Species-area Relationship Models Research Articles

Environmental Factors Shape the Differences in Biodiversity-Area Relationships in Riverine Macroinvertebrates of Two Rivers in the Tibetan Plateau in China

The species-area relationship (SAR) is a well-established, globally recognized ecological pattern, and research on SAR has expanded to include the phylogenetic diversity-area relationship (PDAR). However, this research has generally been limited to terrestrial systems. Using data on freshwater macroinvertebrates, the log–log form of the SAR and PDAR power models were compared between the Lhasa River and the Niyang River on the Tibetan Plateau in China. The study reveals that there is a significant difference in the slopes of SAR and PDAR between the two rivers, with the Lhasa River having a considerably higher slope. The beta diversity calculations in these two basins support this pattern, with the Lhasa River exhibiting significantly higher numbers of species and greater total phylogenetic beta diversity than the Niyang River. Regarding species replacement, the turnover component was the primary driver of both species and phylogenetic beta diversity in both rivers. These differences in the beta diversity components were mainly driven by dispersal constraints because spatial distance had a large effect on total beta diversity and turnover fractions. In addition, the nestedness component was more affected by climate and land cover, indicating that highland rivers are subject to the threats of anthropogenic disturbance and climate change. Therefore, spatial factors play a crucial role in determining the distribution of passively dispersed benthic organisms as the scale of change in rivers increases from local to regional effects.

PREDICTING AND VERIFYING BUTTERFLY RICHNESS ON ISLANDS USING THE SPECIES AREA RELATIONSHIP: OTHONI (IONIAN ISLANDS) AS A CASE STUDY

We used the Species Area Relationship (SAR) (modelled with the power function) to predict the butterfly richness of Othoni, the westernmost Ionian island, (Greece), by comparing two datasets: one only based on literature data, and the other including new records. Although the SAR based on literature data indicated that butterfly richness for this island was already well sampled (nine species recorded against 7.3 predicted by the model), during a four-day fieldwork in August 2023 we spotted 11 previously unrecorded butterfly species. We discussed that the evaluation of the SAR was largely affected by under sampling of small islands while faunal inventories of large islands appeared almost complete. This was also reflected by a very high slope (z ≈ 0.5) and an intercept (c ≈ 2) which appears quite low for Mediterranean butterflies. A SAR model only including large islands and those showing richness above the 95% confidence interval revealed more trustworthy c and z values (0.3 and 8, respectively). We conclude that evaluating SAR parameters using literature data which did not originate from specifically planned research in archipelagos comprising small islands could return unreliable predictions. Moreover, we documented that the current faunal list of Othoni island can be considered sufficiently accurate to reliably include this island in wider biogeographical analyses. Key Words: Butterflies, Ionian islands, Othoni, Richness, Species area relationship.

The impact of the German timber footprint on potential species loss in supply regions

Previous own assessments have shown that a) Germany has a wood consumption above global average, b) is strongly dependent on imports and c) has a domestic roundwood production that is at the limit of the sustainable harvest potential. Thereby Germany further increases the pressures on global forests which are already stressed by climate-change related impacts and a continuously growing global demand for wood. This leads to negative impacts on the biodiversity in the areas where wood is harvested. This paper aims to show the connection between Germany's timber consumption footprint and the impact on the biodiversity in the regions where the roundwood is sourced. A two-step process is used. In the first step, high-resolution land cover and land use maps are used as a basis for the countryside species-area relationship model, assessing the projected loss of the four taxa amphibians, birds, mammals and reptiles in relation to undisturbed natural ecosystems due to forests occupied for roundwood production. In the second step, roundwood equivalents consumed in Germany in 2015 are traced back to the region of origin using an environmentally-extended input-output analysis and the thereby induced potential species loss is calculated. We show that the highest impact on projected species richness loss caused by roundwood logging is taking place in Oceania (3.34E−03 species/m3), Carribean (1.56E−04 species/m3), and East Asia (1.43E−04 species/m3). German roundwood consumption has the highest projected species loss in the United States (7.4 species), followed by China (7.3 species) and Brazil (4.8 species). From a biodiversity impact perspective, Germany could theoretically reduce its impact by relocating imports to European countries. In view of the planetary boundary of sustainable roundwood consumption, which has already been exceeded, reducing consumption appears to be the only viable long-term option for high-consumption countries such as Germany to reduce negative impacts on global biodiversity.

