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ABSTRACT Aim Location Taxon Methods Results Main Conclusions An ecological community consists of species of various abundances that reflect their responses to the environmental conditions. A classic macroecological pattern, the species abundance distribution (SAD), has been studied for diverse taxa and communities and integrated into numerous modelling tools. Despite its widespread use, a mathematical model that can capture variations in the empirical SAD and describe its response to environmental changes is still lacking. By integrating the Maximum Entropy Theory of Ecology (METE) with a generalised entropy called Rényi's entropy, we aim to develop a new ecoinformatic model that can predict the variation of empirical SAD along multiple environmental gradients.Panama.Angiosperms.We extend the METE using the Rényi's entropy as an uncertainty measure. We apply this extended METE, called Rényi model, to the tree abundance data from 49 plots in Panama and predict the SAD within each plot. We estimate Rényi's parameter q by fitting the predicted SAD to the empirical SAD in each plot. We further compile climate and soil data from the Panama plots and analyse their relationships with the estimated q using multiple regressions.Rényi model provides adequate description of the empirical SADs and outperforms lognormal or log‐series models in 40 of the 49 tree plots, according to the Akaike information criterion. Variations in Renyi's q estimates (from 1/2 to 1) reflect shifts in the empirical SADs. Multiple regressions reveal that P, Al and NH4, three soil chemicals that are important for tree growth and species distribution, significantly affect Renyi's q across plots.These findings suggest that the Rényi model and Rényi's q can characterise the SAD of communities under environmental changes. They also indicate the potential of using generalised entropies to predict macroecological patterns in stressed ecosystems. [ABSTRACT FROM AUTHOR]

Aims: The relationship between habitat area and species evenness quantifies species relative abundance distribution changes across habitat fragments, providing more information than considering only the species richness to predict biodiversity distribution patterns in fragmented landscapes. However, unlike the species‐area relationships (SARs), the Species Evenness‐Area Relationship (SEARs) has yet to be explored across taxa at a large spatial scale. Here, we resolved how the relationship between species evenness and fragment area varies among taxonomic groups and environmental factors. Location: Global. Taxa: Insecta, Aves, Amphibians and Squamata, Plantae, Arachnida, Mammalia, Mollusca. Methods: We compiled 67 datasets from the FragSAD database, including information on fragments area, species richness, and species abundance of six taxa worldwide. We calculated the species evenness index for each fragment, which is independent of species richness, and tested the relationship between species evenness and fragment area across taxonomic groups. We also used the power model to fit SEAR for each dataset and identified landscape variables with a detectable impact on the occurrence of significant SEARs. Results: In contrast to the positive relationship between species richness and fragment area, species evenness was negatively affected by fragment area when controlling for other environmental factors and the relationships varied significantly among taxonomic groups. Specifically, there were significant negative associations between species evenness and fragment area for insects, birds, spiders, and mammals but not for plants and amphibians. Meanwhile, the occurrence of significant SEARs depends on the number of fragments and total fragment area. Main Conclusions: The contrasting patterns of SEARs and SARs among taxonomic groups highlight the complexity of the mechanisms regulating biodiversity patterns. Although the number of species increases with the increase of fragment area, the decreased evenness implies community instability on larger fragments. Therefore, understanding the prevalence and underlying mechanisms in determining SEARs has critical implications for biodiversity conservation. [ABSTRACT FROM AUTHOR]

Grasslands support a variety of herbivores that profoundly impact biodiversity and ecosystem functioning at local and regional scales. Understanding how different herbivores influence plant diversity across multiple scales is crucial for effective biodiversity conservation. However, most studies have focussed on the effects of grazing intensity on plant diversity, neglecting the impacts and associated mechanisms of different herbivores across scales.Based on a 7‐year grazing experiment with 16 plots in Inner Mongolia's typical steppe, we compared the scale‐dependent effects of different herbivores (cattle, sheep and goats) on plant diversity at moderate grazing intensity. We used the species–area relationship (SAR) and linear mixed models to analyse the changes in species richness across multiple scales (1, 16, 32, 64, 128, 256, 512 and 1024 m2). To understand SAR slope changes, we examined four potential mechanisms: overall species richness, total number of individuals, species abundance distribution and species aggregation.We found that grazing had scale effects on plant diversity, as indicated by a significant decrease in the SAR slope. This decrease in slope suggests that the negative impacts of grazing were more pronounced at larger scales. Additionally, the scale effects of different herbivores on plant diversity varied. Cattle had stronger positive impacts on diversity than sheep and goats at both small (1 m2) and large (1024 m2) scales. Conversely, sheep and goats had stronger negative effects on diversity than did the control at the large scale (1024 m2).The decrease in the SAR slope was mainly caused by changes in overall species richness and species abundance distribution. This was primarily because cattle had a stronger impact on dominant species, whereas sheep and goats had a stronger impact on rare species.Synthesis: Our results demonstrate that even at the same intensity, the grazing effects on species diversity vary with the study scale, herbivore type and their interaction. This finding has important implications for the conservation of grassland biodiversity given that grazing typically occurs at larger scales than in studies with quadrats and involves various herbivores with distinct effects on plant diversity. [ABSTRACT FROM AUTHOR]

Pinus kwangtungensis is an endangered evergreen conifer tree species, and its in situ conservation has been considered one of the most critical issues. However, relative protection is limited by the lack of understanding of its community structure and underlying assembly processes. To study how the species diversity and assembly processes of Pinus kwangtungensis coniferous forest (CF) differed with regional climax community, this study established a series forest dynamic plots both in CF and evergreen deciduous broadleaved mixed forest (EDBM). By performing comparison analysis and PER-SIMPER approaches, we quantified the differences in species diversity and community assembly rules. The results showed that the species α-diversity of CF differed greatly from the EDBM both in species richness and evenness. In addition, the stochastic process acted a more important role in determining species composition, indicating the uncertainty in presence of species. The soil phosphorus and changeable calcium content were the main factors driving the differences in biodiversity, which the importance of soil nutrient factors in driving species composition. Our study highlighted that we should consider the community structure and ecological process when conducting conservation of Pinus kwangtungensis. [ABSTRACT FROM AUTHOR]

Anomalies in species abundance data can potentially cause classification errors in ecological forecasting models. Accurate estimation of anomalies locations can enhance the predictive capacity of models. This study aims to propose an approach for precisely identifying and correcting anomalies within imbalanced species abundance data, thereby addressing the challenges posed by both anomalous and imbalanced species abundance distributions (SADs). A model-agnostic statistical tool, Confident Learning (CL) theory, is introduced to estimate the probability of each sample being misclassified during the prediction phase. Specifically, the approach targets classification errors from models trained on imbalanced SADs for data-cleansing, identifying these records as anomalies. The approach is applied to tuna fisheries datasets, focusing specifically on bigeye tuna (Thunnus obesus), a targeted species in longline fishing, and albacore tuna (Thunnus alalunga), a non-target species in the tropical Atlantic Ocean. These datasets, spanning from 2016 to 2019, featured a spatial resolution of 0.5° × 0.5° and daily temporal resolution, providing a comprehensive view of imbalanced data scenarios. The results demonstrate that all the predictors: Support Vector Machine (SVM), Logistic Regression (LR), Random Forests (RF), and Extreme Gradient Boosting (XGBoost) were considerably enhanced after training on the cleaned datasets. Notably, SVM and LR achieved overall accuracy rates of over 90% on predicting both low- and high-abundant fishing grounds. The proposed approach reveals that the elimination of anomalies can enhance the robustness of ecological forecasting models to imbalanced SADs, offering new insights and technical support for the delicate prediction and assessment of ecological resources.

