therefore allows us to examine the long-term processes governing the formation of regional biotas, and potentially helps build spatially explicit models for future biodiversity loss. However, the extent to which biogeographic patterns can be preserved in the fossil record is not well understood. Here, we perform a suite of simulations based on the present-day distribution of North American mammals, aimed at quantifying the preservation potential of beta diversity and spatial richness patterns over extinction events of varying intensities, and after applying a stepped series of taphonomic filters. We show that taphonomic biases related to body size are the biggest barrier to reconstructing biogeographic patterns over extinction events, but that these may be compensated for by both the small mammal record preserved in bird castings, as well as range expansion in surviving species. Overall, our results suggest that the preservation potential of biogeographic patterns is surprisingly high, and thus that the fossil record represents an invaluable dataset recording the changing spatial distribution of biota over key intervals in Earth History.

Detecting turnover among complex communities using null models: a case study with sky-island haemosporidian parasites

Turnover in species composition between sites, or beta diversity, is a critical component of species diversity that is typically influenced by geography, environment, and biotic interactions. Quantifying turnover is particularly challenging, however, in multi-host, multi-parasite assemblages where undersampling is unavoidable, resulting in inflated estimates of turnover and uncertainty about its spatial scale. We developed and implemented a framework using null models to test for community turnover in avian haemosporidian communities of three sky islands in the southwestern United States. We screened 776 birds for haemosporidian parasites from three genera (Parahaemoproteus, Plasmodium, and Leucocytozoon) by amplifying and sequencing a mitochondrial DNA barcode. We detected infections in 280 birds (36.1%), sequenced 357 infections, and found a total of 99 parasite haplotypes. When compared to communities simulated from a regional pool, we observed more unique, single-mountain haplotypes and fewer haplotypes shared among three mountain ranges than expected, indicating that haemosporidian communities differ to some degree among adjacent mountain ranges. These results were robust even after pruning datasets to include only identical sets of host species, and they were consistent for two of the three haemosporidian genera. The two more distant mountain ranges were more similar to each other than the one located centrally, suggesting that the differences we detected were due to stochastic colonization-extirpation dynamics. These results demonstrate that avian haemosporidian communities of temperate-zone forests differ on relatively fine spatial scales between adjacent sky islands. Null models are essential tools for testing the spatial scale of turnover in complex, undersampled, and poorly known systems.

Cannot see the diversity for all the species: Evaluating inclusion criteria for local species lists when using abundant citizen science data

Abundant citizen science data on species occurrences are becoming increasingly available and enable identifying composition of communities occurring at multiple sites with high temporal resolution. However, for species displaying temporary patterns of local occurrences that are transient to some sites, biodiversity measures are clearly dependent on the criteria used to include species into local species lists. Using abundant opportunistic citizen science data from frequently visited wetlands, we investigated the sensitivity of α- and β-diversity estimates to the use raw versus detection-corrected data and to the use of inclusion criteria for species presence reflecting alternative site use. We tested seven inclusion criteria (with varying number of days required to be present) on time series of daily occurrence status during a breeding season of 90 days for 77 wetland bird species. We show that even when opportunistic presence-only observation data are abundant, raw data may not produce reliable local species richness estimates and rank sites very differently in terms of species richness. Furthermore, occupancy model based α- and β-diversity estimates were sensitive to the inclusion criteria used. Total species lists (all species observed at least once during a season) may therefore mask diversity differences among sites in local communities of species, by including vagrant species on potentially breeding communities and change the relative rank order of sites in terms of species richness. Very high sampling effort does not necessarily free opportunistic data from its inherent bias and can produce a pattern in which many species are observed at least once almost everywhere, thus leading to a possible paradox: The large amount of biological information may hinder its usefulness. Therefore, when prioritizing among sites to manage or preserve species diversity estimates need to be carefully related to relevant inclusion criteria depending on the diversity estimate in focus.

Drivers of beta diversity in modern and ancient reef-associated soft-bottom environments

Beta diversity, the compositional variation among communities, is often associated with environmental gradients. Other drivers of beta diversity include stochastic processes, priority effects, predation, or competitive exclusion. Temporal turnover may also explain differences in faunal composition between fossil assemblages. To assess the drivers of beta diversity in reef-associated soft-bottom environments, we investigate community patterns in a Middle to Late Triassic reef basin assemblage from the Cassian Formation in the Dolomites, Northern Italy, and compare results with a Recent reef basin assemblage from the Northern Bay of Safaga, Red Sea, Egypt. We evaluate beta diversity with regard to age, water depth, and spatial distance, and compare the results with a null model to evaluate the stochasticity of these differences. Using pairwise proportional dissimilarity, we find very high beta diversity for the Cassian Formation (0.91 ± 0.02) and slightly lower beta diversity for the Bay of Safaga (0.89 ± 0.04). Null models show that stochasticity only plays a minor role in determining faunal differences. Spatial distance is also irrelevant. Contrary to expectations, there is no tendency of beta diversity to decrease with water depth. Although water depth has frequently been found to be a key factor in determining beta diversity, we find that it is not the major driver in these reef-associated soft-bottom environments. We postulate that priority effects and the biotic structuring of the sediment may be key determinants of beta diversity.

Are cities hotspots for bees? Local and regional diversity patterns lead to different conclusions

With the decline of natural habitats, there is an ongoing debate about the importance of the urban environment for pollinating insects. Our research assessed patterns in wild bee species composition, as well as α-, β- and γ-diversity patterns and the nestedness structure in urban, suburban and rural areas. For three years bees were collected along 18 sampling transects in the Poznań area in western Poland. The average species diversity (α-diversity) and the average number of specimens per sample (local abundance) did not differ significantly between the three classes of urbanization. The rarefaction analysis, however, was partly contradictory to the results recorded on the local scale. The highest dissimilarity in the species composition among the samples was observed in the rural areas, while the lowest (more homogenous) was in the urban areas. The differences were significant. This resulted in the highest γ-diversity (cumulative number of species) in the rural areas and the lowest in the urban areas. Furthermore, the bee community in the habitats studied was significantly nested, indicating that species-poor sites (sites with high rank) constituted subsets of species-rich sites (sites with low rank) and that this pattern was not random. Samples collected in urban areas had a significantly higher nestedness rank compared to samples from the other two classes of urbanization, thus suggesting that the urban bee community is a subset of the rural bee community. This is an important conclusion, which emphasises that different components of species diversity need to be screened to identify the real biological impact of urbanisation on bee communities.