The relationship between naturalized alien and native plant species: insights from oceanic islands of the south-east Pacific over the last 200 years

Aim: The relationship between native and naturalized alien species has been widely studied, particularly across large geographic scales. However, our knowledge of the spatial and temporal variations of their relationships is still limited, particularly for remote oceanic islands such as those of the south-east Pacific and across islands and archipelagos. In this study, we aim to assess the relationships between native and naturalized alien species by analyzing their current patterns of species-area relationships at different spatial scales, in addition to temporal variations in species richness, over the last 200 years.Area: One island (Rapa Nui) and two archipelagos (Juan Fernandez and Desventuradas Islands) comprising a total of 11 oceanic islands of the south-east Pacific (OISEP).Methods: We assembled the most comprehensive dataset of the vascular flora of the OISEP from currently available island flora checklists and updated with recent publications. Each plant species was classified as being native or naturalized alien. We examined temporal changes by estimating species richness, naturalization rates and naturalized-to-native ratios over time based on the first collection year of each naturalized alien species. Then, we determined the best shape of naturalized alien species richness accumulation over time by contrasting the fit of lineal, exponential, sigmoidal and Weibull regressions. Finally, we analyzed the relationships between native and naturalized species firstly at the inter-archipelagic scale by fitting island species-area relationship models and secondly at the island scale by performing ranged major axis regression analysis on residual values.Results: The OISEP flora dataset contained 674 species of which 282 were native and 392 were naturalized alien. Native island species-area relationships were similar to those of the naturalized alien species. Naturalized alien species richness increased notably through time with two clear peaks in 1950 and 2000. A Weibull regression and an exponential shape over time were the most appropriate fits for naturalized alien species richness accumulations at the inter-archipelagic scale, which further emphasizes the notable increase in naturalized alien species richness experienced in the timeframe examined here.Main conclusions: The relationship between naturalized alien species richness and native species richness was found to be independent of the geographic scale. The number of naturalized alien species clearly exceeded the number of native species on most islands but also for the whole OISEP. The accumulation of newly detected naturalized alien species does not show any sign of saturation and it is likely that new species will arrive in the future. Increased efforts on monitoring, prevention and biosecurity are needed to halt biological invasions on these unique island ecosystems.

Microbial Species-Area Relationships on the Skins of Amphibian Hosts.

Unlike species-area relationships (SARs) that have been widely reported for plants and animals on Earth, there is no clear understanding of the SARs for microorganisms. In this study, 358 specimens of 10 amphibian host species collected from the rural Chengdu region of southwest China were selected as island models for evaluating SAR curve shapes and assessing the skin microbiota from different amphibian species. The results showed that skin microbial diversity, measured using Hill's number, presented significant differences between hosts, but the difference was insignificant between habitat-specific classifications of hosts. As for microbial SARs, other than the classical power-law (PL) model describing an expected steady increase in microbial diversity as sampled skin area increases, two additional trends were observed: (i) microbial diversity first rises and gradually decreases after reaching a maximum accrual diversity (MaxAD) and (ii) microbial diversity decreases and starts to rise after reaching the minimum accrual diversity (MinAD). Among the four SAR statistical models compared, it was consistently found that the models that can describe MaxAD were favorably selected in the highest frequency. Models that can describe MinAD and PL model also performed reasonably well. However, PL had the poorest fitting power, implying the necessity of introducing biologically meaningful complex SAR models in microbial diversity research. In conclusion, through multihost analyses, our study provided compelling evidence that microbial SARs are complex and nonlinear. A variety of ecological mechanisms may be used for explaining these, including, but not limited to, community saturation, small-island effects, or sampling heterogeneity. IMPORTANCE In this study, we investigate species-area relationships (SARs) for skin-borne symbiotic microbes of wildlife hosts. Unlike the traditional SARs for plants and animals, symbiotic microbial SARs were complex. We found that both U-shaped and inverted U-shaped SAR models were widely favored for microbial taxa than the well-known power-law model in different host species. These favored models presented interesting statistical features, including minimal or maximal accrual diversity or inflection point. We provide intuitive derivations of these statistical properties. We showed that different habitat-specific amphibian hosts did not present distinct microbial diversity and skin-related SAR patterns. We predicted that approximately 600 to 1,400 cm2 (in two-dimensional [2D] measurement) or approximately 1,200 to 3 500 cm2 (in 3D measurement) are the skin area threshold range that can allow the emergence of minimal or maximal accrual microbial diversity with high chances. Finally, we list a variety of ecological mechanisms that may be used for explaining the observed nonlinear SAR trends.