Species abundance distribution (SAD) combines species richness with species abundance in a community and is an important indicator of community structure. Although many studies have applied mathematical models to fit the SADs of plant communities, there are still few studies on the changes in the shape of SAD (i.e., the skewness of the SAD curves) along the environmental gradient. Especially for forest communities, it is still unclear whether the model fitting and shape change of SADs are consistent in different vegetation types. Here, 28 plots of 20 m × 20 m were set up in Hynobius amjiensis National Nature Reserve according to the main forest vegetation types. The species composition and abundance of each species were surveyed in each plot. The logseries model and the lognormal model were fitted to the SAD in each plot, and then the best-fit model was selected based on the corrected Akaike's Information Criteria (AICc). The α value in Gambin model and the η value in Weibull model were calculated to reflect the shape of SAD in each plot. The λ value in Weibull model was calculated to reflect the scale of SAD (i.e., the range observed in abundance). The relationship between altitude and the shape and scale of SAD was analyzed. The results were as follows: (1) The logseries model fitted SAD better than the lognormal model. (2) When all plots were included, there was no significant correlation between SAD shape (α and η) and altitude, but there was a significant positive correlation between the λ value and altitude. (3) There was a negative correlation between altitude and α and η values in the mixed evergreen and deciduous broad-leaved forests, and there was a significant positive correlation between the α value and altitude in the deciduous broad-leaved forests, while there was no significant correlations between both α value and η value and altitude. The results indicate that the model fitting and shape change of SADs along the environmental gradient are related to the vegetation types of the forest community. Therefore, it is necessary to consider the vegetation types when analyzing the relationship between SAD and impact factors in plant communities.

Species abundance distribution (SAD) combines species richness with species abundance in a community and is an important indicator of community structure. Although many studies have applied mathematical models to fit the SADs of plant communities, there are still few studies on the changes in the shape of SAD (i.e., the skewness of the SAD curves) along the environmental gradient. Especially for forest communities, it is still unclear whether the model fitting and shape change of SADs are consistent in different vegetation types. Here, 28 plots of 20 m × 20 m were set up in Hynobius amjiensis National Nature Reserve according to the main forest vegetation types. The species composition and abundance of each species were surveyed in each plot. The logseries model and the lognormal model were fitted to the SAD in each plot, and then the best-fit model was selected based on the corrected Akaike's Information Criteria (AICc). The a value in Gambin model and the η value in Weibull model were calculated to reflect the shape of SAD in each plot. The A value in Weibull model was calculated to reflect the scale of SAD (i.e., the range observed in abundance). The relationship between altitude and the shape and scale of SAD was analyzed. The results were as follows: (1) The logseries model fitted SAD better than the lognormal model. (2) When all plots were included, there was no significant correlation between SAD shape (a and n) and altitude, but there was a significant positive correlation between the A value and altitude. (3) There was a negative correlation between altitude and a and η values in the mixed evergreen and deciduous broad-leaved forests, and there was a significant positive correlation between the a value and altitude in the deciduous broad-leaved forests, while there was no significant correlations between both a value and n value and altitude. The results indicate that the model fitting and shape change of SADs along the environmental gradient are related to the vegetation types of the forest community. Therefore, it is necessary to consider the vegetation types when analyzing the relationship between SAD and impact factors in plant communities. [ABSTRACT FROM AUTHOR]

Pinus kwangtungensis is an endangered evergreen conifer tree species, and its in situ conservation has been considered one of the most critical issues. However, relative protection is limited by the lack of understanding of its community structure and underlying assembly processes. To study how the species diversity and assembly processes of Pinus kwangtungensis coniferous forest (CF) differed with regional climax community, this study established a series forest dynamic plots both in CF and evergreen deciduous broadleaved mixed forest (EDBM). By performing comparison analysis and PER-SIMPER approaches, we quantified the differences in species diversity and community assembly rules. The results showed that the species α-diversity of CF differed greatly from the EDBM both in species richness and evenness. In addition, the stochastic process acted a more important role in determining species composition, indicating the uncertainty in presence of species. The soil phosphorus and changeable calcium content were the main factors driving the differences in biodiversity, which the importance of soil nutrient factors in driving species composition. Our study highlighted that we should consider the community structure and ecological process when conducting conservation of Pinus kwangtungensis.

[Objective] To investigate the response of species diversity and richness distribution of plant functional groups to degradation in the Gannan alpine meadow, we analyzed the community construction mechanism and resource utilization of different plant functional groups with the deepening of degradation. [Methods] We took the Gannan alpine meadow as the research object, collected the data by sample survey method, fitted the model of species multiplicity, and classified the community species by two-way cluster analysis. [Results] With the deepening of degradation, the vegetation species were dominated by gramineae and saxifragaceae, which were gradually changed to the domination of miscellaneous grasses. The functional group of the miscellaneous grasses played a dominant role in the distribution of the diversity of the community. The multidimensional distribution of all the species was changed with the deepening of degradation, in which the optimal fitting model for the non-degraded meadows was VOLKOV, for the mildly degraded meadows was GEO, and for the moderately and severely degraded meadows were BRO, where the resource allocation mode shifted from random to fixed allocation. The ecological niche model dominated the optimal fitting model for the grass functional group, and the resource allocation mode was dominated by both fixed and random allocation. The optimal fitting model for the legume functional group was BRO, and the resource allocation mode was dominated by fixed allocation. The optimal fitting model for the miscellaneous grass functional group shifted from neutral to neutral allocation mode. The optimal fitting model of the weed functional group shifted from neutral model to ecological niche model, consistent with the optimal model of the multidimensional distribution of all species. The resource allocation shifted from the random allocation to fixed allocation. [Conclusion] The weed functional group is the main reason influencing the multidimensional distribution of the community species. However, the contribution of the graminoid and legume functional groups should not be neglected.

The various vegetation types in the karst landscape have been considered the results of heterogeneous habitats. However, the lack of a comprehensive understanding of regional biodiversity patterns and the underlying ecological processes limits further research on ecological management. This study established forest dynamic plots (FDPs) of the dominant vegetation types (shrubland, SL; mixed tree and shrub forest, MTSF; coniferous forest, CF; coniferous broadleaf mixed forest, CBMF; and broadleaf forest, BF) in the karst landscape and quantified the species diversity patterns and potential ecological processes. The results showed that in terms of diversity patterns, the evenness and species richness of the CF community were significantly lower than other vegetation types, while the BF community had the highest species richness. The other three vegetation types showed no significant variation in species richness and evenness. However, when controlling the number of individuals of FDPs, the rarefied species richness showed significant differences and ranked as BF > SL > MTSF > CBMF > CF, highlighting the importance of considering the impacts of abundance. Additionally, the community assembly of climax communities (CF or BF) was dominated by stochastic processes such as species dispersal or species formation, whereas deterministic processes (habitat filtering) dominated the secondary forests (SL, MTSF, and CBMF). These findings proved that community assembly differs mainly between the climax community and other communities. Hence, it is crucial to consider the biodiversity and of the potential underlying ecological processes together when studying regional ecology and management, particularly in heterogeneous ecosystems. [ABSTRACT FROM AUTHOR]

Cocoa agroforestry system is a form of permanent agriculture where cocoa grows in association with different tree species. This study assessed forest trees assemblages in six aged cocoa agroforests (CAFs). Trees were inventoried on 88 CAF plots (25 × 25 m) of aged 5, 10, 15, 20, 25, and 30 years. MacArthur Broken Stick model, Chao-1 estimates, and Hill numbers were used to quantify tree assemblages. Analysis of similarity was performed to compare species composition of assemblages. A total of 268 trees comprising 33 species and 14 families were identified in the six aged CAFs. No consistent patterns were observed for forest trees assemblages as farms aged from 5 to 30 years. Species composition and abundance distribution were similar among the CAFs. Terminalia superba (n = 58) was the most abundant forest tree species across the six CAFs. The 25-year-old CAF was the highest in species richness, while the 10-year-old was the most diverse (qD = 2.84). The inconsistent patterns for forest trees assemblages in the six CAFs highlight the influence of farm management activities during cocoa farm establishment. The presence of valuable forest tree species (e.g., Cola gigantea, Triplochiton scleroxylon, and Enthandrophragma cylindricum) underscores the importance of sustaining good management practices, especially in older cocoa agroforests. [ABSTRACT FROM AUTHOR]

