Species-area relationships always overestimate extinction rates from habitat loss

Anthropogenic land-use change decreases pollination and male and female fitness in terrestrial flowering plants

BACKGROUND AND AIMS

The majority of the Earth's land area is currently occupied by humans. Measuring how terrestrial plants reproduce in these pervasive environments is essential for understanding their long-term viability and their ability to adapt to changing environments.

METHODS

We conducted hierarchical and phylogenetically independent meta-analyses to assess the overall effects of anthropogenic land-use changes on pollination, and male and female fitness in terrestrial plants.

KEY RESULTS

We found negative global effects of land-use change (i.e. mainly habitat loss and fragmentation) on pollination and on female and male fitness of terrestrial flowering plants. Negative effects were stronger in plants with self-incompatibility systems and in plants pollinated by invertebrates, regardless of life form and sexual expression. Pollination and female fitness of pollination-generalist and pollination-specialist plants were similarly negatively affected by land-use change, whereas male fitness of specialist plants showed no effects.

CONCLUSIONS

Our findings indicate that angiosperm populations remaining in fragmented habitats negatively affect pollination, and female and male fitness, which will probably decrease the recruitment, survival and long-term viability of plant populations remaining in fragmented landscapes. We underline the main current gaps of knowledge for future research agendas and call not only for a decrease in the current rates of land-use changes across the world but also to embark on active restoration efforts to increase the area and connectivity of remaining natural habitats.

Food environmental footprint: Evolution of the countryside species-area relationship (SAR) with new methodologies

The species-area relationship (SAR) is one of the oldest in ecology, linking the increase in species richness in sampling area. Later, new parameters were incorporated into its equation, such as taxon-specific responses, habitats use by species and species adapted to human-modified habitats, originating the Countryside SAR, a version intended to integrate the life cycle assessment (LCA) methodology, which is still inefficiencies when used to evaluate food production systems. Therefore, we present the first attempt to incorporate into Countryside SAR the minimum land demand parameter for food production, the food environmental footprint - EFP, and improve the use of the method within the agricultural sciences scope. To prepare the EFP, we used land cover data for two types of food systems: agriculture (annual crops), composed of nine types of food; and, livestock (pasture), consisting of meat production. They were later tested in inventories for the Western European broadleaf forest ecoregion (ecocode: PA0445). The most important result observed was that the models responded to variations in production values, resulting in higher impact and a more conservative result when EFP is adopted. But as historically integrating a productivity parameter, or performance of production systems, has been left out of the development of SAR, only the first step has been taken. Therefore, incorporating minimum land demand for food production into the Countryside SAR appears to be a new stage in its development, allowing to generate results that consider the "efficiency" of food production, assuming a more agronomic profile. However, this is still the first attempt to include the EFP in the Countryside SAR, and we believe that our models should still be subject to further evaluation.

Complex interactive responses of biodiversity to multiple environmental drivers

There remains considerable doubt, debate, and confusion regarding how biodiversity responds to gradients of important environmental drivers, such as habitat size, resource productivity, and disturbance. Here we develop a simple but comprehensive theoretical framework based on competition-colonization multispecies communities to examine the separate and interactive effects of these drivers. Using both numerical simulations and analytical arguments, we demonstrate that the critical trade-off between competitive and colonization ability can lead to complex nonlinear, zig-zag responses in both species richness and the inverse Simpson index along gradients of these drivers. Furthermore, we find strong interactions between these drivers that can dramatically shift the response of biodiversity to these gradients. The zig-zag patterns in biodiversity along ecological gradients, together with the strong interactions between the drivers, can explain the mixed findings of empirical studies and syntheses, thereby providing a new paradigm that can reconcile debates on the relationships between biodiversity and multiple drivers.

Assembly Graph as the Rosetta Stone of Ecological Assembly

Ecological assembly-the process of ecological community formation through species introductions-has recently seen exciting theoretical advancements across dynamical, informational, and probabilistic approaches. However, these theories often remain inaccessible to non-theoreticians, and they lack a unifying lens. Here, I introduce the assembly graph as an integrative tool to connect these emerging theories. The assembly graph visually represents assembly dynamics, where nodes symbolise species combinations and edges represent transitions driven by species introductions. Through the lens of assembly graphs, I review how ecological processes reduce uncertainty in random species arrivals (informational approach), identify graphical properties that guarantee species coexistence and examine how the class of dynamical models constrain the topology of assembly graphs (dynamical approach), and quantify transition probabilities with incomplete information (probabilistic approach). To facilitate empirical testing, I also review methods to decompose complex assembly graphs into smaller, measurable components, as well as computational tools for deriving empirical assembly graphs. In sum, this math-light review of theoretical progress aims to catalyse empirical research towards a predictive understanding of ecological assembly.

Climate change extinctions

Climate change is expected to cause irreversible changes to biodiversity, but predicting those risks remains uncertain. I synthesized 485 studies and more than 5 million projections to produce a quantitative global assessment of climate change extinctions. With increased certainty, this meta-analysis suggests that extinctions will accelerate rapidly if global temperatures exceed 1.5°C. The highest-emission scenario would threaten approximately one-third of species, globally. Amphibians; species from mountain, island, and freshwater ecosystems; and species inhabiting South America, Australia, and New Zealand face the greatest threats. In line with predictions, climate change has contributed to an increasing proportion of observed global extinctions since 1970. Besides limiting greenhouse gases, pinpointing which species to protect first will be critical for preserving biodiversity until anthropogenic climate change is halted and reversed.