Generalized Logarithmic Species-Area Relationship Resolves the Arrhenius-Gleason Debate

The species-area relationship (SAR) is widely applied in ecology. Mathematically, it is usually expressed as either a semi-log or power-law relationship, with the former being introduced by Gleason and the latter by Arrhenius. We here resolve the dispute about which form of the SAR to prefer by introducing a novel model that smoothly transforms between the Gleason semi-log (GSL) and Arrhenius power law (APL) forms. The model introduced has the form of lnq (S) = a + z ln A, with lnq being a generalized logarithmic function, which is a linear map (y = x) for q = 0 and a logarithmic map (y = ln x) for q = 1 and q can take any intermediate value between 0 and 1. We applied this model to 100 datasets (mostly islands), linking species richness to island area. The APL was the preferred model in 68% of head-to-head comparisons with the GSL. Both models were supported in 40% of cases. In just under half (44%) of the cases, an intermediate model best explained the data. The results demonstrate the utility of a simple intermediate SAR model. Visualizing the profile of the range of model fits for all q ∈ [0, 1] (a q chart) allows us to gain extra insight into SARs not yielded by head-to-head comparisons of GSL and APL. The mathematics related to the generalized logarithmic function introduced here should have applications to other areas of ecological modelling.

Thresholds in the Species-Area-Habitat Model: Evidence from the Bryophytes on Continental Islands.

To clarify whether (1) there are thresholds in the species-area-habitat relationship for bryophytes and potential mechanisms, (2) such thresholds vary among different bryophyte groups, and (3) choros is better than area or habitat alone in the prediction of SR. Islands in central and southern Zhejiang, China. We investigated the species richness (SR) of five bryophyte groups (total bryophytes, total mosses, liverworts, acrocarpous mosses, and pleurocarpous mosses) and habitat types on 66 islands. By using four threshold models, the logarithmic and the power models, we quantified their SR-choros relationships (SKRs), species-area relationships (SARs), and species-habitat relationships (SHRs). We also conducted path analyses to detect the direct effects of area per se and habitat per se on the SR. The AICc values of the SKR models were overall smaller than those of the respective SAR and SHR models. The left-horizontal two-threshold model was best for the SKRs. A phenomenon (the small-choros effect, SCE) in which SR independently varied choros below a given threshold was detected. The SCE thresholds were smaller in mosses than in liverworts and in acrocarpous mosses than in pleurocarpous mosses. No direct and positive effects of habitat per se on the SR were detected below choros thresholds for all five groups. There were two thresholds and SCEs in the SKRs of all five bryophyte groups. The SCEs likely resulted from the elimination of the direct and positive effects of habitat diversity on the SR of the bryophytes on small choros islands. The SCE thresholds were high for species groups sensitive to environments. Choros was better than area or habitat alone in determining the SR of the bryophytes on continental islands.