As a vital component of arbor forests, understory vegetation serves as an essential buffer zone for storing carbon due to its strong capacity for community regeneration. This study aimed to identify the diversity pattern and construction mechanism of Platycladus orientalis and Pinus elliottii understory vegetation based on large-scale sample surveys. The Bayesian Information Criterion value of species abundance distribution (SAD) indicated that the Zipf and Zipf–Mandelbrot models were the best-fitting models. The SAD and gambin fitting results suggested that the Pi. elliottii community had a more balanced structure, with most species being relatively abundant. The multiple regression tree model detected four and six indicator species in P. orientalis and Pi. elliottii communities, respectively. The α-diversity index increased with a rise in altitude and showed a wavy curve with latitude. Linear regression between the β diversity and environmental and geographic distance indicated that the P. orientalis and Pi. elliottii understory communities tended to be dominated by different ecological processes. The partition of β diversity indicated that both communities were dominated by turnover processes, which were caused by environmental classification or spatial constraints. This study helped to understand the diversity maintenance in the P. orientalis and Pi. elliottii understory vegetation communities, and will benefit for diversity restoration and conservation of pure conifer forests.

The SAR11 clade is likely the most abundant microbial lineage on earth. Here, we provide detailed analyses of the group's richness and AD in poorly studied Southern microbiomes. This requires whole community composition analyses to be performed, which are also provided in conjunction with the SAR11‐specific studies. In this way, the work describes unknown aspects of the diversity of an outstanding bacterial lineage and novel data on remote and relatively little‐studied microbial communities. Background: Massively parallel sequencing of environmental DNA allows microbiological studies to be performed in greater detail than was possible with first‐generation sequencing. For example, it facilitates the use of approaches hitherto largely applied to flora and fauna, such as rank abundance distribution (RAD) analyses. Methods: Here, we set out to advance the knowledge on Ca. Pelagibacterales (SAR11) communities from southern South America using environmental sequences from the open ocean in the Argentine sea, the uncharted Engaño Bay, as well as a river and an oligohaline shallow lake from the Patagonian Steppe ecoregion. The structures of the SAR11 assemblages present in these ecosystems were dissected by direct and rarefaction‐based estimates of species richness, and evaluations of the corresponding abundance distributions (ADs), which was addressed by RAD analyses. Results: Microbial community composition analyses revealed that the studied SAR11 assemblages coexist with 27 bacterial phyla. SAR11 richness was in general very high, but ADs turned out to be highly uneven. The results were compatible with prior knowledge, and similar to that derived from point estimates of diversity. However, our comprehensive dissection allowed for more detailed quantitative comparisons to be made between the environments surveyed, and revealed differences regarding both richness and the underlying ADs. Conclusions: Despite SAR11 assemblages being extremely rich, their ADs are very uneven. Richness and ADs can vary, not only between fresh and salt water, but also between oceanic and coastal marine environments. The obtained results provide insights on general topics such as adaptation and the contrast between marine and freshwater radiations. [ABSTRACT FROM AUTHOR]

The ecological influence of functional traits on species persistence as well as on their role over the organization of forest communities in the Brazilian Cerrado biome have not been fully understood yet. In this study, we assessed the effects of six functional groups, characterized by three seed dispersal syndromes (i.e., anemochory, autochory, and zoochory) and three wood density classes (i.e., hardwood, lightwood, and softwood), on tree spatial distribution patterns, habitat occupancy, and ecosystem services (biomass hyper dominance and abundance) provided by a forest community located in the “Parque do Lajeado”, state of Tocantins, Brazil. The similarity among study sites was characterized by applying the tree dominant height approach and the environmental and soil variables as input. The floristic similarity was assessed by applying the Bray-Curtis index. The zoochoric species showed more aggregated spatial pattern at local scale, which indicates that it is more sensitive to environmental gradients than other dispersal syndromes. Meanwhile, hardwood density species were more established in the community, being more persistent to environmental filters. We observed that a small number of species contributed with about 50% of the abundance and biomass of the community, whose functional traits (wood density and dispersal syndrome) indirectly affect the relationship among the community species richness and their ecosystem functions. We observed that the functional traits related to seed dispersal and wood density functional groups resulted in different spatial distribution patterns of those tree species. Therefore, functional traits and environmental factors combined have substantially affected the structure and composition of forest communities at local scale.

The species–area relationship (SAR) has over a 150‐year‐long history in ecology, but how its shape and origins vary across scales and organisms remains incompletely understood. This is the first subcontinental freshwater study to examine both these properties of the SAR in a spatially explicit way across major organismal groups (diatoms, insects, and fish) that differ in body size and dispersal capacity. First, to describe the SAR shape, we evaluated the fit of three commonly used models, logarithmic, power, and Michaelis–Menten. Second, we proposed a hierarchical framework to explain the variability in the SAR shape, captured by the parameters of the SAR model. According to this framework, scale and species group were the top predictors of the SAR shape, climatic factors (heterogeneity and median conditions) represented the second predictor level, and metacommunity properties (intraspecific spatial aggregation, γ‐diversity, and species abundance distribution) the third predictor level. We calculated the SAR as a sample‐based rarefaction curve using 60 streams within landscape windows (scales) in the United States, ranging from 160,000 to 6,760,000 km2. First, we found that all models provided good fits (R2 ≥ 0.93), but the frequency of the best‐fitting model was strongly dependent on organism, scale, and metacommunity properties. The Michaelis–Menten model was most common in fish, at the largest scales, and at the highest levels of intraspecific spatial aggregation. The power model was most frequent in diatoms and insects, at smaller scales, and in metacommunities with the lowest evenness. The logarithmic model fit best exclusively at the smallest scales and in species‐poor metacommunities, primarily fish. Second, we tested our framework with the parameters of the most broadly used SAR model, the log–log form of the power model, using a structural equation model. This model supported our framework and revealed that the SAR slope was best predicted by scale‐ and organism‐dependent metacommunity properties, particularly spatial aggregation, whereas the intercept responded most strongly to species group and γ‐diversity. Future research should investigate from the perspective of our framework how shifts in metacommunity properties due to climate change may alter the SAR. [ABSTRACT FROM AUTHOR]

Recent research has uncovered rapid compositional and structural reorganization of ecological assemblages, with these changes particularly evident in marine ecosystems. However, the extent to which these ongoing changes in taxonomic diversity are a proxy for change in functional diversity is not well understood. Here we focus on trends in rarity to ask how taxonomic rarity and functional rarity covary over time. Our analysis, drawing on 30 years of scientific trawl data, reveals that the direction of temporal shifts in taxonomic rarity in two Scottish marine ecosystems is consistent with a null model of change in assemblage size (i.e. change in numbers of species and/or individuals). In both cases, however, functional rarity increases, as assemblages become larger, rather than showing the expected decrease. These results underline the importance of measuring both taxonomic and functional dimensions of diversity when assessing and interpreting biodiversity change. [ABSTRACT FROM AUTHOR]