Spatial distribution and priority conservation areas identification in Three-River-Source National Park considering the multifaceted values of plants

Spatially differentiated conservation effort for natural resources is critical to achieving a balance between protection and development in national parks. However, the extent of priority conservation areas for plants that integrate multispecies and multifaceted values is unclear. Here, we selected fine-resolution environmental variables with stronger impacts on wild plant survival to spatialize the distribution of all modeling-eligible species using species distribution models in Three-River-Source National Park, China. These were then combined with in situ conservation results for insufficient data species to identify priority conservation areas (PCAs) in terms of diversity, ecological and economic values, respectively. We analyzed the spatial characteristics of the priority conservation areas and searched for conservation gaps not covered by national nature reserves. The results showed that this study obtained more precise results on the spatial distribution of species by improving environmental variables and upgrading the spatial resolution. In Three-River-Source National Park, the species richness of wild plants showed a decreasing trend from southeast to northwest. There were significant differences in the spatial distribution of the priority conservation areas identified based on the three values, which was the basis for the spatially differentiated conservation and development of wild plant resources. In addition, the priority conservation areas obtained based on ecological value found Top17% priority conservation areas in the Hoh Xil Natural Reserve, which could not be revealed based on diversity or economic value. These results highlight the urgency of implementing multispecies and multifaceted values studies in national parks. In the future, studying conflicts between wildlife priority conservation areas and human activities, and expanding to national parks on a global scale, will be the focus that this study will continue to explore.

Habitat amount modulates biodiversity responses to fragmentation

Anthropogenic habitat destruction leads to habitat loss and fragmentation, both of which interact to determine how biodiversity changes at the landscape level. While the detrimental effects of habitat loss are clear, there is a long-standing debate about the role of habitat fragmentation per se. We identify the influence of the total habitat amount lost as a modulator of the relationship between habitat fragmentation and biodiversity. Using a simple metacommunity model characterized by colonization-competition (C-C) trade-offs, we show that the magnitude of habitat loss can induce a unimodal response of biodiversity to habitat fragmentation. When habitat loss is low, habitat fragmentation promotes coexistence by suppressing competitively dominant species, while habitat fragmentation at high levels of habitat loss can shape many smaller isolated patches that drive extinctions of superior competitors. While the C-C trade-off is not the only mechanism for biodiversity maintenance, the modulation of habitat fragmentation effects by habitat loss is probably common. Reanalysis of a globally distributed dataset of fragmented animal and plant metacommunities shows an overall pattern that supports this hypothesis, suggesting a resolution to the debate regarding the relative importance of positive versus negative fragmentation effects.

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.

Higher trophic levels and species with poorer dispersal traits are more susceptible to habitat loss on island fragments

Ongoing habitat loss and fragmentation caused by human activities represent one of the greatest causes of biodiversity loss. However, the effects of habitat loss and fragmentation are not felt equally among species. Here, we examined how habitat loss influenced the diversity and abundance of species from different trophic levels, with different traits, by taking advantage of an inadvertent experiment that created habitat islands from a once continuous forest via the creation of the Thousand Island Lake, a large reservoir in China. On 28 of these islands with more than a 9000-fold difference in their area (0.12-1154 ha), we sampled plants, herbivorous insects, and predatory insects using effort-controlled sampling and analyses. This allowed us to discern whether any observed differences in species diversity were due to passive sampling alone or to demographic effects that disproportionately influenced some species relative to others. We found that while most metrics of sampling effort-controlled diversity increased with island area, the strength of the effect was exacerbated for species in higher trophic levels. When we more explicitly examined differences in species composition among islands, we found that the pairwise difference in species composition among islands was dominated by species turnover but that nestedness increased with differences in island area, indicating that some species are more likely to be absent from smaller islands. Furthermore, by examining trends of several dispersal-related traits of species, we found that species with lower dispersal propensity tended to be those that were lost from smaller islands, which was observed for herbivorous and predatory insects. Our results emphasize the importance of incorporating within-patch demographic effects, as well as the taxa and traits of species when understanding the influence of habitat loss on biodiversity.

Preference of trees for nest building by critically endangered white-rumped vultures (Gyps bengalensis) in Nepal

White-rumped vultures (Gyps bengalensis) are critically endangered species, and protecting their habitats, particularly the nesting trees, may have a positive impact on their reproductive success. For a better understanding of vultures' habitat needs, the characteristics of nesting trees should be accounted. In this paper, we compare the characteristics of the trees that have vultures' nests and that do not by randomly select a control tree within a 10 m radius of the nesting tree. We extensively searched and monitored the white-rumped vultures' nests, nesting trees, and nesting tree species in Nepal between 2002 and 2022, and measured the characteristics of sampled trees such as their height, girth, canopy spread, branching orders, and whorls. We recorded 1161 nests of white-rumped vulture in total on 194 trees belonging to 19 species over the past two decades. White-rumped vultures preferred the kapok trees (Bombax ceiba) for nest construction than other tree species (χ 2 = 115.38, df = 1, p < .001) as 66.49% of nests were built on them. In the logistic regression model, the number of whorls on a tree, canopy spread, and the height of the first branch determined whether a nest was present or absent on a tree. These results help to prioritize the tree attributes in a habitat conservation plan for vultures.

The influence of climate changes on heavy metals accumulation in Alosa immaculata from the Danube River Basin

This research report provides a comprehensive overview of the historical trends in heavy metal concentrations in the Pontic shad (Alosa immaculata) populations from both the Danube River and the Black Sea, while also exploring the potential influence of global warming on metal accumulation. Through bibliometric modeling analysis, it reveals significant limitations in existing international research, particularly the lack of comprehensive data on the impact of hydroclimatic changes on heavy metal accumulation in Alosa immaculata. Recognizing the critical importance of studies on heavy metal bioaccumulation in Danube shad, this research underscores their significance in defining tolerance thresholds, quantifying the impact of toxic elements along the aquatic food chain, and enhancing the economic sustainability of ichthyofauna monitoring efforts. Furthermore, these studies contribute invaluable insights into the complex dynamics of aquatic ecosystems, offering essential decision-making support for optimizing commercial fishing management practices on the Danube and ensuring robust support systems for industrial fishing endeavors.

How do species richness and its component dependence vary along the natural restoration in extremely heterogeneous forest ecosystems?

