Study on Species-area Relationships in the Southern and Northern Slopes of the Tianshan Mountains

The species–area relationship: an exploration of that ‘most general, yet protean pattern’¹

The species–area relationship (SAR) is one of the most general patterns in ecology. Recently, SARs have been employed as tools for comparing the ecology and biogeography of native and exotic species across spatial scales and exploring the influence of invasive species on native biodiversity. Here, we assess published studies to determine if SARs differ between native and exotic assemblages. We conducted a literature search to find studies that estimated the exponent (z) of the power-law SAR for native and exotic species across the same set of locales. We also compiled intercepts (c) of SARs where available. We used linear mixed models to test if z and c differed between native and exotic SARs and if this relationship differed across taxa. Our literature search produced 36 native-exotic pairs from 23 studies with which to compare the exponent of the power-law SAR. Further, SAR intercepts were available for 21 native-exotic pairs. Overall, exotic SAR exponents (z) did not differ from those of natives. However, this pattern did not hold across all taxonomic groups. Plant assemblages, which are best represented in our data (61% of total), mirrored the overall pattern showing no differences in exponents between native and exotic SARs. On the other hand, SAR exponents were greater for both native bird and animal assemblages. The intercepts (c) of native SARs were significantly greater than those of exotics for all taxa combined and for each individual taxonomic grouping. Our results suggest processes driving the increase in species richness with area are similar for native and exotic plant species, but not for animals. Expanding studies that compare SARs of native and exotic species to more taxonomic groups and different types of SARs (e.g., nested, contiguous, non-contiguous) will facilitate a better understanding of how native and exotic species richness scale with area.

Relative contribution of edge and interior zones to patch size effect on species richness: An example for woody plants

The relationship between sampled area and the number of species within that area, the species–area relationship (SAR), is a major biodiversity pattern and one of a few law‐like regularities in ecology. While the SAR for isolated units (islands or continents) is assumed to result from the dynamics of species colonization, speciation and extinction, the SAR for contiguous areas in which smaller plots are nested within larger sample areas can be attributed to spatial patterns in the distribution of individuals. The nested SAR is typically triphasic in logarithmic space, so that it increases steeply at smaller scales, decelerates at intermediate scales and increases steeply again at continental scales. I will review current theory for this pattern, showing that all three phases of the SAR can be derived from simple geometric considerations. The increase of species richness with area in logarithmic space is generally determined by overall species rarity, so that the rarer the species are on average, the higher is the local slope z. Rarity is scale‐dependent: species occupy only a minor proportion of area at broad spatial scales, leading to upward accelerating shape of the SAR at continental scales. Similarly, species are represented by only a few individuals at fine spatial scales, leading to high SAR slope also at small areas. Geometric considerations reveal links of the SAR to other macroecological patterns, namely patterns of β‐diversity, the species–abundance distribution, and the relationship between energy availability (or productivity) and species richness. Knowledge of the regularities concerning nested SARs may be used for standardizing unequal areas, upscaling species richness and estimating species loss due to area loss, but all these applications have their limits, which also follow from the geometric considerations.

The increase in species richness with area is known as the species–area relationship (SPAR). Although several mutually non-exclusive processes may produce the SPAR, the null, often ignored, hypothesis states that a SPAR can be generated by random placement alone. The log–log-transformed SPAR of coral reef fishes on small patch-reefs revealed a steep slope of 0.55. However, this slope was dependent on the cumulative area of the reef examined and was therefore affected by random placement. After statistically removing the contribution of random placement from the SPAR, the slope was estimated to be 0.21. This is consistent with estimates from other, mostly terrestrial, systems. Furthermore, a randomization procedure, where the probability of fishes to reach a patch was proportional to reef area, showed that the field measured SPAR did not differ from random placement. In addition, fish assemblages on species poor reefs did not form subsets of species rich reefs (i.e., no nestedness) beyond that expected from random placement. Steep log–log-transformed SPARs can be formed by random placement alone, indicating that caution should be used when assigning an ecological meaning to SPARs generated from small spatial scales.

ABSTRACTUnlike 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.

The species–area relationship (SAR) is the oldest and most frequently documented law in ecology. In a community, the SAR is regulated by the abiotic environment and biotic interactions and depends on the individual–spatial distribution of species (ISD) and the species–abundance distribution (SAD). In this study, we explored the effects of aggregation of ISDs and unevenness of SADs on SARs in forests of China by comparing the empirical and simulated SARs of 32 nested plots distributed along an extensive latitudinal gradient. Both aggregation and unevenness affected the shape of SARs significantly: ISDs accounted for 12.6 ± 4.0% of the incremental increase in species richness with area, and SADs accounted for 18.7 ± 3.8 and 23.5 ± 3.9% under the broken‐stick model and even abundance model, respectively. Effects of both aggregation and unevenness decreased as temperature increased, suggesting that individuals of a species were spatially more aggregated than random, and the individuals among species were more discrepant from the null distribution (broken‐stick model and even abundance model in this study), in the cold than in the warm areas. Taken together, our results demonstrate that ISDs and SADs within communities can shape SARs, but these effects vary along latitudinal gradients, and are likely mediated by temperature.