Tropical forest tree communities are structured by a range of large-scale drivers including elevation, certain high-impact anthropogenic activities (e.g., deforestation), and fires. However, low-impact human activities such as foraging may also be subtly but notably altering the composition of tropical forest tree communities. The study assessed the (i) differences in species diversity, patterns of relative abundance, and pairwise beta diversity between trees with edible and inedible fruits and seeds along an elevation gradient, and (ii) impact of human foraging on the forest tree communities in Oban Division of Cross River National Park, Nigeria. Fifteen permanent 40 by 40 m plots were established along an elevational gradient (120–460 m above mean sea level). All trees of 0.1 m diameter at breast height (dbh) and above were measured, identified, and, with the aid of structured questionnaires, classified into those with edible and inedible fruits/seeds. A total of 35 edible species with density of 128 stems/ hectare and basal area of 11.99 m2 /hectare, and 109 inedible species with density of 364 stems/hectare and basal area of 22.42 m2 /hectare were sampled. However, the evenness of edible and inedible species was similar at pooled and plot levels. For inedible species, there was a positive relationship between pairwise beta diversity and elevation, and this was driven mainly by turnover. In contrast, edible species exhibited a non-significant trend between elevation and beta diversity. Thus, the study showed that human foraging of edible fruits may have subtly influenced patterns of species diversity and community structure in this tropical forest. [ABSTRACT FROM AUTHOR]

The relationships between the inorganic nutrients and diversity of dinoflagellate cysts (the N-Dc relationships) are one of the most central issues in coastal ecology. It is not only an important pathway to explore the ecological processes of plankton, but also a key element for assessing eutrophication in marine ecosystems. Although the N-Dc relationships have been studied for many years, they have remained controversial, which may be attributed to (1) using samples collected from a single source (2) considering an insufficient range of nutrient concentrations (3) rarely taking into account species abundance distributions (SAD) that could better represent diversity. In this study, the N-Dc relationships are evaluated according to a compiled dataset, which cover the wide range of nutrient concentrations. Species diversity of cysts are estimated by four common diversity metrics and a new SAD parameter. Results show that all diversity metrics are negative with nutrients, which supports that low diversity of cysts could be considered as a signal of eutrophication. Additionally, this study finds a new pattern that SAD of cysts (Nr/N1, Nr and N1 is the abundance of the r-th and the first species in descending order) with decreasing nutrients appears to gradually approach 1: 1/2: 1/3…. In the future, if this pattern can be verified by more investigations, understanding the negative N-Dc relationships is more likely to provide new direction for assessing and managing eutrophication in coastal ecosystem, and even for exploring the general mechanisms determining diversity.

The relationship between temperature (T) and diversity is one of the most important issues in ecology. It provides a key direction not only for exploring the determinants of diversity's patterns, but also for understanding diversity's responses to climate change. Previous studies suggested that T–diversity relationships could be positive, negative, or unimodal. Although these studies accumulated many informative achievements, they might be unsatisfied due to (1) investigating inadequate range of T, (2) selecting incomplete diversity metrics, and (3) making insufficiently detailed analysis of correlation. In this study, species diversity is estimated by four most commonly used diversity metrics and three parameters of species abundance distribution (SAD), and two global datasets of marine phytoplankton (covering a wider range of T) are used to evaluate the T–diversity relationships according to a piecewise model. Results show that all aspects of diversity (except evenness) have the similar relationship with T in the range of lower T, noting that diversity significantly increases as T increases. However, in the range of higher T, diversity may significantly decrease or nearly constant, which indicates that their relationships may be the unimodal or asymptotic. The asymptotic relationship found by this study is assumed that increasing diversity with T will gradually approach the Zipf's law (1:1/2:1/3...). If such assumption can be verified by future investigations, the intrinsic mechanism of the asymptotic relationship is likely to be crucial in understanding the T–diversity relationships. [ABSTRACT FROM AUTHOR]

The ecological influence of functional traits on species persistence as well as on their role over the organization of forest communities in the Brazilian Cerrado biome have not been fully understood yet. In this study, we assessed the effects of six functional groups, characterized by three seed dispersal syndromes (i.e., anemochory, autochory, and zoochory) and three wood density classes (i.e., hardwood, lightwood, and softwood), on tree spatial distribution patterns, habitat occupancy, and ecosystem services (biomass hyper dominance and abundance) provided by a forest community located in the "Parque do Lajeado", state of Tocantins, Brazil. The similarity among study sites was characterized by applying the tree dominant height approach and the environmental and soil variables as input. The floristic similarity was assessed by applying the Bray-Curtis index. The zoochoric species showed more aggregated spatial pattern at local scale, which indicates that it is more sensitive to environmental gradients than other dispersal syndromes. Meanwhile, hardwood density species were more established in the community, being more persistent to environmental filters. We observed that a small number of species contributed with about 50% of the abundance and biomass of the community, whose functional traits (wood density and dispersal syndrome) indirectly affect the relationship among the community species richness and their ecosystem functions. We observed that the functional traits related to seed dispersal and wood density functional groups resulted in different spatial distribution patterns of those tree species. Therefore, functional traits and environmental factors combined have substantially affected the structure and composition of forest communities at local scale. [ABSTRACT FROM AUTHOR]

The relationship between temperature (T) and species diversity is one of the most fundamental issues in marine diversity. Although their relationships have been discussed for many years, how species diversity is related to T remains a controversial question. Previous studies have identified three T–diversity relationships: positive, negative, and unimodal. Recently, the unimodal relationship has received great attention. However, these studies may be biased by (1) considering the insufficient T range of database, (2) using a single diversity metric (generally species richness, S), and (3) rarely considering species abundance distribution (SAD) that can better represent diversity. Here, to seek a more comprehensive understanding of T–diversity relationships, their relationships are evaluated according to a global planktonic foraminifera dataset, which is usually considered as a model dataset for exploring diversity pattern. Species diversity are estimated by four most commonly used metrics and a new SAD parameter (p). Results show that S and Shannon’s index support the typical unimodal relationship with T. However, evenness and dominance do not have significant unimodality. Additionally, this study conjectures that the SAD parameter p with increasing T will gradually approach the minimum 1, noting that SAD (Nr/N1, where Nr and N1 are the abundance of the rth and the first species in descending order) tends to be 1:1/2:1/3…. This study suggests that the T–diversity relationship cannot be wholly reflected by S and the other aspects of diversity (especially SAD) should be considered.

Secondary forests dominated by Masson pine (Pinus massoniana, MPF) and Chinese fir (Cunninghamia lanceolata, CFF) are widespread in the subtropical areas of China, whereas their biodiversity patterns receive far less attention than biomass patterns. This study aimed to gain insights into the species richness (SR) patterns of the typical natural secondary MPF and CFF in central China, with the old-growth zonal vegetation (evergreen-deciduous broadleaved mixed forest, EDBMF) used as reference. We established 45 plots across the three forest types and surveyed all the stems with a diameter at breast height ≥ 1 cm in each plot. Specifically, we compared the local (plot-level) and rarefied SR among the three forest types; at the metacommunity level, we examined the dependence of the rarefied SR difference between MPF and CFF on the number of individuals (N), species abundance distribution (SAD), and conspecific spatial aggregation (CSA); and we also assessed how local SR changed with N and species dominance within MPF and CFF. Our results showed that MPF had local and rarefied SR levels higher than CFF and closer to EDBMF. Both N and SAD had positive contributions to the high rarefied SR level of MPF (relative to CFF), while CSA had negative contributions. The N contributions were significant and dominated at most scale, the SAD contributions were considerable and significant at large scales, and the CSA contributions were significant at small and intermediate scales. Moreover, within MPF and CFF, local SR changed with N more generally than with species dominance. In conclusion, at both local and metacommunity level, MPF was generally more species-rich than CFF, and this difference remarkably depended on N, suggesting that the habitat conditions of CFF may be stressful for species persistence. Our findings also have several implications for biodiversity research and ecosystem management.