Giant habitat heterogeneity is an important factor contributing to the high species richness (SR) in karst forests. Yet, the driving factor behind the alterations in SR patterns during natural restoration remains unclear. In this study, we established the forest dynamics plots along the natural restoration sequence (including shrub-tree mixed forest stage (SC), secondary forest stage (SG) and old-growth forest sage (OG)) in degraded karst forests to compare the SR and the dependence on its components (including total community abundance, species abundance distribution (SAD), and conspecific spatial aggregation (CSA)) among stages of natural restoration. By evaluating the degree of contribution of the components to local SR and rarefied SR, we found that the SG exhibited the highest local SR, while the rarefied SR remained increasing along the restoration sequence after controlling the sample size. At SC-SG stage, SAD and CSA contributed negatively to the differences in SR, while abundance made a positive contribution to SR differences. At SG-OG, abundance contributed positively to the difference in SR at all scales, while SAD contributed negatively at small scales. No significant contribution of CSA was found at observed scales. In addition, local SR varied more significantly with PIE than with abundance. Our research emphasizes the importance of eliminating the influence of abundance on species richness in forest ecology and management, as well as the significance of separately evaluating the components that shape the diversity patterns.

How many species will Earth lose to climate change?

Climate change may be an important threat to global biodiversity, potentially leading to the extinction of numerous species. But how many? There have been various attempts to answer this question, sometimes yielding strikingly different estimates. Here, we review these estimates, assess their disagreements and methodology, and explore how we might reach better estimates. Large-scale studies have estimated the extinction of ~1% of sampled species up to ~70%, even when using the same approach (species distribution models; SDMs). Nevertheless, worst-case estimates often converge near 20%-30% species loss, and many differences shrink when using similar assumptions. We perform a new review of recent SDM studies, which show ~17% loss of species to climate change under worst-case scenarios. However, this review shows that many SDM studies are biased by excluding the most vulnerable species (those known from few localities), which may lead to underestimating global species loss. Conversely, our analyses of recent climate change responses show that a fundamental assumption of SDM studies, that species' climatic niches do not change over time, may be frequently violated. For example, we find mean rates of positive thermal niche change across species of ~0.02°C/year. Yet, these rates may still be slower than projected climate change by ~3-4 fold. Finally, we explore how global extinction levels can be estimated by combining group-specific estimates of species loss with recent group-specific projections of global species richness (including cryptic insect species). These preliminary estimates tentatively forecast climate-related extinction of 14%-32% of macroscopic species in the next ~50 years, potentially including 3-6 million (or more) animal and plant species, even under intermediate climate change scenarios.

Conservation macrogenetics: harnessing genetic data to meet conservation commitments

Genetic biodiversity is rapidly gaining attention in global conservation policy. However, for almost all species, conservation relevant, population-level genetic data are lacking, limiting the extent to which genetic diversity can be used for conservation policy and decision-making. Macrogenetics is an emerging discipline that explores the patterns and processes underlying population genetic composition at broad taxonomic and spatial scales by aggregating and reanalyzing thousands of published genetic datasets. Here we argue that focusing macrogenetic tools on conservation needs, or conservation macrogenetics, will enhance decision-making for conservation practice and fill key data gaps for global policy. Conservation macrogenetics provides an empirical basis for better understanding the complexity and resilience of biological systems and, thus, how anthropogenic drivers and policy decisions affect biodiversity.

Relocating built-up land for biodiversity conservation in an uncertain future

Land use changes associated with habitat loss, fragmentation, and degradation exert profoundly detrimental impacts on biodiversity conservation. Urban development is one of the prevailing anthropogenic disturbances to wildlife habitat, because these developments are often considered permanent and irreversible. As a result, the potential benefits of built-up land relocation for biodiversity conservation have remained largely unexplored in environmental management practices. Here, we analyze recent built-up land relocation in Shanghai and explore how such restoration programs can affect future land change trajectories with regards to biodiversity conservation. Results show that 187.78 km2 built-up land in Shanghai was restored to natural habitat between 2017 and 2020. Further simulation analysis highlights that relocating built-up land can substantially promote conserve biodiversity. In particular, there would be less habitat loss, better natural habitat quality and more species habitat-suitable range under the scenarios with built-up land relocation. Species extinction assessment suggest that amphibians, mammals, and reptiles will all have an increasingly high extinction risk without built-up land relocation. However, there will even be a marginal decrease in extinction risk over time for mammals and reptiles if the relocation of built-up land is permitted, but still a moderate increase in extinction risk for amphibians. This study highlights the importance of incorporating rigorous conservation planning prior to development activities, thereby underpinning a sustainable approach to environmental management.

Avian Diversity Responds Unimodally to Natural Landcover: Implications for Conservation Management

Predicting species' ecological responses to landcovers within landscapes could guide conservation practices. Current modelling efforts derived from classic species-area relationships almost always predict richness monotonically increasing as the proportion of landcovers increases. Yet evidence to explain hump-shaped richness-landcover patterns is lacking. We tested predictions related to hypothesised drivers of peaked relationships between richness and proportion of natural landcover. We estimated richness from breeding bird atlases at different spatial scales (25 to 900 km2) in New York State and Southern Ontario. We modelled richness to gradients of natural landcover, temperature, and landcover heterogeneity. We controlled models for sampling effort and regional size of the species pool. Species richness peaks as a function of the proportion of natural landcover consistently across spatial scales and geographic regions sharing similar biogeographic characteristics. Temperature plays a role, but peaked relationships are not entirely due to climate-landcover collinearities. Heterogeneity weakly explains richness variance in the models. Increased amounts of natural landcover promote species richness to a limit in landscapes with relatively little (<30%) natural cover. Higher amounts of natural cover and a certain amount of human-modified landcovers can provide habitats for species that prefer open habitats. Much of the variation in richness among landscapes must be related to variables other than natural versus human-dominated landcovers.

