模拟植物多样性的大尺度分布：从气候和生产力推知的一种可能性（英文）

 鉴于全球植被/生物群区在现状气候条件下已经被很好地模拟并在未来气候变化情景下得到很好的预测,人们有必要和急需模拟大尺度（区域、洲际至全球）植物多样性的分布格局。陆地生物圈模型的发展（从生物地理模型和生物地球化学模型到动态和耦合的植被模型）,气候-生物多样性相互关系和生产力-生物多样性相互关系研究成果的增多,以及基于现有生物多样性调查的全球生物多样性理论和经验制图的进步,加大了模拟大尺度植物多样性格局的可能性。本文的目的是：综述当前气候-生物多样性相互关系和生产力-生物多样性相互关系的主要研究成果以及大尺度     

Do Stacked Species Distribution Models Reflect Altitudinal Diversity Patterns?

The objective of this study was to evaluate the performance of stacked species distribution models in predicting the alpha and gamma species diversity patterns of two important plant clades along elevation in the Andes. We modelled the distribution of the species in the Anthurium genus (53 species) and the Bromeliaceae family (89 species) using six modelling techniques. We combined all of the predictions for the same species in ensemble models based on two different criteria: the average of the rescaled predictions by all techniques and the average of the best techniques. The rescaled predictions were then reclassified into binary predictions (presence/absence). By stacking either the original predictions or binary predictions for both ensemble procedures, we obtained four different species richness models per taxa. The gamma and alpha diversity per elevation band (500 m) was also computed. To evaluate the prediction abilities for the four predictions of species richness and gamma diversity, the models were compared with the real data along an elevation gradient that was independently compiled by specialists. Finally, we also tested whether our richness models performed better than a null model of altitudinal changes of diversity based on the literature. Stacking of the ensemble prediction of the individual species models generated richness models that proved to be well correlated with the observed alpha diversity richness patterns along elevation and with the gamma diversity derived from the literature. Overall, these models tend to overpredict species richness. The use of the ensemble predictions from the species models built with different techniques seems very promising for modelling of species assemblages. Stacking of the binary models reduced the over-prediction, although more research is needed. The randomisation test proved to be a promising method for testing the performance of the stacked models, but other implementations may still be developed.     

GAM模型和BRT模型在长江口鱼类群落多样性预测中的比较

长江口为西太平洋最大的河口,评估其鱼类群落多样性分布能够为长江口生态系统的修复和管理提供科学依据.本研究基于2012—2014年长江口渔业监测数据,分别使用GAM模型和BRT模型建立各站点水域鱼类群落多样性指数与环境和时空因子之间的关系.结合线性回归方程,采用交叉验证的方式对模型的预测能力和拟合效果进行评价,并绘制了2014年长江口鱼类群落多样性指数和丰富度指数的空间分布图.结果表明: 盐度、pH和叶绿素a对多样性指数贡献最高,pH、溶解氧和叶绿素a是对丰富度指数贡献率最高的环境因子.BRT模型对于多样性指数和丰富度指数的拟合和预测结果均优于GAM模型.空间分布预测显示,相较于GAM模型,BRT模型能够对长江口小面积水域间的鱼类群落多样性作更好的区分,河口外侧水域的鱼类群落多样性明显高于河口内侧水域,而北支水域的多样性高于南支水域.     

Benthic diversity patterns in oxygenation gradients: an example from the Middle Jurassic of Switzerland

