Monitoring an Arizona Ponderosa Pine Restoration: Sampling Efficiency and Multivariate Analysis of Understory Vegetation

As monitoring plans for the restoration of Pinus ponderosa forests in the southwestern United States evolve toward examining multifactor ecosystem responses to ecological restoration, designing efficient sampling procedures for understory vegetation will become increasingly important. The objective of this study was to compare understory composition and diversity among thin/burn and control treatments in a P. ponderosa restoration, while simultaneously examining the effects of sampling design and multivariate analyses on which conclusions were based. Using multi‐response permutation procedures (MRPP), we tested the null hypothesis of no difference in understory species composition among treatments using different data matrices (e.g., frequency and cover) for two different sampling methods. Treatment differences were subtle and were detected by an intensive 50, 1‐m² subplot sampling method for all data matrices but were not detected by a less intensive point‐intercept sampling method for any matrix. Sampling methods examined in this study controlled results of multivariate analyses more than the data matrices used to summarize data generated by a sampling method. We partitioned data into plant life form and native/exotic species categories for MRPP, and this partitioning isolated plant groups most responsible for treatment differences. We also examined the effects of number of 1‐m² subplots sampled on mean‐species‐richness/m² estimates and found that estimates based on 10 subplots and based on 50 subplots were highly correlated (r = 0.99). Species–area curves indicated that the 50, 1‐m² subplot sampling method detected the common species of sites but failed to detect the majority of rare species. Additional sampling‐design studies are needed to develop single sampling designs that produce multifactor data on plant composition, diversity, and spatial patterns amenable to multivariate analyses as part of monitoring plans of vegetation responses to ecological restoration.     

Evaluating a sampling protocol for assessing plant diversity in prairie fens

Prairie fens are globally vulnerable wetlands that are considered a conservation priority due to threats to their high biodiversity and hydrological functions. Establishing a thorough and repeatable plant sampling protocol is critical to evaluating conservation and management initiatives. Our goal was to evaluate a sample methodology designed to assess prairie fen plant diversity and determine if it produced results (1) representative of site diversity, (2) comparable among fens, and (3) efficient to collect. Nineteen fens between 8.5 and 28.4 ha were surveyed twice within one growing season during 2012 and 2013 field seasons using an area-proportional, random design. The turnover in species between spring and summer sampling periods within a site ranged from 8 to 50 %. Sample coverage of total estimated plant species richness ranged from 84.8 to 95.0 % with a mean of 90.1 %. We compared results from our area-proportional, random design to simulated random samples of 10, 15, 20, 25, 30, 35 and 40 quadrats per site. No significant difference was found in sample coverage per fen when using sampling rates of 25, 30, or 35 quadrats per site versus the area-proportional design. Shannon’s diversity index and floristic quality index differed by sample period and number of quadrats sampled per fen. Our sample design produced acceptable levels of coverage and facilitated comparisons across fens. Our methodology could be applied to future research, restoration monitoring, and conservation planning efforts in Midwestern prairie fens.     

Are Plant Censuses Carried Out on Small Quadrats More Reliable than on Larger Ones?

Plant censuses are known to be significantly affected by observers’ biases. In this study, we checked whether the magnitude of observer effects (defined as the % of total variance) varied with quadrat size: we expected the census repeatability (% of the total variance that is not due to measurement errors) to be higher for small quadrats than for larger ones. Variations according to quadrat size of the repeatability of species richness, Simpson equitability and reciprocal diversity indices, Ellenberg indicator values, plant cover and plant frequency were assessed using 359 censuses of vascular plants. These were carried out independently by four professional botanists during spring 2002 on the same 18 forest plots, each comprising one 400-m² quadrat, four 4-m² and four 2-m² quadrats. Time expenditure was controlled for. General Linear Models using random effects only were applied to the ecological indices to estimate variance components and magnitude of the following effects (if possible): plot, quadrat, observer, plant species and two-way interactions. High repeatability was obtained for species richness and Ellenberg indicator values. Species richness and Ellenberg indicator values were generally more accurate but also more biased in large quadrats. Simpson reciprocal diversity and equitability indices were poorly repeatable (especially equitability) probably because plant cover estimates varied widely among observers, irrespective of quadrat size. Grouping small quadrats usually increased the repeatability of the variable considered (e.g. species richness, Simpson diversity, plant cover) but the number of plant species found on those pooled 16 m² was much lower than if large plots were sampled. We therefore recommend to use large, single quadrats for forest vegetation monitoring.     