Time to Step Up Conservation: Climate Change Will Further Reduce the Suitable Habitats for the Vulnerable Species Marbled Polecat (Vormela peregusna)

Habitat loss and human threats are putting the marbled polecat (Vormela peregusna) on the brink of extinction. Numerous recent studies have found that climate change will further deteriorate the living environment of endangered species, leading to their eventual extinction. In this study, we used the results of infrared camera surveys in China and worldwide distribution data to construct an ensemble model consisting of 10 commonly used ecological niche models to specify potential suitable habitat areas for V. peregusna under current conditions with similar environments to the sighting record sites. Changes in the suitable habitat for V. peregusna under future climate change scenarios were simulated using mid-century (2050s) and the end of the century (2090s) climate scenarios provided by the Coupled Model Intercomparison Project Phase 6 (CMIP6). We evaluated the accuracy of the model to obtain the environmental probability values (cutoff) of the V. peregusna distribution, the current distribution of suitable habitats, and future changes in moderately and highly suitable habitat areas. The results showed that the general linear model (GLM) was the best single model for predicting suitable habitats for V. peregusna, and the kappa coefficient, area under the curve (AUC), and true skill statistic (TSS) of the ensemble model all exceeded 0.9, reflecting greater accuracy and stability than single models. Under the current conditions, the area of suitable habitat for V. peregusna reached 3935.92 × 10⁴ km², suggesting a wide distribution range. In the future, climate change is predicted to severely affect the distribution of V. peregusna and substantially reduce the area of suitable habitats for the species, with 11.91 to 33.55% of moderately and highly suitable habitat areas no longer suitable for the survival of V. peregusna. This shift poses an extremely serious challenge to the conservation of this species. We suggest that attention be given to this problem in Europe, especially the countries surrounding the Black Sea, Asia, China, and Mongolia, and that measures be taken, such as regular monitoring and designating protected areas for the conservation of vulnerable animals.

The evolution of extant South American tropical biomes

This review explores the evolution of extant South American tropical biomes, focusing on when and why they developed. Tropical vegetation experienced a radical transformation from being dominated by non-angiosperms at the onset of the Cretaceous to full angiosperm dominance nowadays. Cretaceous tropical biomes do not have extant equivalents; lowland forests, dominated mainly by gymnosperms and ferns, lacked a closed canopy. This condition was radically transformed following the massive extinction event at the Cretaceous-Paleogene boundary. The extant lowland tropical rainforests first developed at the onset of the Cenozoic with a multistratified forest, an angiosperm-dominated closed canopy, and the dominance of the main families of the tropics including legumes. Cenozoic rainforest diversity has increased during global warming and decreased during global cooling. Tropical dry forests emerged at least by the late Eocene, whereas other Neotropical biomes including tropical savannas, montane forests, páramo/puna, and xerophytic forest are much younger, greatly expanding during the late Neogene, probably at the onset of the Quaternary, at the expense of the rainforest.

Human appropriation of net primary production as driver of change in landscape-scale vertebrate richness

Aim

Land use is the most pervasive driver of biodiversity loss. Predicting its impact on species richness (SR) is often based on indicators of habitat loss. However, the degradation of habitats, especially through land-use intensification, also affects species. Here, we evaluate whether an integrative metric of land-use intensity, the human appropriation of net primary production, is correlated with the decline of SR in used landscapes across the globe.

Location

Global.

Time period

Present.

Major taxa studied

Birds, mammals and amphibians.

Methods

Based on species range maps (spatial resolution: 20 km × 20 km) and an area-of-habitat approach, we calibrated a "species-energy model" by correlating the SR of three groups of vertebrates with net primary production and biogeographical covariables in "wilderness" areas (i.e., those where available energy is assumed to be still at pristine levels). We used this model to project the difference between pristine SR and the SR corresponding to the energy remaining in used landscapes (i.e., SR loss expected owing to human energy extraction outside wilderness areas). We validated the projected species loss by comparison with the realized and impending loss reconstructed from habitat conversion and documented by national Red Lists.

Results

Species-energy models largely explained landscape-scale variation of mapped SR in wilderness areas (adjusted R 2-values: 0.79-0.93). Model-based projections of SR loss were lower, on average, than reconstructed and documented ones, but the spatial patterns were correlated significantly, with stronger correlation in mammals (Pearson's r = 0.68) than in amphibians (r = 0.60) and birds (r = 0.57).

Main conclusions

Our results suggest that the human appropriation of net primary production is a useful indicator of heterotrophic species loss in used landscapes, hence we recommend its inclusion in models based on species-area relationships to improve predictions of land-use-driven biodiversity loss.

Testing the Resource Hypothesis of Species-Area Relationships: Extinction Cannot Work Alone

The mechanisms that underpin the species-area relationship (SAR) are crucial for both the development of biogeographic theory and the application of biodiversity conservation. Since its origin, the resource hypothesis, which proposes that rich resources in vast ecosystems will lower extinction rates and shape the SAR, has not been tested. The impossibility to quantify resources and extinction rates using plants and animals as research subjects, as well as the inability to rule out the influences of the area per se, habitat diversity, dispersal, and the historical background of biodiversity, make testing this hypothesis problematic. To address these challenges and test this hypothesis, two sets of microbial microcosm experimental systems with positive and negative correlated resources and volumes were created in this work. The results of 157 high-throughput sequencing monitoring sessions at 11 time points over 30 consecutive days showed that neither of the experimental groups with positive or negative correlations between total resources and microcosm volume had a significant SAR, and there were no negative correlations between extinction rates and resources. Therefore, in our microcosmic system, resources do not influence extinction rates or shape the SAR. Dispersal should be the principal mode of action if the resource theory is correct.

Genetic diversity loss in the Anthropocene

Anthropogenic habitat loss and climate change are reducing species' geographic ranges, increasing extinction risk and losses of species' genetic diversity. Although preserving genetic diversity is key to maintaining species' adaptability, we lack predictive tools and global estimates of genetic diversity loss across ecosystems. We introduce a mathematical framework that bridges biodiversity theory and population genetics to understand the loss of naturally occurring DNA mutations with decreasing habitat. By analyzing genomic variation of 10,095 georeferenced individuals from 20 plant and animal species, we show that genome-wide diversity follows a mutations-area relationship power law with geographic area, which can predict genetic diversity loss from local population extinctions. We estimate that more than 10% of genetic diversity may already be lost for many threatened and nonthreatened species, surpassing the United Nations' post-2020 targets for genetic preservation.