Understanding the mechanisms of ecological community dynamics and how they could be affected by environmental changes is important. Population dynamic models have well known ecological parameters that describe key characteristics of species such as the effect of environmental noise and demographic variance on the dynamics, the long‐term growth rate, and strength of density regulation. These parameters are also central for detecting and understanding changes in communities of species; however, incorporating such vital parameters into models of community dynamics is challenging. In this paper, we demonstrate how generalized linear mixed models specified as intercept‐only models with different random effects can be used to fit dynamic species abundance distributions. Each random effect has an ecologically meaningful interpretation either describing general and species‐specific responses to environmental stochasticity in time or space, or variation in growth rate and carrying capacity among species. We use simulations to show that the accuracy of the estimation depends on the strength of density regulation in discrete population dynamics. The estimation of different covariance and population dynamic parameters, with corresponding statistical uncertainties, is demonstrated for case studies of fish and bat communities. We find that species heterogeneity is the main factor of spatial and temporal community similarity for both case studies. [ABSTRACT FROM AUTHOR]

Understanding how and why species abundance distributions (SADs) vary with sampling scale has been a long-standing issue in ecology. By fitting various SAD models with observations collected in three large forest field plots, the objective of this study is to explore how the shape of SADs and the predictive ability of SAD models vary with sampling scales. Based on a large dataset collected in the Changbaishan, Jiaohe and Liangshui forests in northeastern China, observed SADs were compared with SADs estimated using five different models (log-normal, broken stick, Zipf, niche preemption and neutral model) at four sampling scales (10 × 10 m, 30 × 30 m, 60 × 60 m and 90 × 90 m). The results show that the studied SADs are scale dependent. Niche-based models provided a better fit at small sample sizes, the predictive ability decreasing with increasing sampling scale. The neutral model performed better at large sample sizes, the predictive ability increasing with increasing sampling scale. We identify the models that provided the best fit to observed species abundance distributions across spatial scales, and conclude that there is not one best SAD model for all spatial scales. Future studies should consider the scale effects on the species abundance distribution.

Abstract Describing the variation in commonness and rarity in a community is a fundamental method of evaluating biodiversity. Such patterns have been studied in the context of species abundance distributions (SADs) among macroscopic organisms in numerous communities. Recently, models for analyzing variation in local SAD shapes along environmental gradients have been constructed. The recent development of high‐throughput sequencing enables evaluation of commonness and rarity in local communities of microbes using operational taxonomic unit (OTU) read number distributions (ORDs), which are conceptually similar to SADs. However, few studies have explored the variation in local microbial ORD shapes along environmental gradients. Therefore, the similarities and differences between SADs and ORDs are unclear, clouding any universal rules of global biodiversity patterns. We investigated the similarities and differences in ORD shapes versus SADs, and how well environmental variables explain the variation in ORDs along latitudinal and depth gradients. Herein, we integrate ORDs into recent comparative analysis methods for SAD shape using datasets generated on the Tara Oceans expedition. About 56% of the variance in skewness of ORDs among global oceanic bacterial communities was explained with this method. Moreover, we confirmed that the parameter combination constraints of Weibull distributions were shared by ORDs of bacterial communities and SADs of tree communities, suggesting common long‐term limitation processes such as adaptation and community persistence acting on current abundance variation. On the other hand, skewness was significantly greater for bacterial communities than tree communities, and many ecological predictions did not apply to bacterial communities, suggesting differences in the community assembly rules for microbes and macroscopic organisms. Approaches based on ORDs provide opportunities to quantify macroecological patterns of microbes under the same framework as macroscopic organisms.

Interspecific differences in species abundances are one of the oldest and most universal patterns in ecology, yet little is known about how these differences are generated over evolutionary time. In this study, we test whether there is evidence for phylogenetic signal in population densities of four large groups of terrestrial vertebrates, namely birds, mammals, amphibians, and squamates. In addition, we test the hypothesis that the relative number of species in a clade might be a predictor of the abundance of its constituent species. However, given that the number of species in a clade is the outcome of both its age and diversification rate, and each of these factors was tested separately. Our results provide strong support for phylogenetic signal in species densities for all clades, regardless of differences in how species density was computed, or phylogenetic uncertainty. On the other hand, there was no evidence for a relationship between species abundance and the diversity of its encompassing clade. The implications of phylogenetic signal are discussed in the context of models of species abundance distributions, including Hubbell's neutral theory of biodiversity and biogeography. [ABSTRACT FROM AUTHOR]

My research aimed to examine a variety of macroecological and biogeographical patterns using a large number of purely habitat island datasets (i.e. isolated patches of natural habitat set within in a matrix of human land uses) sourced from both the literature and my own sampling, with the objective of testing various macroecological and biogeographical patterns. These patterns can be grouped under four broad headings: 1) species–area relationships (SAR), 2) nestedness, 3) species abundance distributions (SADs) and 4) species incidence functions (function of area). Overall, I found that there were few hard macroecological generalities that hold in all cases across habitat island systems. This is because most habitat island systems are highly disturbed environments, with a variety of confounding variables and ‘undesirable’ species (e.g. species associated with human land uses) acting to modulate the patterns of interest. Nonetheless, some clear patterns did emerge. For example, the power model was by the far the best general SAR model for habitat islands. The slope of the island species–area relationship (ISAR) was related to the matrix type surrounding archipelagos, such that habitat island ISARs were shallower than true island ISARs. Significant compositional and functional nestedness was rare in habitat island datasets, although island area was seemingly responsible for what nestedness was observed. Species abundance distribution models were found to provide useful information for conservation in fragmented landscapes, but the presence of undesirable species substantially affected the shape of the SAD. In conclusion, I found that the application of theory derived from the study of true islands, to habitat island systems, is inappropriate as it fails to incorporate factors that are unique to habitat islands.

Several rare species of the island of Cuba are facing local extinction risk and threats. The endemic Cuban Black-Hawk (Buteogallus gundlachii) is threatened by habitat loss as ~50% of its original habitat has been fragmented by tourism activity. Despite this situation, little information on its population size is available and its abundance patterns in relation to environmental variables are largely unknown. Such information is urgently needed to understand its geographic distribution and population abundance trends. We modeled the spatial patterns of abundance of the hawk in central Cuba and then assessed the effectiveness of protected areas for conserving this species. We fitted an ecological niche model to occurrence data of the Cuban Black-Hawk. The centroid of the predicted distribution range was calculated in ecological space and the multidimensional Euclidean distance to the niche centroid (DNC) was estimated. A function describing the relationship between the species abundance and the distance to the niche centroid was used to construct a map depicting the distribution of the Cuban Black-Hawk abundance. The potential distribution range of the raptor encompasses a 703.4 km2 area and represents 12.5% of the total study area. Results show an inverse relationship between DNC and abundance (R2 = 0.37): the sites closer to the centroid of the ecological niche of the species contain more individuals. The model shows that a shorter distance to the coastline and larger distance to urban zones increase the probability of occurrence of the hawk. Based on these results, we estimated that only 24% of the area where a high hawk abundance is expected is currently included in protected areas. We suggest establishing priority survey sites and strengthening protection of the Cuban Black-Hawk in the zones we identified as most valuable in the archipelago. This approach could also be used for other rare and endemic species in other ecosystems.