Etter, W. 1995 11 30 Benthic diversity patterns in oxygenation gradients: an example from the Middle Jurassic of Switzerland.
A high-resolution study of the lower Opalinum Clay (Aalenian, Middle Jurassic) of northern Switzerland revealed a pattern of macrobenthic diversity and abundance which does not conform with the dysaerobic-biofacies models currently in use. The upper dysoxic zone contains an association of moderate diversity and moderate abundance which, with increasing oxygen depletion, is replaced by an association dominated by a few peak opportunists (tiny epibenthic bivalves and presumably small annelids) at high abundances but very low diversity. In the lower dysoxic zone, abundance drops to very low levels, but diversity rises again to quite high values. The rather high diversity of the lower dysaerobic biofacies is explained in part by the presence of specialized chemosymbiontic species. The pattern documented in the lower Opalinum Clay has been calibrated by sedimentologic, taphonomic, ichnologic, and microfaunal evidence. It contradicts equilibrium models, which postulate gradual or even linear decreases in both abundance and diversity with increasing oxygen-depletion of the bottom water. The equation of rising diversity with improved oxygenation can be misleading and can yield erroneous results in the reconstruction of ancient bottom-water oxygenation. □ Dysaerobic biofacies, high-resolution study, diversity, chemosymbionts, equilibrium and non-equilibrium models .     

Primary productivity is weakly related to floristic alpha and beta diversity across Australia

Aim Ecosystem functions such as productivity may be influenced not only by the biological diversity at each location (α‐diversity) but also by the biological turnover between locations (β‐diversity). We perform a continental‐scale test of the strength and direction of relationships between gross primary productivity (GPP) and both α‐ and β‐diversity. Location Continental Australia. Methods Species occurrence records were used to quantify the taxonomic α‐diversity of vascular plants in approximately 11,000 1 km × 1 km grid cells across Australia, and to calculate the average β‐diversity within a 10‐km radius around each cell. The magnitude and variability of monthly, MODIS‐derived remotely sensed GPP (2001–12) were summarized for continental Australia, as were rainfall and temperature over the same period. Generalized additive models were then used to test whether the magnitude or variability of GPP were distinctly influenced by either biodiversity measure, over and above the influence of environmental conditions. Results Precipitation and temperature explained large proportions of deviance in the magnitude (75.6%) and variability (38.3%) of GPP across the Australian continent. GPP was marginally more strongly related to species richness than it was to species turnover. However, neither diversity measure provided substantial increases in the explanatory power of GPP models over and above that of environment‐only models (always < 1%). Main conclusions The relationship between primary productivity and taxonomic α‐ and β‐diversity was weak for the Australian flora. Our findings question the generality of key assumptions, predictions and results in the literature regarding the strength of empirical relationships between productivity and biodiversity across multiple biological levels (α‐, β‐ and γ‐diversity) at macroecological scales.     

Predicting alpha diversity of African rain forests: models based on climate and satellite‐derived data do not perform better than a purely spatial model

Aim Our aim was to evaluate the extent to which we can predict and map tree alpha diversity across broad spatial scales either by using climate and remote sensing data or by exploiting spatial autocorrelation patterns. Location Tropical rain forest, West Africa and Atlantic Central Africa. Methods Alpha diversity estimates were compiled for trees with diameter at breast height ≥ 10 cm in 573 inventory plots. Linear regression (ordinary least squares, OLS) and random forest (RF) statistical techniques were used to project alpha diversity estimates at unsampled locations using climate data and remote sensing data [Moderate Resolution Imaging Spectroradiometer (MODIS), normalized difference vegetation index (NDVI), Quick Scatterometer (QSCAT), tree cover, elevation]. The prediction reliabilities of OLS and RF models were evaluated using a novel approach and compared to that of a kriging model based on geographic location alone. Results The predictive power of the kriging model was comparable to that of OLS and RF models based on climatic and remote sensing data. The three models provided congruent predictions of alpha diversity in well‐sampled areas but not in poorly inventoried locations. The reliability of the predictions of all three models declined markedly with distance from points with inventory data, becoming very low at distances > 50 km. According to inventory data, Atlantic Central African forests display a higher mean alpha diversity than do West African forests. Main conclusions The lower tree alpha diversity in West Africa than in Atlantic Central Africa may reflect a richer regional species pool in the latter. Our results emphasize and illustrate the need to test model predictions in a spatially explicit manner. Good OLS or RF model predictions from inventory data at short distance largely result from the strong spatial autocorrelation displayed by both the alpha diversity and the predictive variables rather than necessarily from causal relationships. Our results suggest that alpha diversity is driven by history rather than by the contemporary environment. Given the low predictive power of models, we call for a major effort to broaden the geographical extent and intensity of forest assessments to expand our knowledge of African rain forest diversity.     