The role of continental shelf bathymetry in shaping marine range shifts in the face of climate change

As a consequence of anthropogenic climate change, marine species on continental shelves around the world are rapidly shifting deeper and poleward. However, whether these shifts deeper and poleward will allow species to access more, less, or equivalent amounts of continental shelf area and associated critical habitats remains unclear. By examining the proportion of seabed area at a range of depths for each large marine ecosystem (LME), we found that shelf area declined monotonically for 19% of LMEs examined. However, the majority exhibited a greater proportion of shelf area in mid-depths or across several depth ranges. By comparing continental shelf area across 2° latitudinal bands, we found that all coastlines exhibit multiple instances of shelf area expansion and contraction, which have the potential to promote or restrict poleward movement of marine species. Along most coastlines, overall shelf habitat increases or exhibits no significant change moving towards the poles. The exception is the Southern West Pacific, which experiences an overall loss of area with increasing latitude. Changes in continental shelf area availability across latitudes and depths are likely to affect the number of species local ecosystems can support. These geometric analyses help identify regions of conservation priority and ecological communities most likely to face attrition or expansion due to variations in available area.

Global Human Consumption Threatens Key Biodiversity Areas

Key biodiversity areas (KBAs) are critical regions for preserving global biodiversity. KBAs are identified by their importance to biodiversity rather than their legal status. As such, KBAs are often under pressure from human activities. KBAs can encompass many different land-use types (e.g., cropland, pastures) and land-use intensities. Here, we combine a global economic model with spatial mapping to estimate the biodiversity impacts of human land use in KBAs. We find that global human land use within KBAs causes disproportionate biodiversity losses. While land use within KBAs accounts for only 7% of total land use, it causes 16% of the potential global plant loss and 12% of the potential global vertebrate loss. The consumption of animal products accounts for more than half of biodiversity loss within KBAs, with housing the second largest at around 10%. Bovine meat is the largest single contributor to this loss, at around 31% of total biodiversity loss. In terms of land use, lightly grazed pasture contributes the most, accounting for around half of all potential species loss. This loss is concentrated mainly in middle- and low-income regions with rich biodiversity. International trade is an important driver of loss, accounting for 22-29% of total potential plant and vertebrate loss. Our comprehensive global, trade-linked analysis provides insights into maintaining the integrity of KBAs and global biodiversity.

Diversity Scaling of Human Digestive Tract (DT) Microbiomes: The Intra-DT and Inter-individual Patterns

The human gut microbiome has been extensively studied, but its diversity scaling (changes or heterogeneities) along the digestive tract (DT) as well as their inter-individual heterogeneities have not been adequately addressed to the best of our knowledge. Here we fill the gap by applying the diversity-area relationship (DAR), a recent extension to the classic species-area relationship (SAR) in biogeography, by reanalyzing a dataset of over 2000 16s-rRNA microbiome samples obtained from 10 DT sites of over 200 individuals. We sketched out the biogeography “maps” for each of the 10 DT sites by cross-individual DAR analysis, and the intra-DT distribution pattern by cross-DT-site DAR analysis. Regarding the inter-individual biogeography, it was found that all DT sites have the invariant (constant) scaling parameter—all sites possessing the same diversity change rate across individuals, but most sites have different potential diversities, which include the portions of diversity that may be absent locally but present regionally. In the case of this study, the potential diversity of each DT site covers the total diversity of the respective site from all individuals in the cohort. In terms of the genus richness, an average individual hosts approximately 20% of the population-level genus richness (total bacterial genus of a human population). In contrast, in terms of community biodiversity, the percentages of individual over population may exceed 90%. This suggests that the differences between individuals in their DT microbiomes are predominantly in the composition of bacterial species, rather than how their abundances are distributed (i.e., biodiversity). Regarding the intra-DT patterns, the scaling parameter (z) is larger—suggesting that the intra-DT biodiversity changes are larger than inter-individual changes. The higher intra-DT heterogeneity of bacteria diversity, as suggested by larger intra-DT z than the inter-individual heterogeneity, should be expected since the intra-DT heterogeneity reflects the functional differentiations of the DT tract, while the inter-individual heterogeneity (z) reflects the difference of the same DT site across individuals. On average, each DT site contains 21–36% of the genus diversity of the whole DT, and the percentages are even higher in terms of higher taxon levels.

Population-level diversity-disease relationship (p-DDR) in the human microbiome associated diseases

Diversity-disease relationship (DDR) is a de facto standard analysis in the studies of human microbiome associated diseases (MADs). For example, the species richness or Shannon entropy are routinely compared between the healthy and diseased groups. Nevertheless, the basic scale of the standard diversity analysis is individual subject rather than a cohort or population because the diversity is computed for individual samples, not for the group. Here we aim to expand the current DDR study from individual focus to population level, which can offer important insights for understanding the epidemiology of MADs. We analyzed the diversity-disease relationship at cohort scale based on a collection of 23 datasets covering the major human MADs. Methodologically, we harness the power of a recent extension to the classic species-area relationship (SAR), i.e., the diversity-area relationship (DAR), to achieve the expansion from individual DDR to inter-subject diversity scaling analysis. Specifically, we apply the DAR analysis to estimate and compare the potentially maximal accrual diversities of the healthy and diseases groups, as well as the inter-subject diversity scaling parameters and the individual-to-population diversity ratios. It was shown that, except for the potential diversity (D_max) at the cohort level in approximately 5.4% cases of MADs, DAR parameters displayed no significant differences between healthy and diseased treatments. That is, the DAR parameters are rather resilient against MADs, except for the potential diversity in some diseases. We compared our population-level DDR with the existing individual-level DDR patterns and proposed a hypothesis to interpret their differences.

Chinese caterpillar fungus (Ophiocordyceps sinensis) in China: Current distribution, trading, and futures under climate change and overexploitation

Chinese caterpillar fungus (Ophiocordyceps sinensis) is a precious traditional medicine which is mostly distributed on the Qinghai-Tibetan Plateau (QTP). Due to its medicinal values, it has become one of the most valuable biological commodities and widely traded in recent years worldwide. However, its habitat has changed profoundly in recent years under global warming as well as anthropogenic pressures, resulting in a sharp decline in its wild population in recent years. Based on the occurrence samples, this paper estimates the potential distribution of caterpillar fungus using MaxEnt model. The model simulates potential geographical distribution of the species under current climate conditions, and examine future distributions under different climatic change scenarios (i.e., RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 have been modelled in 2050s and 2070s, respectively). For examining the impacts of climate change in future, the integrated effects of climatic impact, trading, and overexploitation had been analyzed in detailed routes. The results show that: 1) The distribution patterns of caterpillar fungus under scenario RCP 2.6 have been predicted without obvious changes. However, range shift has been observed with significant shrinks across all classes of suitable areas in Tianshan, Kunlun Mountains, and the southwestern QTP in 2050s and 2070s under RCP 4.5, RCP 6.0 and RCP 8.5 scenarios, respectively. 2) The exports were decreasing drastically in recent years. Guangzhou and Hongkong are two international super import and consumption centres of caterpillar fungus in the world. 3) Both ecological and economic sustainable utilization of the caterpillar fungus has been threatened by the combined pressures of climate change and overexploitation. A strict but effective regulation and protection system, even a systematic management plan not just on the collectors but the whole explore process are urgently needed and has to be issued in the QTP.

