Species Abundance Data Research Articles

Reconciling empirical interactions and species coexistence.

Coexistence in ecological communities is governed largely by the nature and intensity of species interactions. Countless studies have proposed methods to infer these interactions from empirical data, yet models parameterised using such data often fail to recover observed coexistence patterns. Here, we propose a method to reconcile empirical parameterisations of community dynamics with species-abundance data, ensuring that the predicted equilibrium is consistent with the observed abundance distribution. To illustrate the approach, we explore two case studies: an experimental freshwater algal community and a long-term time series of displacement in an intertidal community. We demonstrate how our method helps recover observed coexistence patterns, capture the core dynamics of the system, and, in the latter case, predict the impacts of experimental extinctions. Collectively, these results demonstrate an intuitive approach for reconciling observed and empirical data, improving our ability to explore the links between species interactions and coexistence in natural systems.

Spatio-temporal variability of phytoplankton assemblages and its controlling factors in spring and summer in the Subei Shoal of Yellow Sea, China

The Subei Shoal is a special coastal area with complex physical oceanographic properties in the Yellow Sea. In the present study, the distribution of phytoplankton and its correlation with environmental factors were studied during spring and summer of 2012 in the Subei Shoal of the Yellow Sea. Phytoplankton species composition and abundance data were accomplished by Utermohl method. Diatoms represented the greatest cellular abundance during the study period. In spring, the phytoplankton cell abundance ranged from 1.59×103 to 269.78×103 cell/L with an average of 41.80×103 cell/L, and Skeletonema sp. and Paralia sulcata was the most dominant species. In summer, the average phytoplankton cell abundance was 72.59×103 cell/L with the range of 1.78×103 to 574.96×103 cell/L, and the main dominant species was Pseudo-nitzschia pungens, Skeletonema sp., Dactyliosolen fragilissima and Chaetoceros curvisetus. The results of a redundancy analysis (RDA) showed that turbidity, temperature, salinity, pH, dissolved oxygen (DO), the ratio of dissolved inorganic nitrogen to silicate and SiO4-Si (DIN/SiO4-Si) were the most important environmental factors controlling phytoplankton assemblages in spring or summer in the Subei Shoal of the Yellow Sea.

Plant community strategies responses to recent eruptions of Popocatépetl volcano, Mexico

AbstractQuestionsWhat are the mechanisms operating behind the plant community structure changes over time after lahars activity of Popocatépetl volcano? We hypothesize that functional diversity matters more than species richness and that, after major disturbances, the pioneer plant community will first show a ruderal composition, that subsequently changes into successional stages in which competitive and stress‐tolerating species become dominant life‐forms. We expect this process to be revealed by the community's functional signature.LocationPopocatépetl volcano in Mexico (19°1′0″N, 98°37′0″W) which has undergone large eruptive activity that has caused lahars formation.MethodsIn 2002, survey plots were established in the bottom of the Huilóac gorge. Species composition and abundance data were thereafter collected for 10 years. In 2013, data on three functional traits leaf area (LA), leaf dry matter content and LA of 67 species were obtained and each species was assigned to a strategy according to the CSR (Competitive, Stress‐Tolerant or Ruderal) scheme. A community‐functional signature was calculated for each year. Also, a parallel ordination of plots strategies composition in time was performed to confirm functional shift trends.ResultsInitial successional phases were dominated by ruderal and competitive species. Thereafter, the communities went through a phase of increasing heterogeneity of strategies, which was followed by dominance of competitive and stress‐tolerant strategists in the later years. Parallel ordination confirmed the gradient of functional differentiation through time.ConclusionsThe change from ruderal/competitive to stress‐tolerant and competitive species with time suggests that the most recent lahar event played a major role in sorting species according to their tolerance for disturbances. Thereafter, a major trend has been the gradual shift from ruderal to stress‐tolerant species (conifers and alpine grasses).

Dominant tree species drive beta diversity patterns in western Amazonia.