Species Richness of Benthic Macrofauna on Rocky Outcrops in the Adriatic Sea by Using Species-Area Relationship (SAR) Tools

In the northern Adriatic Sea, rocky outcrops called “trezze” or “tegnúe” are known as biodiversity hotspots. A total of 45 rocky outcrops were studied by using non-destructive photographic sampling during SCUBA diving. Ten invertebrate phyla with 196 taxa were recorded, 86% of which were determined at species level. Among them, 65% of the taxa were sessile, primarily represented by the phyla Porifera and Chordata. The aims of the study were: to characterize the species richness and composition of epifaunal invertebrates living on rocky outcrops; to test the efficiency of using the outcrop area as a predictor of epifauna richness, using the Arrhenius Species-Area Relationship (SAR) model; and to compare the expected richness resulting from the SAR model with the richness observed from the analysis of random photo-squares. Our results show that the SAR model describes the relationship between epibenthic species richness and outcrop size well and may have important practical applications for biodiversity estimations and nature conservation implications. It provides a useful tool, also in terms of economy and speed, to estimate the species richness of the benthic epifauna of the numerous outcrops that remain unsurveyed, based on their size.

On the shape and origins of the freshwater species-area relationship.

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.

长白山暗针叶林群落物种多样性维持机制

PDF HTML阅读 XML下载 导出引用 引用提醒 长白山暗针叶林群落物种多样性维持机制 DOI: 10.5846/stxb202202210407 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目（32001312） Species diversity maintenance mechanism of dark coniferous forests community in Changbai Mountain Author: Affiliation: Fund Project: The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:植物群落物种多样性维持机制一直是生态学研究的热点话题，其中生态位理论和中性理论是被普遍接受的两种理论观点，但是目前关于生态位理论和中性理论在群落物种多样性维持中的相对重要性还没有统一定论。基于长白山暗针叶林群落数据，采用单物种-面积关系模型探究特定树种对邻域物种丰富度的影响，并借助同质性和异质性泊松零模型检验其显著性。（1）群落水平上，在3-15 m空间尺度上，促进种占据优势地位，在>15 m空间尺度上，中性种逐渐取代促进种起主导作用，抑制种比例较低，并且随着空间尺度变化幅度不大。（2）物种水平上，采用同质性泊松零模型检验树种对邻域物种丰富度的影响，臭冷杉、花楷槭、青楷槭在0-20 m空间尺度上对邻域物种丰富度增加起促进作用，黄花落叶松、鱼鳞云杉在0-20 m空间尺度上抑制了邻域物种丰富度增加。花楸树、黑桦和硕桦在全部研究尺度上表现为中性种，髭脉槭、大青杨、红松等在不同研究尺度上表现为不同的作用效果。剔除了生境过滤作用的异质性泊松零模型检验结果与同质性泊松零模型结果差异不显著，表明研究样地内生境过滤作用对多样性格局形成影响不大，各树种间的相互作用对群落物种组成影响较大，进一步证明了生态位理论能够解释长白山暗针叶林物种多样性维持。 Abstract:The maintenance mechanism of plant community species diversity has always been a hot topic in ecological research. Niche theory and neutral theory are two widely accepted theoretical viewpoints, but the relative importance of niche theory and neutral theory in the maintenance of community species diversity has not been unified. Based on the data of dark coniferous forest community in Changbai Mountain, this study used the individual species-area relationship model (ISAR) to explore the impacts of specific tree species on neighborhood species richness, and used homogeneity and heterogeneity Poisson zero model to test its significance. The results showed that:(1) at the community level, in the 3-15 m spatial scale, the promoting species occupied the dominant position. At scale >15 m, the neutral species gradually replaced the accumulators, the proportion of repellers species was low, and the change range with the spatial scale was small. (2) At the species level, the homogeneity Poisson zero model was used to test the influence of tree species on the neighborhood species richness. At the spatial scale of 0-20 m, Abies nephrolepis, Acer ukurunduense and Acer tegmentosum promoted the increase of species richness in the neighborhood, while Larix olgensis and Picea jezoensis inhibited the increase of neighborhood species richness. Sorbus pohuashanensis, Betula dahurica and Betula costata were neutral species at the scale of 0-20 m. Acer barbinerve, Populus cathayana, and Pinus koraiensis showed different effects on different scales. There was no significant difference between the results of heterogeneity Poisson null model excluding habitat filtering and homogeneous Poisson null model, indicating that habitat filtering had little effect on the formation of diversity pattern in the study plot. It was mainly due to the interaction between tree species contributed to the species composition structure of the community, which further proved that niche theory could explain the maintenance of species diversity in dark coniferous forest of Changbai Mountain. 参考文献 相似文献 引证文献