Performance of nonparametric species richness estimators in a high diversity plant community

Abstract. The efficiency of four nonparametric species richness estimators — first‐order Jackknife, second‐order Jackknife, Chao2 and Bootstrap — was tested using simulated quadrat sampling of two field data sets (a sandy ‘Dune’ and adjacent ‘Swale’) in high diversity shrublands (kwongan) in south‐western Australia. The data sets each comprised > 100 perennial plant species and > 10 000 individuals, and the explicit (x‐y co‐ordinate) location of every individual. We applied two simulated sampling strategies to these data sets based on sampling quadrats of unit sizes 1/400th and 1/100th of total plot area. For each site and sampling strategy we obtained 250 independent sample curves, of 250 quadrats each, and compared the estimators’ performances by using three indices of bias and precision: MRE (mean relative error), MSRE (mean squared relative error) and OVER (percentage overestimation). The analysis presented here is unique in providing sample estimates derived from a complete, field‐based population census for a high diversity plant community. In general the true reference value was approached faster for a comparable area sampled for the smaller quadrat size and for the swale field data set, which was characterized by smaller plant size and higher plant density. Nevertheless, at least 15–30% of the total area needed to be sampled before reasonable estimates of S_t (total species richness) were obtained. In most field surveys, typically less than 1% of the total study domain is likely to be sampled, and at this sampling intensity underestimation is a problem. Results showed that the second‐order Jackknife approached the actual value of S_t more quickly than the other estimators. All four estimators were better than S_obs (observed number of species). However, the behaviour of the tested estimators was not as good as expected, and even with large sample size (number of quadrats sampled) all of them failed to provide reliable estimates. First‐ and second‐order Jackknives were positively biased whereas Chao2 and Bootstrap were negatively biased. The observed limitations in the estimators’ performance suggests that there is still scope for new tools to be developed by statisticians to assist in the estimation of species richness from sample data, especially in communities with high species richness.     

Efficient sampling of plant diversity in arid deserts using non-parametric estimators

Surveying plant diversity in arid desert areas is extremely difficult because of the harsh climate, hostile terrain, lack of roads, and insecurity, which is why it is particularly important to improve the sampling efficiency, but few relevant studies have been done. The performance of non-parametric estimators was assessed with first-hand field data to determine (a) the threshold of the proportion of uniques (number of species that occur in exactly one plot divided by the number of species sampled) that involves the least sampling effort and (b) the method of locating plots to obtain a more reliable estimate of species richness. The study area (Gurbantunggut desert, China) was divided into five sub-regions based on variation in physical environment and vegetation. The following common correction factors were selected: ACE, Chao1, Bootstrap, Chao2, ICE, Jack1, and Jack2. The estimates for each sub-region (partition) and for the entire region (without partition), the threshold of proportion of uniques, and the method of determining sampling locations (including prior sampling of plots that show large differences in habitats) were compared in terms of their ability to predict the number of species more accurately. We found that ACE and Chao1 (which use abundance data) showed more biased estimates than the other factors (incidence data), and best estimator is Jack1. Species richness was significantly underestimated for the region, but the non-parametric estimators could estimate the species richness for each sub-region reliably. Sampling locations affected the performance of non-parametric estimators significantly. The threshold of minimum sampling was 15% and that of uniques was 30%; the two were able to limit the bias within 5 and 10%, respectively. It is concluded that the non-parametric estimators can estimate the plant diversity of arid deserts reliably from the data on incidence. The study area (on the scale of a region) should be partitioned to improve the performance of the non-parametric estimators. The plots with larger differences in habitats should be sampled more extensively based on the threshold of the proportion of uniques.     