A New Approach to Diversity Indices – Modeling and Mapping Plant Biodiversity of Nallihan (A3-Ankara/Turkey) Forest Ecosystem in Frame of Geographic Information Systems

Modeling and mapping possibilities of Shannon–Wiener, Simpson, and number of species (NS) indices were researched using geographic information systems (GIS) and remote sensing (RS) tools in Nallihan forest ecosystem of Turkey. The relationships between the indices and a number of independent variables such as topography, geology, soil, climate, normalized difference vegetation index (NDVI), and land cover were investigated to understand relationships between plant diversity and ecosystem. Georeferenced field data from the established 56 quadrats (50 × 20 m) were used to calculate the indices. Principle component analysis (PCA) and multiple regression were employed for data reduction and model development, respectively. Three diversity maps were produced using the developed models. Residual maps and logical interpretations in ecological point of view were used to test the validity of the models. Elevation and climatic factors formed the most important components that are effective determinants of plant species diversity, but geological formations, soil, land cover and land-use characteristics also influenced plant diversity. Considering the different responses of the models, Shannon–Wiener (SWI) and NS models were found suitable for rare cover types, while Simpson (SIMP) model might be appropriate for single dominant land covers in the study area.     

A hierarchical perspective of plant diversity

Predictive models of plant diversity have typically focused on either a landscape's capacity for richness (equilibrium models), or on the processes that regulate competitive exclusion, and thus allow species to coexist (nonequilibrium models). Here, we review the concepts and purposes of a hierarchical, multiscale model of the controls of plant diversity that incorporates the equilibrium model of climatic favorability at macroscales, nonequilibrium models of competition at microscales, and a mixed model emphasizing environmental heterogeneity at mesoscales. We evaluate the conceptual model using published data from three spatially nested datasets: (1) a macroscale analysis of ecoregions in the continental and western U.S.; (2) a mesoscale study in California; and (3) a microscale study in the Siskiyou Mountains of Oregon and California. At the macroscale (areas from 3889 km2 to 638,300 km2), climate (actual evaporation) was a strong predictor of tree diversity (R2 = 0.80), as predicted by the conceptual model, but area was a better predictor for vascular plant diversity overall (R2 = 0.38), which suggests different types of plants differ in their sensitivity to climatic controls. At mesoscales (areas from 1111 km2 to 15,833 km2), climate was still an important predictor of richness (R2 = 0.52), but, as expected, topographic heterogeneity explained an important share of the variance (R2 = 0.19) showed positive correlations with diversity of trees, shrubs, and annual and perennial herbs, and was the primary predictor of shrub and annual plant species richness. At microscales (0.1 ha plots), spatial patterns of diversity showed a clear unimodal pattern along a climate-driven productivity gradient and a negative relationship with soil fertility. The strong decline in understory and total diversity at the most productive sites suggests that competitive controls, as predicted, can override climatic controls at this scale. We conclude that this hierarchical, multiscale model provides a sound basis to understand and analyze plant species diversity. Specifically, future research should employ the principles in this paper to explore climatic controls on species richness of different life forms, better quantify environmental heterogeneity in landscapes, and analyze how these large-scale factors interact with local nonequilibrium dynamics to maintain plant diversity.     

Diverse pathways of oxidative folding of disulfide proteins: underlying causes and folding models

The pathway of oxidative folding of disulfide proteins exhibits a high degree of diversity, which is manifested mainly by distinct structural heterogeneity and diverse rearrangement pathways of folding intermediates. During the past two decades, the scope of this diversity has widened through studies of more than 30 disulfide-rich proteins by various laboratories. A more comprehensive landscape of the mechanism of protein oxidative folding has emerged. This review will cover three themes. (1) Elaboration of the scope of diversity of disulfide folding pathways, including the two opposite extreme models, represented by bovine pancreatic trypsin inhibitor (BPTI) and hirudin. (2) Demonstration of experimental evidence accounting for the underlying mechanism of the folding diversity. (3) Discussion of the convergence between the extreme models of oxidative folding and models of conventional conformational folding (framework model, hydrophobic collapse model).     