Structuring mechanism of tree species diversity pattern in an evergreen broadleaved forest in Con Dao National Park, Vietnam

The spatial structure of a community and the ecological mechanisms that control it are central themes in community ecology. This study aimed to investigate the ecological mechanisms driving the coexistence of tree species in the evergreen broadleaved forests in Con Dao National Park, Vietnam. We employed two null models: complete spatial randomness and inhomogeneous Poisson process within the framework of the individual species-area relationship model. The analyses focused on the effects of habitat filtering and species interactions. We discovered habitat heterogeneity in a 4-ha study plot that contained 5,653 tree individuals belonging to sixty-four plant families. The results demonstrated the critical role of habitat filtering and species interactions in maintaining species diversity within the plant community. The study also indicated that the local diversity structure of tree species depended on the spatial scale. This study went beyond niche and neutral theories by emphasizing the significance of ecological field theory and the principle of asymmetric competition in explaining the coexistence of tree species in evergreen broadleaved forests. Our findings may provide valuable insights into biodiversity conservation and the management of evergreen broadleaved forests, helping to improve further plant diversity conservation activities in the study area.

Detecting and comparing extinction debts of amphibians in different habitats of southwestern China

As a global biodiversity hotspot, southwestern China has been increasingly disturbed by human activities and has been undergoing rapid urbanization in recent years. In order to provide recommendations for conservation strategies, this paper explores the disequilibrium between land use and amphibian diversity. Four types of suitable habitat that are suitable for amphibians to inhabit (including farmland, woodland, grassland, and water habitat) were assessed and compared. Through fitting 20 models for species–area relationships (SARs), we found that different habitat types had different best-fitted SAR models. However, the conventional power law model had the advantage of being estimated without extreme values, and the estimation usually did not involve numerical problems. As such, we compared the debt mapping patterns derived from the best-fit SAR models and the power models. Regardless of the SAR models used, current amphibian richness was more strongly correlated with the past habitat area, suggesting that amphibian extinction debt existed in the region. Distribution of debt magnitude in different habitats presented congruent results: 1) The debt magnitude predicted in different habitats varied in decreasing order with grassland, water habitats, woodland, and farmland. 2) Debt magnitude in the region near the Chengdu Plain was high, while the extinction debt magnitude in the western region near the Qinghai-Tibet Plateau was low. This followed expectations, as there is a profound impact of human activities in the Chengdu Plain that threatens the survival of amphibian species in that area. In summary, our results suggest that some specific habitats (grasslands and water) and areas (Chengdu Plain) need greater conservation effort to better protect the habitats of amphibians and reduce the extinction risks of species.

Applicability of Common Algorithms in Species–Area Relationship Model Fitting

The species–area relationship (SAR) describes a law of species richness changes as the sampling area varies. SAR has been studied for more than 100 years and is of great significance in the fields of biogeography, population ecology, and conservation biology. Accordingly, there are many algorithms available for fitting the SARs, but their applicability is not numerically evaluated yet. Here, we have selected three widely used algorithms, and discuss three aspects of their applicability: the number of iterations, the time consumption, and the sensitivity to the initial parameter setting. Our results showed that, the Gauss–Newton method and the Levenberg–Marquardt method require relatively few iterative steps and take less time. In contrast, the Nelder–Mead method requires relatively more iteration steps and consumes the most time. Regarding the sensitivity of the algorithm to the initial parameters, the Gauss–Newton and the Nelder–Mead methods are more sensitive to the choice of initial parameters, while the Levenberg–Marquardt method is relatively insensitive to the choice of initial parameters. Considering that the Gauss–Newton method and the Levenberg–Marquardt method can only be used to fit smooth SAR models, we concluded that the Levenberg–Marquardt model is the best choice to fit the smooth SARs, while the Nelder–Mead method is the best choice to fit the non-smooth SARs.