Non-random sampling and its role in habitat conservation: a comparison of three wetland macrophyte sampling protocols

Aquatic macrophytes provide essential spawning and nursery habitat for fish, valuable food source for waterfowl, migratory birds and mammals, and contribute greatly to overall biodiversity of coastal marshes of the Laurentian Great Lakes. Two approaches have been used to survey the plant community in coastal wetlands, and these include the grid (GR) and transect (TR) methods. These methods have been used to identify the average species richness at different sites, but their suitability for determining total species richness of a site has not been tested. In this paper, we compare the performance of these two established methods with that of the Stratified method (ST), which uses the sampler’s judgment to guide them to different habitat zones within the wetland. We used the three protocols to compare species richness of six coastal wetlands of the Great Lakes, three pristine marshes in eastern Georgian Bay (Lake Huron) and three degraded wetlands in Lake Ontario, Canada. The greatest species richness was associated with the ST method, irrespective of wetland quality. The ST method was also more efficient (fewer quadrats sampled), and revealed the most number of unique (those found with only one method) and uncommon species (those found in <5% of the quadrats). Despite these statistical differences, we found that sampling method did not significantly affect the performance of a recently developed index of wetland quality, the Wetland Macrophyte Index. These results have important implications for designing macrophyte surveys to track changes in biodiversity and wetland quality.     

Limited sampling hampers “big data” estimation of species richness in a tropical biodiversity hotspot

Macro‐scale species richness studies often use museum specimens as their main source of information. However, such datasets are often strongly biased due to variation in sampling effort in space and time. These biases may strongly affect diversity estimates and may, thereby, obstruct solid inference on the underlying diversity drivers, as well as mislead conservation prioritization. In recent years, this has resulted in an increased focus on developing methods to correct for sampling bias. In this study, we use sample‐size‐correcting methods to examine patterns of tropical plant diversity in Ecuador, one of the most species‐rich and climatically heterogeneous biodiversity hotspots. Species richness estimates were calculated based on 205,735 georeferenced specimens of 15,788 species using the Margalef diversity index, the Chao estimator, the second‐order Jackknife and Bootstrapping resampling methods, and Hill numbers and rarefaction. Species richness was heavily correlated with sampling effort, and only rarefaction was able to remove this effect, and we recommend this method for estimation of species richness with “big data” collections.     

Effects of an exotic invasive macrophyte (tropical signalgrass) on native plant community composition,species richness and functional diversity

1. The issue of freshwater species being threatened by invasion has become central in conservation biology because inland waters exhibit the highest species richness per unit area, but apparently have the highest extinctions rates on the planet. 2. In this article, we evaluated the effects of an exotic, invasive aquatic grass (Urochloa subquadripara– tropical signalgrass) on the diversity and assemblage composition of native macrophytes in four Neotropical water bodies (two reservoirs and two lakes). Species cover was assessed in quadrats, and plant biomass was measured in further quadrats, located in sites where tropical signalgrass dominated (D quadrats) and sites where it was not dominant or entirely absent (ND quadrats). The effects of tropical signalgrass on macrophyte species richness, Shannon diversity and number of macrophyte life forms (a surrogate of functional richness) were assessed through regressions, and composition was assessed with a DCA. The effects of tropical signalgrass biomass on the likelihood of occurrence of specific macrophyte life forms were assessed through logistic regression. 3. Tropical signalgrass had a negative effect on macrophyte richness and Shannon and functional diversity, and also influenced assemblage composition. Emergent, rooted with floating stems and rooted submersed species were negatively affected by tropical signalgrass, while the occurrence of free‐floating species was positively affected. 4. Our results suggest that competition with emergent species and reduction of underwater radiation, which reduces the number of submersed species, counteract facilitation of free‐floating species, contributing to a decrease in plant diversity. In addition, homogenisation of plant assemblages shows that tropical signalgrass reduces the beta diversity in the macrophyte community. 5. Although our results were obtained at fine spatial scales, they are cause for concern because macrophytes are an important part of freshwater diversity.     