Effects of species diversity on disease risk

The transmission of infectious diseases is an inherently ecological process involving interactions among at least two, and often many, species. Not surprisingly, then, the species diversity of ecological communities can potentially affect the prevalence of infectious diseases. Although a number of studies have now identified effects of diversity on disease prevalence, the mechanisms underlying these effects remain unclear in many cases. Starting with simple epidemiological models, we describe a suite of mechanisms through which diversity could increase or decrease disease risk, and illustrate the potential applicability of these mechanisms for both vector-borne and non-vector-borne diseases, and for both specialist and generalist pathogens. We review examples of how these mechanisms may operate in specific disease systems. Because the effects of diversity on multi-host disease systems have been the subject of much recent research and controversy, we describe several recent efforts to delineate under what general conditions host diversity should increase or decrease disease prevalence, and illustrate these with examples. Both models and literature reviews suggest that high host diversity is more likely to decrease than increase disease risk. Reduced disease risk with increasing host diversity is especially likely when pathogen transmission is frequency-dependent, and when pathogen transmission is greater within species than between species, particularly when the most competent hosts are also relatively abundant and widespread. We conclude by identifying focal areas for future research, including (1) describing patterns of change in disease risk with changing diversity; (2) identifying the mechanisms responsible for observed changes in risk; (3) clarifying additional mechanisms in a wider range of epidemiological models; and (4) experimentally manipulating disease systems to assess the impact of proposed mechanisms.     

Species diversity and genetic diversity: parallel processes and correlated patterns

Species diversity and genetic diversity may be correlated as a result of processes acting in parallel at the two levels. However, no theories predict the conditions under which different relationships between species diversity and genetic diversity might arise and therefore when one level of diversity may be predicted using the other. I used simulation models to investigate the parallel influence of locality area, immigration rate, and environmental heterogeneity on species diversity and genetic diversity. The most common pattern was moderate to strong positive species-genetic diversity correlations (SGDCs). Such correlations may be driven by any one of the three locality characteristics examined, but important exceptions and patterns emerged. Genetic diversity and species diversity were more weakly correlated when genetic diversity was measured for rare versus common species. Environmental heterogeneity not only imposes spatially varying selection on populations and communities but also causes changes in species' population sizes and therefore genetic diversity; these interacting processes can create positive, negative, or unimodal relationships of genetic diversity with species diversity. When species are considered as part of multispecies communities, predictions from single-species models of genetic diversity apply in some instances (effects of area and immigration) but often not in others (effects of environmental heterogeneity).     

Highly diverse community structure in a remote central Tibetan geothermal spring does not display monotonic variation to thermal stress

We report an assessment of whole-community diversity for an extremely isolated geothermal location with considerable phylogenetic and phylogeographic novelty. We further demonstrate, using multiple statistical analyses of sequence data, that the response of community diversity is not monotonic to thermal stress along a gradient of 52-83 degrees C. A combination of domain- and division-specific PCR was used to obtain a broad spectrum of community phylotypes, which were resolved by denaturing gradient gel electrophoresis. Among 58 sequences obtained from microbial mats and streamers, some 95% suggest novel archaeal and bacterial diversity at the species level or higher. Moreover, new phylogeographic and thermally defined lineages among the Cyanobacteria, Chloroflexi, Eubacterium and Thermus are identified. Shannon-Wiener diversity estimates suggest that mats at 63 degrees C supported highest diversity, but when alternate models were applied [Average Taxonomic Distinctness (AvTD) and Variation in Taxonomic Distinctness (VarTD)] that also take into account the phylogenetic relationships between phylotypes, it is evident that greatest taxonomic diversity (AvTD) occurred in streamers at 65-70 degrees C, whereas greatest phylogenetic distance between taxa (VarTD) occurred in streamers of 83 degrees C. All models demonstrated that diversity is not related to thermal stress in a linear fashion.     