Understanding how species are non‐randomly distributed in space and how the resulting spatial structure responds to ecological, biogeographic, and anthropogenic drivers is a critical piece of the biodiversity puzzle. However, most metrics that quantify the spatial structure of diversity (i.e., community differentiation), such as Whittaker's β‐diversity, depend on sampling effort and are influenced by species pool size, species abundance distributions, and numbers of individuals. Null models are useful for identifying the degree of differentiation among communities due to spatial structuring relative to that expected from sampling effects, but do not accommodate the influence of sample completeness (i.e., the proportion of the species pool in a given sample). Here, we develop an approach that makes use of individual‐ and coverage‐based rarefaction and extrapolation, to derive a metric, βC, which captures changes in intraspecific aggregation independently of changes in the species pool size. We illustrate the metric using spatially explicit simulations and two case studies: (1) a re‐analysis of the "Gentry" plot data set consisting of small forest plots spanning a latitudinal gradient from North to South America and (2) comparing a large plot in high diversity tropical forests of Barro Colorado Island, Panama, with a plot in a lower diversity temperate forest in Harvard Forest, Massachusetts, USA. We find no evidence for systematic changes in spatial structure with latitude in these data sets. As it is rooted in biodiversity sampling theory and explicitly controls for sample completeness, our approach represents an important advance over existing null models for spatial aggregation. Potential applications range from better descriptors of biogeographic diversity patterns to the consolidation of local and regional diversity trends in the current biodiversity crisis. [ABSTRACT FROM AUTHOR]

Aims It is important to explore the underlying mechanisms that cause triphasic species–area relationship (triphasic SAR) across different scales in order to understand the spatial patterns of biodiversity. Methods Instead of theory establishment or field data derivation, I adopted a data simulation method that used the power function of SAR to fit log-normal distribution of species abundance. Important Findings The results showed that one-step sampling caused biphasic SAR and n -step sampling could cause 2 n -phasic SAR. Practical two-step sampling produced triphasic SAR due to the Preston and Pan effects in large areas. Furthermore, before exploring biological or ecological mechanisms for the nature phenomenon, we should identify or exclude potential mathematical, statistical or sampling reasons. [ABSTRACT FROM AUTHOR]

Here, we propose a theory for the structure of communities of competing species. We include ecologically realistic assumptions, such as density dependence and stochastic fluctuations in the environment, and analyze how evolution caused by r - and K -selection will affect the packing of species in the phenotypic space as well as the species abundance distribution. Species-specific traits have the same matrix G of additive genetic variances and covariances, and evolution of mean traits is affected by fluctuations in population size of all species. In general, the model produces a shape of the distributions of log abundances that is skewed to the left, which is typical of most natural communities. Mean phenotypes of the species in the community are distributed approximately uniformly on the surface of a multidimensional sphere. However, environmental stochasticity generates selection that deviates species slightly from this surface; nonetheless, phenotypic distribution will be different from a random packing of species. This model of community evolution provides a theoretical framework that predicts a relationship between the structure of the phenotypic space and the form of species abundance distributions that can be compared against time series of variation in community structure. [ABSTRACT FROM AUTHOR]

A species abundance distribution (SAD) characterises patterns in the commonness and rarity of all species within an ecological community. As such, the SAD provides the theoretical foundation for a number of other biogeographical and macroecological patterns, such as the species–area relationship, as well as being an interesting pattern in its own right. While there has been resurgence in the study of SADs in the last decade, less focus has been placed on methodology in SAD research, and few attempts have been made to synthesise the vast array of methods which have been employed in SAD model evaluation. As such, our review has two aims. First, we provide a general overview of SADs, including descriptions of the commonly used distributions, plotting methods and issues with evaluating SAD models. Second, we review a number of recent advances in SAD model fitting and comparison. We conclude by providing a list of recommendations for fitting and evaluating SAD models. We argue that it is time for SAD studies to move away from many of the traditional methods available for fitting and evaluating models, such as sole reliance on the visual examination of plots, and embrace statistically rigorous techniques. In particular, we recommend the use of both goodness-of-fit tests and model-comparison analyses because each provides unique information which one can use to draw inferences.

As a transitional vegetation type between evergreen broadleaved forest and deciduous broadleaved forest, evergreen-deciduous broadleaved mixed forest is composed of diverse plant species. This distinctive forest is generally distributed in mountainous areas with complex landforms and heterogeneous microenvironments. However, little is known about the roles of environmental conditions in driving the species diversity patterns of this forest. Here, based on a 15-ha plot in central China, we aimed to understand how and to what extent topographical characteristics and soil nutrients regulate the number and relative abundance of tree species in this forest. We measured environmental factors (terrain convexity, slope, soil total nitrogen, and phosphorus concentrations) and species diversity (species abundance distribution and species richness) in 20 m × 20 m subplots. Species abundance distribution was characterized by skewness, Berger–Parker index, and the proportion of singletons. The generalized additive model was used to examine the variations in diversity patterns caused by environmental factors. The structural equation model was used to assess whether and how topographical characteristics regulate species diversity via soil nutrients. We found that soil nutrients had significant negative effects on species richness and positive effects on all metrics of species abundance distribution. Convexity had significant positive effects on species richness and negative effects on all metrics of species abundance distribution, but these effects were mostly mediated by soil nutrients. Slope had significant negative effects on skewness and the Berger–Parker index, and these effects were almost independent of soil nutrients. Soil nutrients and topographical characteristics together accounted for 9.5–17.1% of variations in diversity patterns and, respectively, accounted for 8.9–13.9% and 3.3–10.7% of the variations. We concluded that soil nutrients were more important than topographical factors in regulating species diversity. Increased soil nutrient concentration led to decreased taxonomic diversity and increased species dominance and rarity. Convexity could be a better proxy for soil nutrients than slope. Moreover, these abiotic factors played limited roles in regulating diversity patterns, and it is possible that the observed patterns are also driven by some biotic and abiotic factors not considered here.

As a transitional vegetation type between evergreen broadleaved forest and deciduous broadleaved forest, evergreen-deciduous broadleaved mixed forest is composed of diverse plant species. This distinctive forest is generally distributed in mountainous areas with complex landforms and heterogeneous microenvironments. However, little is known about the roles of environmental conditions in driving the species diversity patterns of this forest. Here, based on a 15-ha plot in central China, we aimed to understand how and to what extent topographical characteristics and soil nutrients regulate the number and relative abundance of tree species in this forest. We measured environmental factors (terrain convexity, slope, soil total nitrogen, and phosphorus concentrations) and species diversity (species abundance distribution and species richness) in 20 m × 20 m subplots. Species abundance distribution was characterized by skewness, Berger–Parker index, and the proportion of singletons. The generalized additive model was used to examine the variations in diversity patterns caused by environmental factors. The structural equation model was used to assess whether and how topographical characteristics regulate species diversity via soil nutrients. We found that soil nutrients had significant negative effects on species richness and positive effects on all metrics of species abundance distribution. Convexity had significant positive effects on species richness and negative effects on all metrics of species abundance distribution, but these effects were mostly mediated by soil nutrients. Slope had significant negative effects on skewness and the Berger–Parker index, and these effects were almost independent of soil nutrients. Soil nutrients and topographical characteristics together accounted for 9.5–17.1% of variations in diversity patterns and, respectively, accounted for 8.9–13.9% and 3.3–10.7% of the variations. We concluded that soil nutrients were more important than topographical factors in regulating species diversity. Increased soil nutrient concentration led to decreased taxonomic diversity and increased species dominance and rarity. Convexity could be a better proxy for soil nutrients than slope. Moreover, these abiotic factors played limited roles in regulating diversity patterns, and it is possible that the observed patterns are also driven by some biotic and abiotic factors not considered here. [ABSTRACT FROM AUTHOR]