Plant functional traits capture species richness variations along a flooding gradient

Local species coexistence is the outcome of abiotic and biotic filtering processes which sort species according to their trait values. However, the capacity of trait‐based approaches to predict the variation in realized species richness remains to be investigated. In this study, we asked whether a limited number of plant functional traits, related to the leaf‐height‐seed strategy scheme and averaged at the community level, is able to predict the variation in species richness over a flooding disturbance gradient. We further investigated how these mean community traits are able to quantify the strength of abiotic and biotic processes involved in the disturbance–productivity–diversity relationship. We thus tested the proposal that the deviation between the fundamental species richness, assessed from ecological niche‐based models, and realized species richness, i.e. field‐observed richness, is controlled by species interactions. Flooding regime was determined using a detailed hydrological model. A precise vegetation sampling was performed across 222 quadrats located throughout the flooding gradient. Three core functional traits were considered: specific leaf area (SLA), plant height and seed mass. Species richness showed a hump‐shaped response to disturbance and productivity, but was better predicted by only two mean community traits: SLA and height. On the one hand, community SLA that increased with flooding, controlled the disturbance‐diversity relationship through habitat filtering. On the other hand, species interactions, the strength of which was captured by community height values, played a strong consistent role throughout the disturbance gradient by reducing the local species richness. Our study highlights that a limited number of simple, quantitative, easily measurable functional traits can capture the variation in plant species richness at a local scale and provides a promising quantification of key community assembly mechanisms.     

Biogeography of vascular plants on habitat islands, peninsulas and mainlands in an eascentral Swedish agricultural landscape

The increase of island species richness with area can be explained by an increase in habitat diversity or by an equilibrium of species immigration and extinction. We examined vascular plant species richness in 39 sites (24 habitat islands, 7 'habitat peninsulas' and 8 comparable 'mainland' sites). We sampled at three scales: whole sites, meadows within sites and quadrats (4 m × 4 m) within meadows. All sites (10–10⁴ m²) contained natural vegetation within arable fields in eascentral Sweden. There was a strong correlation between species richness and area for whole sites and for meadows There was no correlation, however, between species richness in quadrats and site area. The difference between site and meadow results on one side and quadrat results on the other suggests that species richness increases with whole site area primarily because large sites are more diverse than smaller ones. Speciearea relationships did not differ between islands, peninsula and mainland sites. Thus, patterns of species richness on our sites were more consistent with habitat diversity than an immigratioextinction equilibrium.     

Factors affecting species diversity of plant communities and the restoration process in the loess area of China

The Loess Plateau of China is a special region that has suffered from soil erosion and water loss for a long time. Ecological restoration is an urgent task for this region. This study aims to characterize the variation in the vegetation restoration process on the abandoned croplands in the loess area. A series of quadrats were set up in different restoration stages in the Yancun watershed, Shanxi Province, an area of typical loess hills and gullies. Species and environmental data were recorded in each quadrat. Multivariate analysis and indices for species richness, diversity and evenness were used in the analysis. A series of plant community stages with different composition, structure and environments were identified by clustering analysis (UPGMA). These communities included three main restoration stages, grassland stage, scrubland stage and forest stage, and nine sub-stages, i.e. nine associations. Canonical correspondence analysis (CCA) showed that time since abandonment was the key factor for the restoration process, and the first CCA axis was effectively a time gradient. Elevation, soil type, slope and aspect were also important in the restoration process in the loess area. Species richness and diversity increased, and evenness decreased in the restoration process. The variation of species richness and diversity significantly correlated with time since abandonment, elevation and soil type. Time since abandonment is most important to the restoration process and species diversity is the main indicator of community changes in restoration in the Loess Plateau. For effective management, abandoned lands should be kept from disturbance.     