Mid-domain models as predictors of species diversity patterns: bathymetric diversity gradients in the deep sea

Geometric constraints represent a class of null models that describe how species diversity may vary between hard boundaries that limit geographic distributions. Recent studies have suggested that a number of large scale biogeographic patterns of diversity (e.g. latitude, altitude, depth) may reflect boundary constraints. However, few studies have rigorously tested the degree to which mid-domain null predictions match empirical patterns or how sensitive the null models are to various assumptions. We explore how variation in the assumptions of these models alter null depth ranges and consequently bathymetric variation in diversity, and test the extent to which bathymetric patterns of species diversity in deep sea gastropods, bivalves, and polychaetes match null predictions based on geometric constraints.
Range–size distributions and geographic patterns of diversity produced by these null models are sensitive to the relative position of the hard boundaries, the specific algorithms used to generate range sizes, and whether species are continuously or patchily distributed between range end points. How well empirical patterns support null expectations is highly dependent on these assumptions. Bathymetric patterns of species diversity for gastropods, bivalves and polychaetes differ substantially from null expectations suggesting that geometric constraints do not account for diversity–depth patterns in the deep sea benthos.     

Environmental fluctuations and the maintenance of genetic diversity in age or stage-structured populations

The ability of random fluctuations in selection to maintain genetic diversity is greatly increased when generations overlap. This result has been derived previously using genetic models with very special assumptions about the population age structure. Here we explore its robustness in more realistic population models, with very general age structure or physiological structure. For a range of genetic models (haploid, diploid, single and multilocus) we find that the condition for maintaining genetic diversity generalizes almost without change. Genetic diversity is maintained by selection if a product of the form (generation overlap)×(selection intensity)×(variability in the selection regime) is sufficiently large, where the generation overlap is measured in units of Fisher's reproductive value. This conclusion is based on a local evolutionary stability analysis, which differs from the standard “protected polymorphism” criterion for the maintenance of genetic diversity. Simulation results match the predictions from the local stability analysis, but not those from the protected polymorphism criterion. The condition obtained here for maintaining genetic diversity requires fitness fluctuations that are substantial but well within the range observed in many studies of natural populations.     

Tree diversity on islands: assembly rules,passive sampling and the theory of island biogeography

Aim Species diversity is distributed heterogeneously through space, for reasons that are poorly understood. We tested three hypotheses to account for spatial variation in coniferous tree species diversity in a temperate island archipelago. The theory of island biogeography (ToIB) predicts that island area affects species diversity both directly (by increasing habitat diversity) and indirectly (by increasing abundances, which in turn reduce extinction rates). The ToIB also predicts that island isolation directly affects species diversity by reducing immigration rates. The passive sampling hypothesis predicts that island area and isolation both affect species diversity indirectly, by increasing and decreasing abundances, respectively. Community assembly rules (i.e. even partitioning of conifer abundances among islands) might also reduce tree species diversity beyond the core predictions of ToIB and the passive sampling hypothesis. Location Barkley Sound, British Columbia, Canada. Methods The abundances of eight coniferous tree species were quantified on 34 islands and two (1 ha) mainland plots. The predictions of the ToIB and the passive sampling hypothesis were tested using path analysis, and null models were used to test for abundance‐based assembly rules and to further test the passive sampling hypothesis. Results Path analysis showed that island area and isolation did not have direct, statistical effects on tree species diversity. Instead, both geographic variables had direct statistical effects on total tree abundances, which in turn predicted tree diversity. Results from several passive sampling null models were correlated with observed patterns in species diversity, but they consistently overestimated the number of tree species inhabiting most islands. A different suite of null models showed support for community assembly rules, or that tree species often reached higher abundances on islands that housed fewer heterospecific trees. Main conclusions Results were inconsistent with the ToIB. Instead, patterns in tree diversity were best explained by a combination of stochastic (passive sampling) and deterministic (assembly rules) processes. Stochastic and deterministic processes are commonly considered to be exclusive explanations for island community structure, but results from this study suggest that they can work synergistically to structure island tree communities.     