The forests of western Amazonia are among the most diverse tree communities on Earth, yet this exceptional diversity is distributed highly unevenly within and among communities. In particular, a small number of dominant species account for the majority of individuals, whereas the large majority of species are locally and regionally extremely scarce. By definition, dominant species contribute little to local species richness (alpha diversity), yet the importance of dominant species in structuring patterns of spatial floristic turnover (beta diversity) has not been investigated. Here, using a network of 207 forest inventory plots, we explore the role of dominant species in determining regional patterns of beta diversity (community-level floristic turnover and distance-decay relationships) across a range of habitat types in northern lowland Peru. Of the 2,031 recorded species in our data set, only 99 of them accounted for 50% of individuals. Using these 99 species, it was possible to reconstruct the overall features of regional beta diversity patterns, including the location and dispersion of habitat types in multivariate space, and distance-decay relationships. In fact, our analysis demonstrated that regional patterns of beta diversity were better maintained by the 99 dominant species than by the 1,932 others, whether quantified using species-abundance data or species presence-absence data. Our results reveal that dominant species are normally common only in a single forest type. Therefore, dominant species play a key role in structuring western Amazonian tree communities, which in turn has important implications, both practically for designing effective protected areas, and more generally for understanding the determinants of beta diversity patterns.

Spatio-temporal variation in marine fish traits reveals community-wide responses to environmental change

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 610:205-222 (2019) - DOI: https://doi.org/10.3354/meps12826 Spatio-temporal variation in marine fish traits reveals community-wide responses to environmental change Esther Beukhof*, Tim S. Dencker, Laurene Pecuchet, Martin Lindegren Centre for Ocean Life, National Institute of Aquatic Resources (DTU Aqua), 2800 Kongens Lyngby, Denmark *Corresponding author: estb@aqua.dtu.dk ABSTRACT: Marine ecosystems are exposed to a range of environmental and anthropogenic stressors, including climate change and overexploitation. A promising way towards understanding the impacts of such stressors on community composition is by considering species traits rather than species identity. Here, we describe the spatio-temporal dynamics in fish community traits using >30 yr of species abundance data from the North Sea combined with trait information on body size, life history, growth rate, reproduction and trophic level for demersal fish species in the area. We assessed whether the derived patterns and trends in community-weighted mean traits could be explained by a range of environmental stressors and fishing. Our results revealed strong spatial structuring and long-term changes in the trait composition of North Sea fish, with temporal changes not being uniformly distributed in space. Among the environmental drivers investigated, depth was one of the best predictors, primarily explaining the spatial variation in lifespan, growth rate, trophic level and fecundity. This can be explained by variables that co-vary with depth, e.g. temperature, seasonality, salinity and productivity. Finally, we found only weak relationships between fishing and the spatial variation of traits, suggesting that the spatial trait composition of the community is mostly determined by the environment. Yet, long-term changes in trait composition, primarily in body size, have previously been shown to be affected by size-selective fishing. Our study exemplifies how traits can be used to summarize complex community dynamics and responses to environmental and anthropogenic stressors as well as their usefulness for ecosystem-based management. KEY WORDS: Marine fish · Traits · Spatio-temporal · Community weighted mean · North Sea · Community composition · Climate change · Fishing Full text in pdf format Supplementary material PreviousCite this article as: Beukhof E, Dencker TS, Pecuchet L, Lindegren M (2019) Spatio-temporal variation in marine fish traits reveals community-wide responses to environmental change. Mar Ecol Prog Ser 610:205-222. https://doi.org/10.3354/meps12826 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 610. Online publication date: February 01, 2019 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2019 Inter-Research.