Relationships between landscape patterns and species richness of trees,shrubs and vines in a tropical forest

The present study aims to identify and characterize the relationships among landscape structure and plant diversity in a tropical landscape forest in Quintana Roo, Mexico. Total species richness as well as that of trees, shrubs and vines species were identified from 141 sampling quadrats (16,543 individuals sampled). Based on vegetation classes obtained from multi-spectral satellite image classification, I constructed plant diversity maps of the landscape under study using stratified kriging. I calculated the mean number of species in individual patches as the average values of kriging estimates inside of each patch. I then explored the relationships between landscape pattern metrics and the species richness of trees, shrubs and vines, as well as all groups combined using regression analysis. I employed Akaike Information Criterion (AIC) to select a set of candidate models. Based on akaike weights, I calculated model-averaged parameters. Results show that plant diversity of the patches depends on both the quality of the surrounding habitats and the proximity of surrounding patches (i.e., patch isolation).     

The Impact of Seeding Method on Diversity and Plant Distribution in Two Restored Grasslands

Previous studies have compared grassland restoration techniques based on resulting species richness and composition. However, none have determined if different techniques generate different plant distributions in space, which may further impact restoration success. This study tests if there are quadrat‐scale (1 m²) differences between paired drilled and broadcast plantings in diversity, composition, and plant distributions. Higher competition intensity in and more contiguous spaces between rows in drill‐seeded restorations were hypothesized to result in larger patches of native grasses and exotic species. Two paired drill‐ and broadcast‐seeded plantings were sampled in June 2007 in Iowa, U.S.A. Within 10 quadrats in each planting, we measured species abundance with point intercept sampling and plant distributions by dividing the quadrat into 64 cells and recording the most abundant species in each cell. Drilled and broadcast plantings at both sites had similar Simpson’s diversity and evenness. However, the effect of planting type on species richness, composition, and plant distribution was site dependent. Native warm‐season grasses in one site, and exotic species in the second, occupied more space and were distributed in larger patches in drilled plantings. Furthermore, drilled canopies consistently captured more light than broadcast canopies. This suggests that initial differences in seed placement can affect resulting plant distributions, resource use, and potentially long‐term species turnover. Mechanisms structuring vegetation in these communities need to be further investigated to determine if this approach can provide more information on long‐term diversity maintenance in restorations than traditional measures.     

In and out: Effects of shoot- vs. rooted-presence sampling methods on plant diversity measures in mountain grasslands

Plant diversity measures (e.g., alpha- and beta-diversity) provide the basis for a number of ecological indication and monitoring methods. These measures are based on species counts in sampling units (plots or quadrats). However, there are two alternative conventions for defining a vascular plant species as “present” in a plot, i.e. “shoot presence” (a species is recorded if the vertical projection of any above-ground part falls within the plot) and “rooted presence” (a species is recorded only when an individual is rooted inside the plot). Very few studies addressed the effects of the two sampling conventions on species richness and diversity indices. We sampled mountain dry grasslands in Italy across different plot sizes and vegetation types to assess how large is the difference in alpha- and beta-diversity values and in sample-based rarefaction curves between the two methods. We found that the difference is greatly dependent on plot size, being more relevant, both in absolute and percentage values, at smaller grain; it is also dependent on habitat type, being larger in shallow-soil communities, as they have a sparser vegetation structure and host life-form types with a larger lateral spread. At fine spatial scales (<1 m²) the difference is large enough to bias statistical inference, and we conclude that at such scales one should not attempt to compare plant diversity indices if they were not obtained with the same sampling convention.     