Species loss from land use of oil palm plantations in Thailand

Expansion of oil palm plantation areas in Thailand, the world's third-largest oil palm producer, for food and fuel may sometimes encroach on forest areas, leading to biodiversity loss. Thailand is in the Indo-Burma biodiversity hotspot, which contains high species richness. This study assesses the impacts of oil palm plantations on bird and insect species richness from land use in the five regions of Thailand by using the countryside Species-Area Relationship model. Data from the Global Biodiversity Information Facility (GBIF) and Thailand’s Land Development Department (LDD) were used for species occurrence and land use data, respectively. This study focuses on the deforestation for oil palm because it poses the highest risk for wildlife compared to other habitats. The taxon affinity and regional characterization factors show the risk to wildlife (birds and insects) in the formerly natural habitat areas (i.e., deciduous, evergreen, and mangrove forests). The results show that the possibility of animal survival in former mangrove forests is higher than in other forests upon occupation, as demonstrated by the taxon affinity. Likewise, deforestation in the northern region causes the least species loss per area, as demonstrated by the lowest average regional characterization factor, because species densities are lowest. However, the impacts on species richness depend on the taxon and the combination of the region and the forest type. While the overall goal should be to minimize the expansion of oil palm, this study indicates in which forest type and Thai region land occupation causes less regional bird and insect species loss.

Global diversity of microbial communities in marine sediment

Microbial life in marine sediment contributes substantially to global biomass and is a crucial component of the Earth system. Subseafloor sediment includes both aerobic and anaerobic microbial ecosystems, which persist on very low fluxes of bioavailable energy over geologic time. However, the taxonomic diversity of the marine sedimentary microbial biome and the spatial distribution of that diversity have been poorly constrained on a global scale. We investigated 299 globally distributed sediment core samples from 40 different sites at depths of 0.1 to 678 m below the seafloor. We obtained ∼47 million 16S ribosomal RNA (rRNA) gene sequences using consistent clean subsampling and experimental procedures, which enabled accurate and unbiased comparison of all samples. Statistical analysis reveals significant correlations between taxonomic composition, sedimentary organic carbon concentration, and presence or absence of dissolved oxygen. Extrapolation with two fitted species-area relationship models indicates taxonomic richness in marine sediment to be 7.85 × 103 to 6.10 × 105 and 3.28 × 104 to 2.46 × 106 amplicon sequence variants for Archaea and Bacteria, respectively. This richness is comparable to the richness in topsoil and the richness in seawater, indicating that Bacteria are more diverse than Archaea in Earth's global biosphere.

Species–area relationship and small‐island effect of bryophytes on the Zhoushan Archipelago, China

AbstractAimThe species–area relationship (SAR) and the small‐island effect (SIE) are of important ecological significance. However, few studies have focused on these topics in regard to bryophytes. We aimed to (1) determine whether SIEs and a SAR with two thresholds and three different processes of species addition exist for bryophytes across continental islands and (2) test whether the SIE threshold tends to be high for stenoecious species with a high sensitivity to habitats and for those with relatively high resource requirements and low dispersal abilities.LocationThe Zhoushan Archipelago, China.TaxonBryophytes.MethodsWe obtained species number data for five bryophyte categories (total bryophytes, total mosses, acrocarpous mosses, pleurocarpous mosses and liverworts) from 66 continental islands of the archipelago and analysed the dataset using 24 SAR models. According to Akaike's information criterion, we identified models suitable for revealing SARs and detecting SIEs among the five bryophyte categories.ResultsThe power model was best for fitting SARs of all bryophyte categories except for pleurocarpous mosses. For detecting SIEs, the three‐segmented model provided the best support for the five categories. There were obvious SIEs for the five bryophyte groups, with area thresholds of 0.11–1.42 km2. The SIE threshold was much higher in liverworts than in mosses and in pleurocarpous mosses than in acrocarpous mosses. The second thresholds for the five categories were similar, ranging from 53.62 to 73.19 km2.Main conclusionsA unique SAR pattern with two area thresholds and three different dominant processes of species addition with island area was found for bryophytes across the continental islands. The second thresholds were not due to in situ speciation but were likely due to the high immigration of bryophytes from the mainland attributed to local residents. The SIE thresholds detected for the different categories of bryophytes indicated that the values tended to be low for species groups with low resource requirements and high dispersal abilities and high for those with a high sensitivity to habitat conditions, the latter indicating that areas for conservation purposes for species sensitive to habitats should be comparatively large.