Modelling spatial biodiversity in the world’s largest mangrove ecosystem—The Bangladesh Sundarbans: A baseline for conservation

AbstractAimMangrove forests are among the most threatened and rapidly vanishing, but poorly understood ecosystems. We aim to uncover the variables driving mangrove biodiversity and produce baseline biodiversity maps for the Sundarbans world heritage site—the Earth's largest contiguous mangrove ecosystem.LocationThe Bangladesh Sundarbans, South Asia.MethodsWe collected species abundance, environmental and disturbance data from 110 permanent sample plots (PSPs) covering the entire Bangladesh Sundarbans (6,017 km2). We applied generalized additive models to determine the key variables shaping the spatial distributions of mangrove diversity and community composition. Biodiversity maps were constructed using covariate‐driven habitat models, and their predictive performances were compared with covariate‐free (i.e., direct interpolation) approaches to see whether the inclusion of habitat variables bolster spatial predictions of biodiversity or whether we can rely on direct interpolation approaches when environmental data are not available.ResultsHistorical forest exploitation, disease, siltation and soil alkalinity were the key stressors causing loss of alpha and gamma diversity in mangrove communities. Both alpha and gamma diversity increased along the downstream‐to‐upstream and riverbank‐to‐forest interior gradients. Mangrove communities subjected to intensive past tree harvesting, disease outbreaks and siltation were more homogeneous in species composition (beta diversity). In contrast, heterogeneity in species composition increased along decreasing salinity and downstream‐to‐upstream gradients. We find that the surviving biodiversity hotspots (comprising many globally endangered tree species) are located outside the established protected area network and hence open to human exploitation. We therefore suggest bringing them immediately under protected area management.Main conclusionsWe provide the first habitat‐based modelling and mapping of alpha, beta and gamma diversity in threatened mangrove communities. In general, habitat‐based models showed better predictive ability than the covariate‐free approach. Nevertheless, the small margin of differences between the approaches demonstrates the utility of direct interpolation approaches when environmental data are unavailable.

Taxonomy and ecology of order Surirellales (Bacillariophyceae) in tropical reservoirs in Southeastern of Brazil

Abstract Aim The aim of this study was to inventory the diatom species of order Surirellales present in the surface sediments of tropical reservoirs (São Paulo State, Brazil) and to correlate their distribution with environmental (pH, total phosphorus, and total nitrogen) and spatial predictors. Methods Samplings were carried out in 31 reservoirs from 2009 to 2014. Vertical profile of water samples was collected in the summer and winter along the reservoirs, and their water column mean results were used to characterize each sampling site. We measured water transparency, euphotic zone, water depth, pH, dissolved oxygen, total nitrogen, and total phosphorus. Surface sediment samples (2 cm top) were collected for diatom analyses. A partial RDA was performed between species abundance data (response matrix) and environmental and spatial variables (predictor matrices). Results 14 species of Surirellales were identified from the surface sediment samples, five of them being identified only at the genus level. Overall, partial RDA showed that the species distribution is constrained by both environmental and spatial predictors. Species were mainly ordinated in relation to pH and light availability. Conclusion Our results demonstrated that the Surirellales species revealed ecological preferences to low nutrient concentrations, neutral to slightly acidic waters, and higher light availability. Moreover, our results suggest that both environmental and spatial factors are important for their species distribution.

Measuring functional dissimilarity among plots: Adapting old methods to new questions

Ecologists routinely use dissimilarity measures between pairs of plots to explore the complex mechanisms that drive community assembly. Traditional dissimilarity measures usually quantify plot-to-plot dissimilarity based either on species presences and absences within plots or on species abundances, thus assuming that all species are equally and maximally distinct from one another. However, the value of dissimilarity measures that incorporate information on functional differences among species is becoming increasingly recognized. Since these ‘functional dissimilarity measures’ have been developed for capturing new aspects of plot-to-plot dissimilarity, they have usually little to do with more traditional measures based solely on species incidence or abundance data. In this paper we introduce a general method for adapting a large family of traditional dissimilarity coefficients to the measurement of functional differences among plots. The behavior of the proposed method, for which we provide a simple R function, was evaluated with published data on plant communities in a coastal marsh plain in Algeria. As shown by the worked example, our proposal produces a coherent framework for summarizing functional dissimilarity among plots. Being based on a generalization of classical dissimilarity measures with well-known properties, this new family of functional dissimilarity indices also has a great potential for future theoretical and applied developments in this field of research.