Selective extinctions resulting from random habitat destruction lead to under-estimates of local and regional biodiversity loss in a manipulative field experiment

Land-use change is a significant cause of anthropogenic extinctions, which are likely to continue and accelerate as habitat conversion proceeds in most biomes. One way to understand the effects of habitat loss on biodiversity is through improved tools for predicting the number and identity of species losses in response to habitat loss. There are relatively few methods for predicting extinctions and even fewer opportunities for rigorously assessing the quality of these predictions. In this paper, we address these issues by applying a new method based on rarefaction to predict species losses after random, but aggregated, habitat loss. We compare predictions from three rarefaction models, individual-based, sample-based, and spatially clustered, to those derived from a commonly used extinction estimation method, the species-area relationship (SAR). We apply each method to a mesocosm experiment, in which we aim to predict species richness and extinctions of arthropods immediately following 50% habitat loss. While each model produced strikingly accurate predictions of species richness immediately after the habitat loss disturbance, each model significantly underestimated the number of extinctions occurring at both the local (within-mesocosm) and regional (treatment-wide) scales. Despite the stochastic nature of our small-scale, short-term, and randomly applied habitat loss experiment, we found surprisingly clear evidence for extinction selectivity, for example, when abundant species with low extinction probabilities were extirpated following habitat loss. The important role played by selective extinction even in this contrived experimental system suggests that ecologically driven, trait-based extinctions play an equally important role to stochastic extinction, even when the disturbance itself has no clear selectivity. As a result, neutrally stochastic null models such as the SAR and rarefaction are likely to underestimate extinctions caused by habitat loss. Nevertheless, given the difficulty of predicting extinctions, null models provide useful benchmarks for conservation planning by providing minimum estimates and probabilities of species extinctions.

Steeper spatial scaling patterns of subsoil microbiota are shaped by deterministic assembly process

Although many studies have investigated the spatial scaling of microbial communities living in surface soils, very little is known about the patterns within deeper strata, nor is the mechanism behind them. Here, we systematically assessed spatial scaling of prokaryotic biodiversity within three different strata (Upper: 0-20 cm, Middle: 20-40 cm, and Substratum: 40-100 cm) in a typical grassland by examining both distance-decay (DDRs) and species-area relationships (SARs), taxonomically and phylogenetically, as well as community assembly processes. Each layer exhibited significant biogeographic patterns in both DDR and SAR (p < .05), with taxonomic turnover rates higher than phylogenetic ones. Specifically, the spatial turnover rates, β and z values, respectively, ranged from 0.016 ± 0.005 to 0.023 ± 0.005 and 0.065 ± 0.002 to 0.077 ± 0.004 across soil strata, and both increased with depth. Moreover, the prokaryotic community in grassland soils assembled mainly according to deterministic rather than stochastic mechanisms. By using normalized stochasticity ratio (NST) based on null model, the relative importance of deterministic ratios increased from 48.0 to 63.3% from Upper to Substratum, meanwhile a phylogenetic based method revealed average βNTI also increased with depth, from -5.29 to 19.5. Using variation partitioning and distance approaches, both geographic distance and soil properties were found to strongly affect biodiversity structure, the proportions increasing with depth, but spatial distance was always the main underlying factor. These indicated increasingly deterministic proportions in accelerating turnover rates for spatial assembly of prokaryotic biodiversity. Our study provided new insights on biogeography in different strata, revealing importance of assembly patterns and mechanisms of prokaryote communities in below-surface soils.

Wetlands rise and fall: Six endangered wetland species showed different patterns of habitat shift under future climate change

Degradation and loss of species' suitable habitats in response to global warming are well documented, which are assumed to be affected by increasing temperature. Conversely, habitat increase of species is little reported and is often considered anomalous and unrelated to climate change. In this study, we first revealed the climate-change-driven habitat shifts of six endangered wetland plants - Bruguiera gymnorrhiza, Carex doniana, Glyptostrobus pensilis, Leersia hexandra, Metasequoia glyptostroboides, and Pedicularis longiflora. The current and future potential habitats of the six species in China were predicted using a maximum entropy model based on thirty-year occurrence records and climate monitoring (from 1960 to 1990). Furthermore, we observed the change of real habitats of the six species based on eight-year field observations (from 2011 to 2019). We found that the six species exhibited three different patterns of habitat shifts including decrease, unstable, and increase. The analysis on the main decisive environmental factors showed that these patterns of habitat shifts are counter to what would be expected global warming but are mostly determined by precipitation-related environmental factors rather than temperature. Collectively, our findings highlight the importance of combining multiple environmental factors including temperature and precipitation for understanding plant responses to climate change.

Knight A, Leroi AM, Rosindell J. Relationship between conservation biology and ecology shown through machine reading of 32,000 articles

Conservation biology was founded on the idea that efforts to save nature depend on a scientific understanding of how it works. It sought to apply ecological principles to conservation problems. We investigated whether the relationship between these fields has changed over time through machine reading the full texts of 32,000 research articles published in 16 ecology and conservation biology journals. We examined changes in research topics in both fields and how the fields have evolved from 2000 to 2014. As conservation biology matured, its focus shifted from ecology to social and political aspects of conservation. The 2 fields diverged and now occupy distinct niches in modern science. We hypothesize this pattern resulted from increasing recognition that social, economic, and political factors are critical for successful conservation and possibly from rising skepticism about the relevance of contemporary ecological theory to practical conservation.