Recovery of mammal diversity in tropical forests: a functional approach to measuring restoration

Ecological restoration is increasingly applied in tropical forests to mitigate biodiversity loss and recover ecosystem functions. In restoration ecology, functional richness, rather than species richness, often determines community assembly, and measures of functional diversity provide a mechanistic link between diversity and ecological functioning of restored habitat. Vertebrate animals are important for ecosystem functioning. Here, we examine the functional diversity of small‐to‐medium sized mammals to evaluate the diversity and functional recovery of tropical rainforest. We assess how mammal species diversity and composition and functional diversity and composition, vary along a restoration chronosequence from degraded pasture to “old‐growth” tropical rainforest in the Wet Tropics of Australia. Species richness, diversity, evenness, and abundance did not vary, but total mammal biomass and mean species body mass increased with restoration age. Species composition in restoration forests converged on the composition of old‐growth rainforest and diverged from pasture with increasing restoration age. Functional metrics provided a clearer pattern of recovery than traditional species metrics, with most functional metrics significantly increasing with restoration age when taxonomic‐based metrics did not. Functional evenness and dispersion increased significantly with restoration age, suggesting that niche complementarity enhances species' abundances in restored sites. The change in community composition represented a functional shift from invasive, herbivorous, terrestrial habitat generalists and open environment specialists in pasture and young restoration sites, to predominantly endemic, folivorous, arboreal, and fossorial forest species in older restoration sites. This shift has positive implications for conservation and demonstrates the potential of tropical forest restoration to recover rainforest‐like, diverse faunal communities.     

Characterizing termite assemblages in fragmented forests: A test case in the Argentinian Chaco

Abstract Termites are major decomposers in tropical ecosystems. To characterize their assemblages in terms of taxonomical and functional composition, Jones and Eggleton (2000, Journal of Applied Ecology 37, 191–203) recently proposed a standardized sampling protocol based on belt transects of 100 m × 2 m. We evaluated the representativeness of samples obtained by this protocol, and its suitability to calculate diversity statistics, by replicating it in an area of naturally fragmented subtropical forest. We sampled six 100 m transects in separate small forest islets, and one transect extended to 500 m in a large islet, recording presence/absence data (occurrences) of termite species in successive quadrats of 5 m × 2 m. In the large islet, strips of 100 m within the 500 m transect produced extremely variable species richness figures. This variability was primarily due to heterogeneity in the spatial distribution of soil‐dwelling termites. Combining non‐contiguous quadrats allowed us to span a broader diversity of microhabitats for an equal effort, providing less variable results and faster species accumulation. Individual transects of 100 m in small forest islets yielded too few samples to allow reliable estimations of total species richness, although these transects when pooled constituted a useful data set for comparison with other sites. In the focal habitat, a single 100 m transect appeared therefore inadequate to allow a reliable characterization of the termite assemblage, even at the level of a single forest islet. To improve the rate of species accumulation and to obtain diversity statistics allowing intersite comparisons, we suggest the use of smaller, non‐contiguous quadrats, and that sampling be continued until stable diversity estimates are obtained. In the habitat studied, such an alternative protocol could be adequately combined with a standardized protocol for collecting ground‐dwelling ants.     

Species–area models to assess biodiversity change in multi-habitat landscapes: The importance of species habitat affinity

Species–area relationships (SARs) are a common tool to assess the impacts of habitat loss on species diversity. Species–area models that include habitat effects may better describe biodiversity patterns; also the shape of the SAR may be best described by other models than the classical power model. We compared the fit of 24 SAR models, i.e. eight basic models using three approaches: (i) single-habitat models, (ii) multi-habitat models which account for the effect of the habitat composition on total species diversity (= choros models) and (iii) multi-habitat models which also account for the differential use of habitats by different species groups (= countryside models). We use plant diversity data from a multi-habitat landscape in NW Portugal. Countryside models had the best fit both when predicting species–area patterns of species groups and of total species richness. Overall, choros models had a better fit than single-habitat models. We also tested the application of multi-habitat models to land-use change scenarios. Estimates of species richness using the choros model only depended on the number of habitats in the landscape. In contrast, for the countryside model, estimates of species richness varied continuously with the relative proportion of the different habitat types in the landscape, and projections suggest that land-use change impacts may be moderated by a species’ ability to use multiple habitats in the landscape. We argue that the countryside SAR is a better model to assess the impacts of land-use changes than the single-habitat SAR or the choros model, as species often face habitat change instead of real habitat loss, and species response to change is contingent on their differential use of habitats in the landscape.     