β‐diversity is a primary biodiversity pattern for inferring community assembly. A randomized null model that generates a standardized β‐deviation has been widely used for this purpose. However, the null model has been much debated and its application is limited to abundance data.Here we derive analytical models for β‐diversity to address the debate, clarify the interpretation and extend the application to occurrence data.The analytical analyses show unambiguously that the standardized β‐deviation is a quantification of the effect size of non‐random spatial distribution of species on β‐diversity for a given species abundance distribution. It robustly scales with sampling effort following a power law with exponent of 0.5. This scaling relationship offers a simple method for comparing β‐diversity of communities of different sizes.Assuming log‐series distribution for the metacommunity species abundance distribution, our model allows for calculation of the standardized β‐deviation using occurrence data plus a datum on the total abundance.Our theoretical model justifies and generalizes the use of the β null model for inferring community assembly rules. [ABSTRACT FROM AUTHOR]

Understanding how and why species abundance distributions (SADs) vary with sampling scale has been a long-standing issue in ecology. By fitting various SAD models with observations collected in three large forest field plots, the objective of this study is to explore how the shape of SADs and the predictive ability of SAD models vary with sampling scales. Based on a large dataset collected in the Changbaishan, Jiaohe and Liangshui forests in northeastern China, observed SADs were compared with SADs estimated using five different models (log-normal, broken stick, Zipf, niche preemption and neutral model) at four sampling scales (10 × 10 m, 30 × 30 m, 60 × 60 m and 90 × 90 m). The results show that the studied SADs are scale dependent. Niche-based models provided a better fit at small sample sizes, the predictive ability decreasing with increasing sampling scale. The neutral model performed better at large sample sizes, the predictive ability increasing with increasing sampling scale. We identify the models that provided the best fit to observed species abundance distributions across spatial scales, and conclude that there is not one best SAD model for all spatial scales. Future studies should consider the scale effects on the species abundance distribution. [ABSTRACT FROM AUTHOR]

Rarity is an important aspect of biodiversity often neglected in ecological studies. Species abundance distributions (SADs) are useful tools to describe patterns of commonness–rarity in ecological communities. Most studies assume field observations of species relative abundances are approximately equal to their true relative abundances, thus dismissing the potential for, and importance of unseen rare species. Here, we adopted the approach proposed by Chao et al. (Ecol, 96:1189–1201, 2015) to estimate the number and abundance of unseen species, and thus the true SADs, for tree species in 48 forest sites in Minas Gerais state, Brazil (4 rainforests, 35 semideciduous forests, and 9 deciduous forests). Also, we assessed the correlations between both unseen and rare species and sampling protocol and environment characteristics (climate, terrain, terrain heterogeneity). We found estimated true SADs invariably had higher species richness values than observed in the surveys, due to the increase in rare species. We estimate that up to 55.6% of tree species per site were unseen (8.5–55.6%), with an average of 26.6%. The estimated percentage of rare species per site was between 31.9% and 72.8%, with an average of 57.78%. We found rarity to be most strongly correlated with the percentage of unidentified trees, local terrain conditions and heterogeneity at site-level. Semideciduous forest and rainforest had similar higher percentages of unseen species (c. 27.2%) when compared to deciduous forests, probably due to the relatively higher local heterogeneity of these forests, which may provide more niches for rare species. Future studies should consider estimating true species abundances to better assess biodiversity. [ABSTRACT FROM AUTHOR]

Insect parasitoids may be an exception to the typical biogeographic pattern of increasing species richness at lower latitudes exhibited by most taxa. Evidence for this 'anomalous' latitudinal gradient has been derived from observations of hymenopteran parasitoids and it has been argued that other parasitoid groups should show a similar pattern of diversity. Several mechanisms have been proposed to explain this disparity, most notably the nasty host and resource fragmentation hypotheses.We review and evaluate these hypotheses with respect to tachinid flies (Diptera: Tachinidae), and bring to the argument evidence from eight trapping surveys from temperate and tropical regions in the Americas including the United States, Costa Rica, and Ecuador. We find no evidence that tachinid fly diversity is lower in the tropics than in the temperate region. Our results, along with other lines of evidence, rather suggest that New World Tachinidae likely conform to the same negative relationship between latitude and richness as their largely phytophagous host taxa.We discuss geographic patterns of tachinid diversity in relation to ecological and evolutionary processes, and why they may differ from their hymenopteran parasitoid counterparts. Parasitoid taxa appear to vary strongly in their diversity responses to latitude and we concur with previous researchers that more survey data are necessary to reach strong conclusions about parasitoid latitudinal diversity patterns. [ABSTRACT FROM AUTHOR]

Aim: Estimating species richness from a series of samples is an important and widely debated issue in ecology and biodiversity conservation. Numerous tests of respective richness estimators gave insights into the precision, the limitations and the pitfalls of richness forecasting. However, few benchmark tests used almost complete empiric census data obtained at those spatial scales where richness estimation is most useful for conservation management. Location: Japan. Methods: We use an extraordinary dataset on the spatial distribution of Japanese plants containing complete information on the occurrence of each Japanese plant species at the 10 × 10 km2 grid cell level. We link the estimates of four estimators representing different theoretical approaches, Chao2, rarefaction, species–area relationships (SAR) and species abundance distributions (SAD), to environmental data using a fully nested sampling design. Results: Chao2 and rarefaction behaved very similar in all tests and significantly underestimated true richness below 40% sampling fraction. SAR and SAD were less precise than Chao2 and rarefaction at higher sampling fraction but also less affected by low sample size. In general, SAD provided robust estimates over the whole range of sampling fraction and 67.4% of estimates ranged within the 10% error level. Higher species spatial turnover increased and high evenness in occurrence decreased the precision of the SAD estimator. Precision of the four estimators was largely unaffected by environmental variability but increased with increasing latitude. Main conclusions: Our results strongly indicate that the pattern of Japanese plant species spatial distribution is sufficiently scale invariant for richness estimators to provide precise forecasting results at the country level. The simplest process to generate such a spatial distribution is ecological drift. [ABSTRACT FROM AUTHOR]

This data-intensive study investigated the delicate balance of niche and neutrality underlying microbial communities in freshwater ecosystems through comprehensive application of high-throughput sequencing, species abundance distribution (SAD), and the neutral community model (NCM), combined with species diversity and phylogenetic measures, which unite the traditional and microbial ecology. On the genus level, 45.10% and 41.18% of the water samples could be explained by the log-normal and Volkov model respectively, among which 31.37% could fit both models. Meanwhile, 55.56% of the sediment samples could be depicted by the log-normal model, and Volkov-fitted samples comprised only 13.33%. Besides, operational taxonomic units (OTUs) from water samples fit Sloan's neutral model significantly better than those in sediment. Therefore, it was concluded that deterministic processes played a great role in both water and sediment ecosystems, whereas neutrality was much more involved in water assemblages than in non-fluidic sediment ecosystems. Secondly, log-normal fitted samples had lower phylogenetic species variability (PSV) than Volkov-fitted ones, indicating that niche-based communities were more phylogenetically clustered than neutrally assembled counterparts. Additionally, further testing showed that the relative richness of rare species was vital to SAD modeling, either niche-based or neutral, and communities containing fewer rare species were more easily captured by theoretical SAD models. [ABSTRACT FROM AUTHOR]

Accidental epiphytism is common among vascular plants in forest ecosystems around the globe. A frequent observation in surveys of accidental epiphytes is the occurrence of few species with high epiphytic abundance, while most co-occurring terrestrial species are rarely found as epiphytes. Based on the general assumption that water is the major limiting factor for epiphytic plants, we hypothesised that differences in drought resistance of accidental epiphytes explain the difference in epiphytic abundances. We exposed 16 species with different epiphytic abundance in central Europe to experimentally induced drought during germination and growth of juvenile plants. Drought resistance differed substantially among species but did not correlate with their epiphytic abundance, neither during germination nor during juvenile growth. In central Europe, accidental epiphytes are usually found on moss cushions or in accumulated arboreal soil on their host tree. In such water-storing substrates, water availability might be less limiting than it is for obligate epiphytes that typically grow on bare bark, which would explain the lack of a correlation between drought resistance and epiphytic abundance of the studied species. Hence, other factors must explain the consistent differences in epiphytic abundance, e.g. dispersal traits and mass effect. [ABSTRACT FROM AUTHOR]