Tree Communities in Three-Year-Old Post-Mining Sites Under Different Forest Restoration Techniques in the Brazilian Amazon

Forest loss and degradation in the Brazilian Amazon due to mining activities has been intense for many years. To reverse this situation, a range of restoration programs for deforested and degraded areas have been created and implemented. The aim of this study was to analyze the tree composition, successional stage, dispersal and pollination syndromes, conservation status of tree species, and proximity to seed sources under different forest restoration techniques (seedling planting, natural regeneration, and assisted natural regeneration or nucleation) implemented in post-mining sites in the Paragominas municipality (Pará, Brazil). Sixty permanent plots with a restoration age of three years were selected for tree sampling. A total of 119 species, 83 genera and 27 botanical families were identified. Sites restored with different techniques significantly differed in tree composition. Seedling planting sites exhibited the highest abundance, species richness, and diversity values. These were dominated less by pioneer species when compared to the natural regeneration and nucleation sites. Entomophilic pollination and zoochory dispersal were highly represented in the three types of restored sites. Abundance and species richness were negatively correlated with distance from plots to seed sources, and they sharply declined in natural regeneration and nucleation plots at >250 m from seed sources. Four threatened species were identified in the restored sites. We conclude that a combination of different restoration strategies at three-year-old post-mining restoration sites in the Brazilian Amazon results in the recovery of considerable levels of local tree diversity.

Predictive sampling effort and species-area relationship models for estimating richness in fragmented landscapes

Loss of habitat, specifically deforestation, is a major driver of biodiversity loss. Species-area relationship (SAR) models traditionally have been used for estimating species richness, species loss as a function of habitat loss, and extrapolation of richness for given areas. Sampling-species relationships (SSRs) are interrelated yet separate drivers for species richness estimates. Traditionally, however, SAR and SSR models have been used independently and not incorporated into a single approach. We developed and compared predictive models that incorporate sampling effort species-area relationships (SESARS) along the entire Atlantic Forest of South America, and then applied the best-fit model to estimate richness in forest remnants of Interior Atlantic Forest of eastern Paraguay. This framework was applied to non-volant small mammal assemblages that reflect different tolerances to forest loss and fragmentation. In order to account for differences in functionality we estimated small mammal richness of 1) the entire non-volant small mammal assemblage, including introduced species; 2) the native species forest assemblage; and 3) the forest-specialist assemblage, with the latter two assemblages being subsets of the entire assemblage. Finally, we geospatially modeled species richness for each of the three assemblages throughout eastern Paraguay to identify remnants with high species richness. We found that multiple regression power-law interaction-term models that only included area and the interactions of area and sampling as predictors, worked best for predicting species richness for the entire assemblage and the native species forest assemblage, while several traditional SAR models (logistic, power, exponential, and ratio) best described forest-specialist richness. Species richness was significantly different between assemblages. We identified obvious remnants with high species richness in eastern Paraguay, and these remnants often were geographically isolated. We also found relatively high predicted species richness (in relation to the entire range of predicted richness values) in several geographically-isolated, medium-size forest remnants that likely have not been considered as possible priority areas for conservation. These findings highlight the importance of using an empirical dataset, created using sources representing diverse sampling efforts, to develop robust predictive models. This approach is particularly important in geographic locations where field sampling is limited yet the geographic area is experiencing rapid and dramatic land cover changes. When combined, area and sampling are powerful modeling predictors for questions of biogeography, ecology, and conservation, especially when addressing habitat loss and fragmentation.

Recent Anthropogenic Plant Extinctions Differ in Biodiversity Hotspots and Coldspots

During the Anthropocene, humans are changing the Earth system in ways that will be detectable for millennia to come [1]. Biologically, these changes include habitat destruction, biotic homogenization, increased species invasions, and accelerated extinctions [2]. Contemporary extinction rates far surpass background rates [3], but they seem remarkably low in plants [4, 5]. However, biodiversity is not evenly distributed, and as a result, extinction rates may vary among regions. Some authors have contentiously argued that novel anthropic habitats and human-induced plant speciation can actually increase regional biodiversity [6, 7]. Here, we report on one of the most comprehensive datasets to date, including regional and global plant extinctions in both biodiversity hotspots (mostly from Mediterranean-type climate regions) and coldspots (mostly from Eurasian countries). Our data come from regions covering 15.3% of the Earth's surface and span over 300 years. With this dataset, we explore the trends, causes, and temporal dynamics of recent plant extinctions. We found more, and faster accrual of, absolute numbers of extinction events in biodiversity hotspots compared to coldspots. Extinction rates were also substantially higher than historical background rates, but recent declines are evident. We found higher levels of taxonomic uniqueness being lost in biodiversity coldspots compared to hotspots. Causes of plant extinctions also showed distinct temporal patterns, with agriculture, invasions, and urbanization being significant drivers in hotspots, while hydrological disturbance was an important driver in coldspots. Overall, plant extinctions over the last three centuries appear to be low, with a recent (post-1990) and steady extinction rate of 1.26 extinctions/year.

Distance-dependent seed‒seedling transition in the tree Castanopsis sclerophylla is altered by fragment size

Negative distance-dependence of conspecific seedling mortality (NDisDM) is a crucial stabilizing force that regulates plant diversity, but it remains unclear whether and how fragment size shifts the strength of NDisDM. Here, we surveyed the seed‒seedling transition process for a total of 25,500 seeds of a local dominant tree species on islands of various sizes in a reservoir and on the nearby mainland. We found significant NDisDM on the mainland and large and medium islands, with significantly stronger NDisDM on medium islands. However, positive distance-dependent mortality was detected on small islands. Changes in distance-dependence were critically driven by both rodent attack and pathogen infestation, which were significantly affected by fragment size. Our results emphasize the necessity of incorporating the effects of fragment size on distance-dependent regeneration of dominant plant species into the existing frameworks for better predicting the consequences of habitat fragmentation.