One of the few general patterns in ecology is the increase of species richness with area. However, factors driving species-area relationship (SAR) are under debate, and the role of human-induced changes has been overlooked so far. Furthermore, SAR studies in tropical regions, in particular in multilayered rain forests are scarce. On the other side, studies of global change-induced impacts on biodiversity have become increasingly important, particular in the tropics, where these impacts are especially pronounced. Here, we investigated if area modulates the effect of land use, elevation and canopy on plant species richness. For the first time we studied SAR in multilayered tropical forests considering all functional groups. We selected 13 natural and disturbed habitats on Kilimanjaro in Tanzania, distributed over an elevational range of 3700 m. In each habitat type, we set up three to six modified Whittaker plots. We recorded all plant species in 64 plots and 640 subplots and described SAR using the power function. Area consistently modulated effects of elevation on plant species richness, partly effects of land use but not effects of plant canopy. Thus, area needs to be taken into account when studying elevational plant species richness patterns. In contrast to temperate regions open and forest habitats did not differ in SAR, probably due to a distinct vertical vegetation zonation in tropical forests. Therefore, it is important to consider all vegetation layers including epiphytes when studying SAR in highly structured tropical regions.

Evaluating the effect of habitat diversity on the species-area relationship using land-bridge islands in Thousand Island Lake, China.

Land-use change remains a major driver of biodiversity loss, and projecting extinction rates for different scenarios of habitat conversion is a key concern in conservation research (Pereira et al. 2010; Wright 2010; de Baan et al. 2013). Species–area relationships (SARs) have been one of the main models used to develop such projections, but they have been criticized recently for overestimating extinctions (He & Hubbell 2011). One problem is that classic projections are based on the assumption that all natural areas converted to human-dominated areas, such as agriculture and forestry, become completely hostile to biodiversity (Pereira et al. 2012). However, there is a growing recognition that many species are not constrained to fragments of their native habitat and that the matrix can play an important role in the conservation of biodiversity (Prugh et al. 2008; Karp et al. 2012). Recently a comparison of 2 models that incorporate the wider landscape context, the countryside SAR (Pereira & Daily 2006) and the matrix-calibrated SAR was conducted by Koh and Ghazoul (2010). Here we show that the results of that comparison are incorrect and that in contrast with their results, the countryside SAR outperforms both the matrix-calibrated SAR and classic SAR projections in projecting tropical bird extinctions. To compare the performance of different species–area models in projecting species extinctions, Koh and Ghazoul examined birds in 20 biodiversity hotspots in the world. For each hotspot they estimated the proportion of native habitat remaining and the proportion converted to disturbed forest, agricultural land, and urban area. For each hotspot, they estimated the number of species extinct or threatened with extinction as all endemic bird species in each hotspot classified as extinct, critically endangered, endangered, or vulnerable by the IUCN. Threatened species are included because they are expected to become extinct when species richness reaches an equilibrium with the amount of remaining habitat. Next they estimated sensitivities, σj, and affinities, hj, through the use of a database of studies of how many species disappear locally when natural habitat is converted to each type of human-dominated landscape. This shows that affinities and sensitivities are related because . Unfortunately, Koh and Ghazoul calculated the affinities simply as and ignored the exponent z. Using this incorrect calculation of affinities they found that the best projections of endemic bird extinctions are with the matrix model, followed by the classic SAR, and that the countryside SAR has the worst performance. We recalculated the projections of extinction rates with the data from Koh and Ghazoul, the z value they used (0.35), and the correct estimate of habitat affinities. We found that the countryside SAR outperformed both the matrix-calibrated SAR and the classic SAR in this data set (Table 1, Fig. 1). There might be other data sets where the matrix-calibrated SAR outperforms the countryside SAR; more research is needed to compare the different SAR models. The countryside SAR is particularly suitable to describe diversity patterns in multi-habitat landscapes even when the original cover or species composition is not known. The results of 2 recent studies show that the performance of the countryside SAR is better than the classic SAR in describing bird (Guilherme & Pereira 2013) and plant (Proenca & Pereira 2013) diversity in such landscapes.

ABSTRACTAims We examine the role of species–area relationships (SARs), climatic parameters and phylogeny in shaping the altitudinal species richness patterns of moths. With respect to SARs, we investigate whether habitat heterogeneity is a probable mechanism for mediating area effects. We investigate the consistency of patterns by comparing several discrete regions.Location Nine mountainous regions in tropical Asia and the Malay Archipelago.Methods Presence‐only records for 292 species of the Lepidopteran family Sphingidae were used to measure interpolated species richness in 200‐m altitudinal bands. Species richness was correlated with area measures, which were calculated from both two‐dimensional map projections and three‐dimensional digital elevation models (DEMs). We used data simulations of homogeneous communities to test for effects of sample (i.e. habitat) heterogeneity as a mechanism causing SARs. Species richness patterns were compared among regions and between the two major sphingid clades, and were related to regional climatic characteristics.Results The area of altitudinal bands was a strong (statistical) explanation of species richness, particularly if area was calculated from three‐dimensional DEMs, but SARs often over‐predict species richness in lowland areas. There was no evidence for habitat heterogeneity as a mechanism of altitudinal SARs (tested for Borneo only). Species richness patterns varied considerably between the nine regions, which may, as an alternative to SARs, be explained by climatic differences such as (temperature) seasonality. Phylogenetic clades differed in species richness patterns exhibited.Main conclusion SARs provide strong empirical explanations for (regional) altitudinal patterns of species richness, but lack of evidence for the most likely mechanism cautions against a priori ‘corrections’ of species richness data for area. Furthermore, SARs are often not a sufficient explanation for the drop in species richness towards lowlands. Climate, or other collinear variables, may offer alternative explanations for altitudinal SARs. More research is needed to understand the mechanisms for SARs in an altitudinal context in order to evaluate their importance in the face of parameter collinearity.