Are there pitfalls to pitfalls? Dung beetle sampling in French Guiana

Dung beetles have widely been accepted as cost-effective indicator taxa for biodiversity assessment; thus, standard protocols have been created to examine their species richness and diversity in many habitats. However, the vast majority of studies adopt short-term sampling protocols; few studies have quantified sampling efficiency at longer time scales or tested the efficacy of species richness estimates. Here we present long- and short-term sampling data from two regions of French Guiana: the Nouragues Tropical Forest Research Station and Kaw Mountain. We examine species richness and diversity, and use these data to make suggestions for future biodiversity assessments of dung beetles using dung baited pitfall transects. Species richness estimates based on short-term samples strongly underestimate the actual species richness by approximately 40?%. Duration of trapping was found to be more important than the number of traps and length of transects; by setting a second transect (4-day sample period) in the same habitat of Nouragues, thereby increasing the sample duration, the number of species increased by 14?%.     

Impacts of heavy grazing on plant species richness: A comparison across rangeland biomes of South Africa

The net effect of heavy grazing and land degradation on plant diversity and richness is insufficiently understood for incorporation in national biodiversity assessments. A study was undertaken to determine the effects of heavy grazing primarily on richness of vascular plant species across the arid and semi-arid rangeland biomes of South Africa. Major grazing contrasts were systematically identified for sampling in rangelands of Succulent Karoo, Nama-Karoo, Thicket, Grassland, Kalahari dune savanna and Mopane savanna. The related parameters of species diversity, evenness and turnover were also examined and analysed at the whole site level. The study represents a new site-level comparison of earlier individual studies that also necessitated recalculation and standardization of original data, where appropriate. Impacts of heavy grazing on plant species richness were found to vary from negligible or slightly positive to distinctly negative, depending on site. The sharp reductions in richness may have been associated with special secondary conditions that can occur in arid areas. Species diversity did not track species richness well and was often dominated by species evenness patterns. Moderate to substantial turnover of species occurred, even with negligible change in species richness. Species turnover was largely associated with replacement of species, except on one site where turnover was more evenly split between its replacement and nestedness components. Heavy grazing altered species composition on all study sites, usually with reduced grazing quality and favouring annual plants. Surprisingly few of the replacement species on most of the study areas were alien or exotic. Remarkably, the magnitude of change in species richness across the limited rainfall gradient of the study often greatly exceeded changes associated with the heavy grazing levels at each site. Use of the significant non-linear relationship found between loss of plant canopy cover through grazing and the relative decline in species richness needs further exploration.     

Should we use proportional sampling for species–area studies?

Aim In this paper we aim to show that proportional sampling can detect species–area relationships (SARs) more effectively than uniform sampling. We tested the contribution of alpha and beta diversity in ant communities as explanations for the SAR. Location Tropical forest remnants in Viçosa, Minas Gerais, Brazil (20 °45′ S, 42 °50′ W). Methods We sampled 17 forest remnants with proportional sampling. To disentangle sampling effects from other mechanisms, species richness was fitted in a model with remnant size, number of samples (sampling effects) and an interaction term. Results A SAR was observed independent of the number of samples, discarding sampling effects. Alpha diversity was not influenced by remnant size, and beta diversity increased with remnant size; evidence to the fact that habitat diversity within remnants could be the dominant cause of the SAR. Such a relationship between beta diversity and remnant area may have also arisen due to the combined effects of territoriality and aggregation of ant species. Main conclusions The proposed model, together with proportional sampling, allowed the distinction between sampling effects and other mechanisms.