From diversity indices to community assembly processes: a test with simulated data

Ecological theory suggests that spatial distribution of biodiversity is strongly driven by community assembly processes. Thus the study of diversity patterns combined with null model testing has become increasingly common to infer assembly processes from observed distributions of diversity indices. However, results in both empirical and simulation studies are inconsistent. The aim of our study is to determine with simulated data which facets of biodiversity, if any, may unravel the processes driving its spatial patterns, and to provide practical considerations about the combination of diversity indices that would produce significant and congruent signals when using null models. The study is based on simulated species’ assemblages that emerge under various landscape structures in a spatially explicit individual‐based model with contrasting, predefined assembly processes. We focus on four assembly processes (species‐sorting, mass effect, neutral dynamics and competition colonization trade‐off) and investigate the emerging species’ distributions with varied diversity indices (alpha, beta and gamma) measured at different spatial scales and for different diversity facets (taxonomic, functional and phylogenetic). We find that 1) the four assembly processes result in distinct spatial distributions of species under any landscape structure, 2) a broad range of diversity indices allows distinguishing between communities driven by different assembly processes, 3) null models provide congruent results only for a small fraction of diversity indices and 4) only a combination of these diversity indices allows identifying the correct assembly processes. Our study supports the inference of assembly processes from patterns of diversity only when different types of indices are combined. It highlights the need to combine phylogenetic, functional and taxonomic diversity indices at multiple spatial scales to effectively infer underlying assembly processes from diversity patterns by illustrating how combination of different indices might help disentangling the complex question of coexistence.     

Structural and taxonomic diversity predict above-ground biomass better than functional measures of maximum height in mixed-species forests

Aims: Mixed-species forests are known to be highly productive systems because of their high species diversity, including taxonomic diversity (species richness) and structural diversity. Recent empirical evidence also points to plant maximum height, as a functional trait that potentially drives forest above-ground biomass (AGB). However, the interrelations between these biotic variables are complex, and it is not always predictable if structural diversity attributes or functional metrics of plant maximum height would act as the most important determinant of stand biomass. Here we evaluated the relative importance of structural diversity attributes and functional metrics of plant maximum height (Hmax) in predicting and mediating AGB response to variation in species richness in mixed-species forests, while also accounting for fine-scale environmental variation. Location: Northern Benin. Methods: We used forest inventory data from mixed-species stands of native and exotic species. We quantified structural diversity as coefficient of variation of tree diameter at breast height (CVdbh) and of height (CVHt). For plant Hmax, we computed three metrics: functional range (FRHmax), functional divergence (FDHmax) and community-weighted mean (CWMHmax). We used topographical variables such as elevation and slope to account for possible environmental effects. Simple and multiple mixed-effects models, and structural equation models were performed to assess the direct and indirect links of AGB with species richness through structural diversity attributes and functional metrics of plant Hmax. Results: Species richness and CVdbh were positively related to AGB, while functional metrics of plant Hmax were not. Structural equation models revealed that species richness influenced AGB indirectly via CVdbh, which alone strongly promoted AGB. Elevation only had a positive direct effect on AGB. While increasing species richness enhanced CVdbh and functional measures of plant Hmax, there was no support for the latter mediating the effects of species richness on AGB. Conclusion: Structural diversity has a significant advantage in predicting and mediating the positive effect of species richness on AGB more so than functional measures of plant Hmax. We argue that structural diversity acts as a mechanism for the species richness–AGB relationship, and that maintaining high structural diversity would enhance biomass in mixed-species forests.     