AimThe positive relationship between species richness and area—the species–area relationship (SAR)—is a key principle in ecology. Previous studies show large variation in the SAR across taxa collectively indicating the necessity of a taxon‐focused approach to accurately evaluate biodiversity scaling patterns. Ants are ideal for this given their global distribution and role in ecosystem functioning. Using data from insular ant communities, this study quantified and investigated various attributes of ant SARs and reviewed the SAR literature for ant faunas, world‐wide, to identify specific areas for improvement.LocationIslands around the world.TaxonAnts (Hymenoptera: Formicidae).MethodsWe aggregated data on species richness and island characteristics from previous studies on ant SARs to evaluate effects of climate, biogeographic realm, and latitude on slope values from these studies. A multimodel inference approach was used to determine the form of the different SARs, and whether there were any differences between mainland and insular SARs. We also assessed differences between mainland and insular SAR slopes and intercepts. To seek a general slope coefficient for ants, we used a mixed‐effect model. Finally, we tested for potential thresholds in the global insular SAR using piecewise regression models.ResultsThere was a negative relationship between SAR slopes and precipitation in both mainland and insular SARs, while SAR slopes and intercept values were higher in mainland compared to insular systems. Strong evidence of thresholds emerged in the global insular SAR. Finally, a general slope of 0.16 was observed for insular systems, which is lower than found in previous studies.Main ConclusionsA taxon‐focused approach proves to showcase unexpected patterns in the SAR. Ant diversity increases faster across area in mainland areas compared to true islands. The influences of climate and biogeographic realms on the ant SAR warrant deeper study. Our review highlights knowledge gaps in the ant SAR that also extend to other taxa, such as the effects of nonnative species on the SAR.

The species-area relationship (SAR), describing the increase in species richness with increasing area, and the latitudinal diversity gradient (LDG), describing the decrease in species richness with increasing latitude, are the oldest and most robust patterns in biogeography, yet connections between them remain poorly understood. Here, using 1,742 floras covering the entirety of North America north of Mexico (NAM) and including all of NAM's native species of vascular plants, we show that the slope of the SAR consistently decreases with increasing latitude. This trend is general and holds for subsets of the floras in eastern and western NAM. The southernmost latitudinal quarter of NAM exhibits SARs more than twice as steep as those of the northernmost quarter for both eastern and western regions. This decrease in SAR slope with increasing latitude is consistent with the environmental texture hypothesis and Rapoport's rule, and it suggests that more detailed studies of species endemism in relation to environmental and historical factors will yield significant insights into the underlying causes of SAR and LDG patterns.

We used a probabilistic approach to address the influence of sampling ar- tifacts on the form of species-area relationships (SARs). We developed a model in which the increase in observed species richness is a function of sampling effort exclusively. We assumed that effort depends on area sampled, and we generated species-area curves under that model. These curves can be realistic looking. We then generated SARs from avian data, comparing SARs based on counts with those based on richness estimates. We used an approach to estimation of species richness that accounts for species detection probability and, hence, for variation in sampling effort. The slopes of SARs based on counts are steeper than those of curves based on estimates of richness, indicating that the former partly reflect failure to account for species detection probability. SARs based on estimates reflect eco- logical processes exclusively, not sampling processes. This approach permits investigation of ecologically relevant hypotheses. The slope of SARs is not influenced by the slope of the relationship between habitat diversity and area. In situations in which not all of the species are detected during sampling sessions, approaches to estimation of species richness integrating species detection probability should be used to investigate the rate of increase in species richness with area.

The species‐area relationship (SAR), describing the increase in species richness with increasing area, and the latitudinal diversity gradient (LDG), describing the decrease in species richness with increasing latitude, are the oldest and most robust patterns in biogeography, yet connections between them remain poorly understood. Here, using 1,742 floras covering the entirety of North America north of Mexico (NAM) and including all of NAM’s native species of vascular plants, we show that the slope of the SAR consistently decreases with increasing latitude. This trend is general and holds for subsets of the floras in eastern and western NAM. The southernmost latitudinal quarter of NAM exhibits SARs more than twice as steep as those of the northernmost quarter for both eastern and western regions. This decrease in SAR slope with increasing latitude is consistent with the environmental texture hypothesis and Rapoport’s rule, and it suggests that more detailed studies of species endemism in relation to environmental and historical factors will yield significant insights into the underlying causes of SAR and LDG patterns.