Recently, a 2018 study by Ulrich et al. introduced the Weibull distribution as a flexible approach to model the distribution of species abundances in ecological communities. They pointed to possible limitations in the realized parameter spaces of this distribution as possibly indicating ecological constraints on species abundances. Here, we explore this question in detail using three large global data sets on quantitatively assessed plant, invertebrate, and vertebrate communities. By fitting the Weibull distribution to these communities, we confirm that only a minor amount of the possible ranges in the scale and the shape parameters of the Weibull distribution are realized. Shapes of distributions become more similar across taxa with increasing species richness and average abundances. This finding points to stochastic explanations for species abundance shapes, possibly linked to local colonization and extinction dynamics. We introduce the Weibull survival time parameter as a way to define the proportion of rare species in a community. This proportion increased with increasing species richness. [ABSTRACT FROM AUTHOR]

Macroecological studies have established widespread patterns of species diversity and abundance in ecosystems but have generally restricted their scope to relatively steady‐state systems. As a result, how macroecological metrics are expected to scale in ecosystems that experience natural disturbance regimes is unknown. We examine macroecological patterns in a fire‐dependent forest of Bishop pine (Pinus muricata). We target two different‐aged stands in a stand‐replacing fire regime: a mature stand with a diverse understory and with no history of major disturbance for at least 40 yr, and one disturbed by a stand‐replacing fire 17 yr prior to measurement. We compare properties of these stands with macroecological predictions from the Maximum Entropy Theory of Ecology (METE), an information entropy‐based theory that has proven highly successful in predicting macroecological metrics in multiple ecosystems and taxa. Ecological patterns in the mature stand more closely match METE predictions than do data from the more recently disturbed, mid‐seral stage stand. This suggests METE's predictions are more robust in late‐successional, slowly changing, or steady‐state systems than those in rapid flux with respect to species composition, abundances, and organisms’ sizes. Our findings highlight the need for a macroecological theory that incorporates natural disturbance, perturbations, and ecological dynamics into its predictive capabilities, because most natural systems are not in a steady state. [ABSTRACT FROM AUTHOR]

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. • Species richness shifted with natural restoration in degraded karst forest, and remained stable after SG stage. • Contributions of components to species richness varies with natural restoration. • Observed Species richness were influenced by its sample size. [ABSTRACT FROM AUTHOR]

The various vegetation types in the karst landscape have been considered the results of heterogeneous habitats. However, the lack of a comprehensive understanding of regional biodiversity patterns and the underlying ecological processes limits further research on ecological management. This study established forest dynamic plots (FDPs) of the dominant vegetation types (shrubland, SL; mixed tree and shrub forest, MTSF; coniferous forest, CF; coniferous broadleaf mixed forest, CBMF; and broadleaf forest, BF) in the karst landscape and quantified the species diversity patterns and potential ecological processes. The results showed that in terms of diversity patterns, the evenness and species richness of the CF community were significantly lower than other vegetation types, while the BF community had the highest species richness. The other three vegetation types showed no significant variation in species richness and evenness. However, when controlling the number of individuals of FDPs, the rarefied species richness showed significant differences and ranked as BF > SL > MTSF > CBMF > CF, highlighting the importance of considering the impacts of abundance. Additionally, the community assembly of climax communities (CF or BF) was dominated by stochastic processes such as species dispersal or species formation, whereas deterministic processes (habitat filtering) dominated the secondary forests (SL, MTSF, and CBMF). These findings proved that community assembly differs mainly between the climax community and other communities. Hence, it is crucial to consider the biodiversity and of the potential underlying ecological processes together when studying regional ecology and management, particularly in heterogeneous ecosystems., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Meng, Li, Chen, Sui, Zhang, Liu, Chen, Wu, Yang, Chen, Yang and Zang.)

Aim: The interaction of land use with local versus regional processes driving biological homogenization (β‐diversity loss) is poorly understood. We explored: (a) stream β‐diversity responses to land cover (forest versus agriculture) in terms of physicochemistry and physicochemical heterogeneity; (b) whether these responses were constrained by the regional species pool, i.e. γ‐diversity, or local assembly processes through local (α) diversity; (c) whether local assembly operated through the regional species abundance distribution (SAD) or intraspecific spatial aggregation; and (d) the dependence on body size, dispersal capacity and trophic level (producer versus consumer). Location: USA, Canada and France. Time period: 1993–2012. Major taxa studied: Stream diatoms, insects and fish. Methods: We analysed six datasets totalling 1,225 stream samples. We compared diversity responses to eutrophication and physicochemical heterogeneity in forested versus agricultural streams with regression methods. Null models quantified the contribution of local assembly to β‐diversity (β‐deviance, βDEV) for both types of land covers and partitioned it into fractions explained by the regional SAD (βSAD) versus aggregation (βAGG). Results: Eutrophication explained homogenization and more uneven regional SADs across groups, but local and regional biodiversity responses differed across taxa. The βDEV was insensitive to land use. The βSAD largely exceeded βAGG and was higher in agriculture. Main conclusions: Eutrophication but not physicochemical heterogeneity of agricultural streams underlay β‐diversity loss in diatoms, insects and fish. Agriculture did not constrain the magnitude of local versus regional effects on β‐diversity but controlled the local assembly mechanisms. Although the SAD fraction dominated in both land covers, it increased further in agriculture at the expense of aggregation. Notably, the regional SADs were more uneven in agriculture, exhibiting excess common species or stronger dominance. Diatoms and insects diverged from fish in terms of biodiversity, SAD shape and βDEV patterns, suggesting an overriding role of body size and/or dispersal capacity compared with trophic position. [ABSTRACT FROM AUTHOR]

Questions: The cover and abundance of individual plant species have been recorded on ordinal scales for millions of plots world‐wide. Ordinal cover data often need to be transformed to a quantitative form (0%–100%), especially when scrutinising summed cover of multiple species. Traditional approaches to transforming ordinal data often assume that data are symmetrically distributed. However, skewed abundance patterns are ubiquitous in plant community ecology. The questions this paper addresses are (a) how can we estimate transformation values for ordinal data that account for the underlying right‐skewed distribution of plant cover; (b) do different plant groups require different transformations; and (c) how do our transformations compare to other commonly used transformations within the context of exploring the aggregate properties of vegetation? Location: Global. Methods: We assigned Braun‐Blanquet cover‐abundance ordinal values to continuous cover observations. We fitted a Bayesian hierarchical beta regression to estimate the predicted mean (PM) cover of each of six plant growth forms within six ordinal classes. We illustrate our method using a case study (2,809 plots containing 95,812 observations), compare the model‐derived estimates to other commonly used transformations and validate our model using an independent dataset (2,227 plots containing 51,497 observations) accessed through the VegBank database. Results: Our model found that PM estimates differed by growth form and that previous methods overestimated cover, especially of smaller growth forms such as forbs and grasses. Our approach reduced the cumulative compounding of errors and was robust when validated against an independent dataset. Conclusions: By accounting for the right‐skewed distribution of cover data, our alternate approach for estimating transformation values can be extended to other ordinal scales. A more robust approach to transforming floristic data and aggregating cover estimates can strengthen ecological analyses to support biodiversity conservation and management. [ABSTRACT FROM AUTHOR]