Range size in mid-domain models of species diversity

Geographical patterns of species diversity have been examined using mid-domain null models, in which the ranges of individual species are simulated by randomly arranging them on a bounded one- or two-dimensional continent. These models have shown that structured patterns in the geographical distribution of biodiversity can arise even under a fully stochastic procedure. In particular, mid-domain models have demonstrated that the random generation of ranges of different sizes and locations can produce a gradient of species diversity similar to the one found in real assemblages, with a peak at the middle of a continent. A less explored feature of mid-domain models is the pattern of range-size frequency distribution. Numerical simulations have provided some insights about the geographic pattern of average range size, but no exploration of the shape of range-size frequency distributions has been carried out. Here I present analytical and numerical models that generate explicit predictions for patterns of range size under the assumptions of mid-domain models of species diversity. Some generalizations include: (1) Mid-domain models predict no geographic gradient of average range size; the mean range size of species occurring at any point on a continent is constant (0.5 of the extent of the continent in the one-dimensional model, 0.25 of the area of the continent in the two-dimensional case); (2) Variance in range size is lowest at the middle of a continent and highest near the corners of a square-shaped continent; (3) The range-size frequency distribution is highly right-skewed at any point of a continent, but the skewness is highest near the corners. Despite their alleged weaknesses, mid-domain models are adequate null models against which real-world patterns can be contrasted.     

Putting the plants back into plant ecology: six pragmatic models for understanding and conserving plant diversity

BACKGROUND: There is a compelling need to protect natural plant communities and restore them in degraded landscapes. Activities must be guided by sound scientific principles, practical conservation tools, and clear priorities. With perhaps one-third of the world's flora facing extinction, scientists and conservation managers will need to work rapidly and collaboratively, recognizing each other's strengths and limitations. As a guide to assist managers in maintaining plant diversity, six pragmatic models are introduced that are already available. Although theoretical models continue to receive far more space and headlines in scientific journals, more managers need to understand that pragmatic, rather than theoretical, models have the most promise for yielding results that can be applied immediately to plant communities. SIX PRAGMATIC MODELS: For each model, key citations and an array of examples are provided, with particular emphasis on wetlands, since "wet and wild" was my assigned theme for the Botanical Society of America in 2003. My own work may seem rather prominent, but the application and refinement of these models has been a theme for me and my many students over decades. The following models are reviewed: (1) species-area: larger areas usually contain more species; (2) species-biomass: plant diversity is maximized at intermediate levels of biomass; (3) centrifugal organization: multiple intersecting environmental gradients maintain regional landscape biodiversity; (4) species-frequency: a few species are frequent while most are infrequent; (5) competitive hierarchies: in the absence of constraints, large canopy-forming species dominate patches of landscape, reducing biological diversity; and (6) intermediate disturbance: perturbations such as water level fluctuations, fire and grazing are essential for maintaining plant diversity. CONCLUSIONS: The good news is that managers faced with protecting or restoring landscapes already have this arsenal of tools at their disposal. The bad news is that far too few of these models are appreciated.     

High speciation rate at temperate latitudes explains unusual diversity gradients in a clade of ectomycorrhizal fungi

Understanding the patterns of biodiversity through time and space is a challenging task. However, phylogeny‐based macroevolutionary models allow us to account and measure many of the processes responsible for diversity buildup, namely speciation and extinction. The general latitudinal diversity gradient (LDG) is a well‐recognized pattern describing a decline in species richness from the equator polewards. Recent macroecological studies in ectomycorrhizal (EM) fungi have shown that their LDG is shifted, peaking at temperate rather than tropical latitudes. Here we investigate this phenomenon from a macroevolutionary perspective, focusing on a well‐sampled group of edible EM mushrooms from the genus Amanita—the Caesar's mushrooms, which follow similar diversity patterns. Our approach consisted in applying a suite of models including (1) nontrait‐dependent time‐varying diversification (Bayesian analysis of macroevolutionary mixtures [BAMM]), (2) continuous trait‐dependent diversification (quantitative‐state speciation and extinction [QuaSSE]), and (3) diversity‐dependent diversification. In short, results give strong support for high speciation rates at temperate latitudes (BAMM and QuaSSE). We also find some evidence for different diversity‐dependence thresholds in “temperate” and “tropical” subclades, and little differences in diversity due to extinction. We conclude that our analyses on the Caesar's mushrooms give further evidence of a temperate‐peaking LDG in EM fungi, highlighting the importance and the implications of macroevolutionary processes in explaining diversity gradients in microorganisms.