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.

Genetic Diversity-Area Relationships across Bird Species.

The genetic diversity-area relationship (GAR), compared with the extensively explored species-area relationship (SAR), remains poorly recognized despite the importance of understanding it for the development and application of biodiversity theory. It has been hypothesized that maintaining genetic diversity within a population is mechanistically similar to maintaining species diversity within a community, implying that GAR trajectories should behave mathematically as SAR ones. Here we test this prediction by fitting microsatellite heterozygosity and allelic richness in relation to distribution range size across bird species against eight well-known SAR models. The Monod model best described the data on resident and migratory species combined and especially the data on resident species only, showing that with increasing range size, genetic diversity across species rapidly increased up to a certain level and then tended toward an asymptote. None of the candidate models provided an adequate fit for the data on migratory species, likely because their breeding range size mostly is large in that a GAR curve has become flat. Our work takes the first step toward formulating GARs and applying them to predicting the effect of habitat fragmentation on genetic diversity.

Latitude-enhanced species-area relationships for conservation planning

Species-area relationship models are useful in conservation planning; however these models could be strengthened with the addition of a latitudinal factor. We built latitude-enhanced species-area relationship models to predict species richness for a variety of common taxa in the eastern United States at local to regional scales. We used data from complete surveys of East Coast parks in the United States to build latitude-enhanced species-area relationship models for amphibians, birds, freshwater fish, mammals, marine fish, plants, and reptiles. We used data from the published literature and United States Fish and Wildlife Refuges to independently test the accuracy of the models. We demonstrated the utility of all modeled taxa within selected East Coast Protected Areas of the United States. Our models explained 35–91% of the variation in surveyed species richness, with marine fish, freshwater fish and reptile models exhibiting the strongest relationships (pseudo-R2 = 0.91, 0.66, and 0.70, respectively). Latitude had the strongest influence in the amphibian model. During accuracy testing, all taxa exhibited significant agreement between observed and predicted species richness and explained 75–97% of the variation. Our demonstration showed that for two similarly sized US Protected Areas, the parcel l.25° lower in latitude would likely have one more bird species, four more plant species, and an additional amphibian species. The latitude term added value to the species-area relationship models for most taxa and proved useful for conservation and urban planning in local to regional sized areas of the East Coast of the United States.

Species-area uncertainties impact the setting of habitat conservation targets and propagate across conservation solutions

Systematic Conservation Planning (SCP) is a widely-used approach to develop networks of protected areas. A crucial step in the SCP process is to set conservation targets for biodiversity features (explicit goals that quantify the minimum amount of each biodiversity feature to be covered by the protected areas). When the biodiversity features are different habitats occurring in the planning region, a relevant approach, based on the Species-Area Relationship (SAR), defines targets so as to maximize biodiversity representation within each habitat type. While many formulations of the SAR exist, their application remains dominated by the log-transformation of Power-law model. However, documented habitat-related and taxonomic idiosyncrasies in the shape of the SAR question the effectiveness of a given ubiquitous model in fitting data compared to others. Here, using 13 SAR functional forms, we investigate whether the habitat-related SAR uncertainties propagate across the entire conservation planning process and lead to both divergent conservation targets and conservation solutions for six habitats in the Mediterranean sea. Results revealed uncertainties in model selection across habitats, which leads to different SAR habitat-targets. Constraining a systemic conservation planning tool (Marxan) with those targets provided contrasted sets of priority areas for different SAR scenario. Our study demonstrated that restraining to one particular SAR model is inappropriate at fitting all SAR datasets, providing consequently conservation targets diverging markedly from data-driven SAR inferences. More importantly, corresponding reserve networks are either inefficient or overstated for the protection of habitats, leading to waste of scarce conservation resources that should be used sparingly. Therefore, we suggest to evaluate different SAR models and, when appropriate to carry out a multi-model inference to provide robust habitat-specific conservation targets.