Geo-referenced population-specific microsatellite data across American continents, the MacroPopGen Database

Population genetic data from nuclear DNA has yet to be synthesized to allow broad scale comparisons of intraspecific diversity versus species diversity. The MacroPopGen database collates and geo-references vertebrate population genetic data across the Americas from 1,308 nuclear microsatellite DNA studies, 897 species, and 9,090 genetically distinct populations where genetic differentiation (FST) was measured. Caribbean populations were particularly distinguished from North, Central, and South American populations, in having higher differentiation (FST = 0.12 vs. 0.07-0.09) and lower mean numbers of alleles (MNA = 4.11 vs. 4.84-5.54). While mammalian populations had lower MNA (4.86) than anadromous fish, reptiles, amphibians, freshwater fish, and birds (5.34-7.81), mean heterozygosity was largely similar across groups (0.57-0.63). Mean FST was consistently lowest in anadromous fishes (0.06) and birds (0.05) relative to all other groups (0.09-0.11). Significant differences in Family/Genera variance among continental regions or taxonomic groups were also observed. MacroPopGen can be used in many future applications including latitudinal analyses, spatial analyses (e.g. central-margin), taxonomic comparisons, regional assessments of anthropogenic impacts on biodiversity, and conservation of wild populations.

Habitat loss over six decades accelerates regional and local biodiversity loss via changing landscape connectance

When habitats are lost, species are lost in the region as a result of the sampling process. However, it is less clear what happens to biodiversity in the habitats that remain. Some have argued that the main influence of habitat loss on biodiversity is simply due to the total amount of habitat being reduced, while others have argued that fragmentation leads to fewer species per site because of altered spatial connectance among extant habitats. Here, we use a unique data set on invertebrate species in ponds spanning six decades of habitat loss to show that both regional and local species richness declined, indicating that species loss is compounded by habitat loss via connectivity loss, and not a result of a sampling process or changes in local environmental conditions. Overall, our work provides some of the clearest evidence to date from a longitudinal study that habitat loss translates into species loss, even within the remaining habitats.

Sketching the Human Microbiome Biogeography with DAR (Diversity-Area Relationship) Profiles

SAR (species area relationship) is a classic ecological theory that has been extensively investigated and applied in the studies of global biogeography and biodiversity conservation in macro-ecology. It has also found important applications in microbial ecology in recent years thanks to the breakthroughs in metagenomic sequencing technology. Nevertheless, SAR has a serious limitation for practical applications-ignoring the species abundance and treating all species as equally abundant. This study aims to explore the biogeography discoveries of human microbiome over 18 sites of 5 major microbiome habitats, establish the baseline DAR (diversity-area scaling relationship) parameters, and perform comparisons with the classic SAR. The extension from SAR to DAR by adopting the Hill numbers as diversity measures not only overcomes the previously mentioned flaw of SAR but also allows for obtaining a series of important findings on the human microbiome biodiversity and biogeography. Specifically, two types of DAR models were built, the traditional power law (PL) and power law with exponential cutoff (PLEC), using comprehensive datasets from the HMP (human microbiome project). Furthermore, the biogeography "maps" for 18 human microbiome sites using their DAR profiles for assessing and predicting the diversity scaling across individuals, PDO profiles (pair-wise diversity overlap) for measuring diversity overlap (similarity), and MAD profile (for predicting the maximal accrual diversity in a population) were sketched out. The baseline biogeography maps for the healthy human microbiome diversity can offer guidelines for conserving human microbiome diversity and investigating the health implications of the human microbiome diversity and heterogeneity.

Biotic and abiotic drivers of species loss rate in isolated lakes

Today, anthropogenic impacts are causing a serious crisis for global biodiversity, with rates of extinction increasing at an unprecedented rate. Extinctions typically occur after a certain delay, and understanding the mechanisms causing delays is a key challenge for both fundamental and applied perspectives. Here, we make use of natural experiments, the isolation of lakes by land uplift in Northern Scandinavia, to examine how yearly extinction rates are affected by time since isolation and a range of abiotic and biotic factors. In this aim, we adapted a model of delayed species loss within isolated communities to test the effects of time since isolation, area, pH, depth and the presence/absence of piscivores on extinction rates. As expected, we found that small and/or young lakes experience a higher annual rate of extinctions per species than larger and/or older ones. Compared to previous studies that were conducted for either young (few thousand years ago) or very old (>10,000 years ago) isolates, we demonstrated over a large and continuous temporal scales (50-5,000 years), similar relationship between extinction rates and age. We also show that extinction rates are modified by local environmental factors such as a strong negative effect of increasing pH. Our results urge for the need to consider the time since critical environmental changes occurred when studying extinction rates. In a wider perspective, our study demonstrates the need to consider extinction debts when modelling future effects of climate change, land-use changes or biological invasions on biodiversity.

Semen Microbiome Biogeography: An Analysis Based on a Chinese Population Study

Investigating inter-subject heterogeneity (or spatial distribution) of human semen microbiome diversity is of important significance. Theoretically, the spatial distribution of biodiversity constitutes the core of microbiome biogeography. Practically, the inter-subject heterogeneity is crucial for understanding the normal (healthy) flora of semen microbiotas as well as their possible changes associated with abnormal fertility. In this article, we analyze the scaling (changes) of semen microbiome diversity across individuals with DAR (diversity-area relationship) analysis, a recent extension to classic SAR (species-area relationship) law in biogeography and ecology. Specifically, the unit of “area” is individual subject, and the microbial diversity in seminal fluid of an individual (area) is assessed via metagenomic DNA sequencing technique and measured in the Hill numbers. The DAR models were then fitted to the accrued diversity across different number of individuals (area size). We further tested the difference in DAR parameters among the healthy, subnormal, and abnormal microbiome samples in terms of their fertility status based on a cross-sectional study of a Chinese cohort. Given that no statistically significant differences in the DAR parameters were detected among the three groups, we built unified DAR models for semen microbiome by combining the healthy, subnormal, and abnormal groups. The model parameters were used to (i) estimate the microbiome diversity scaling in a population (cohort), and construct the so-termed DAR profile; (ii) predict/construct the maximal accrual diversity (MAD) profile in a population; (iii) estimate the pair-wise diversity overlap (PDO) between two individuals and construct the PDO profile; (iv) assess the ratio of individual diversity to population (RIP) accrual diversity. The last item (RIP) is a new concept we propose in this study, which is essentially a ratio of local diversity to regional or global diversity (LRD/LGD), applicable to general biodiversity investigation beyond human microbiome.