Habitat suitability estimated by niche models is largely unrelated to species abundance

AbstractAimData on species occurrences are far more common than data on species abundances. However, a central goal of large‐scale ecology is to understand the spatial distribution of abundance. It has been proposed that species distribution models trained on species occurrence records may capture variation in species abundance. Here, we gauge support for relationships between species abundance and predicted climatic suitability from species distribution models, and relate the slope of this relationship to species traits, evolutionary relationships and sampling completeness.LocationUSA.Time period1658–2017.Major taxa studiedMammal and tree species.Methods, ResultsTo explore the generality of abundance–suitability relationships, we trained species distribution models on species occurrence and species abundance data for 246 mammal species and 158 tree species, and related model‐predicted occurrence probabilities to population abundance predictions. Further, we related the resulting abundance–suitability relationship coefficients to species traits, geographic range sizes, evolutionary relationships and the number of occurrence records to investigate a potential trait or sampling basis for abundance–suitability relationship detectability. We found little evidence for consistent abundance–suitability relationships in mammal ( = .045) or tree ( = −.005) species, finding nearly as many negative and positive relationships. These relationships had little explanatory power, and coefficients were unrelated to species traits, range size or evolutionary relationships.Main conclusionsOur findings suggest that species climatic suitability based on occurrence data may not be reflected in species abundances, suggesting a need to investigate nonclimatic sources of species abundance variation.

Evaluation of the estimate bias magnitude of the Rao's quadratic diversity index.

Rao’s quadratic diversity index is one of the most widely applied diversity indices in functional and phylogenetic ecology. The standard way of computing Rao’s quadratic diversity index for an ecological assemblage with a group of species with varying abundances is to sum the functional or phylogenetic distances between a pair of species in the assemblage, weighted by their relative abundances. Here, using both theoretically derived and observed empirical datasets, we show that this standard calculation routine in practical applications will statistically underestimate the true value, and the bias magnitude is derived accordingly. The underestimation will become worse when the studied ecological community contains more species or the pairwise species distance is large. For species abundance data measured using the number of individuals, we suggest calculating the unbiased Rao’s quadratic diversity index.

Transition probabilities help identify putative drivers of community change in complex systems

Understanding the role of larger-scale processes in modulating the assembly, structure, and dynamics of communities is critical for forecasting the effects of climate-change and managing ecosystems. Developing this comprehensive perspective is difficult though, because species interactions are complex, interdependent, and dynamic through space and time. Typically, experiments focus on tractable subsets of interactions that will be most critical to investigate and explain shifts in communities, but qualitatively base these choices on experience, natural history, and theory. One quantitative approach to identify the putative forces regulating communities, without reducing system complexity, is estimating transition probabilities among species occupying space (i.e., multispecies Markov chain models). Although not mechanistic, these models estimate the relative frequency and importance of ecological pathways in community assembly and dynamics, and can serve as a framework to identify how pathways change across large scales and which are most important to investigate further. Here, we demonstrate this method in the Gulf of Maine (GOM) intertidal zone, where research has largely focused on the local-scale processes that influence communities, while the mechanisms responsible for more regional shifts in communities are less clear. Transition probabilities of faunal elements were quantified bimonthly for ~2.5yr in local intertidal communities at three replicate sites in the southern, mid-coast, and northern GOM. Transitions related to mortality, colonization, and replacement by mussels, barnacles, red algae, and encrusting corallines differed regionally, suggesting specific pathways related to consumer pressure and recruitment vary across the GOM with shifting intertidal community structure. Combined with species abundance data and insights from previous research, we develop and evaluate the pathways by which communities likely change in the GOM. Species interactions in local communities can be complex, and this complexity should be incorporated into hypothesis building, experiments, theory, interpretations, and forecasts in ecology. Such a comprehensive approach will be critical to understand how regional shifts in local interactions can drive large-scale community change.

Molluscs collected with otter trawl in the northern Alboran Sea: main assemblages, spatial distribution and environmental linkage

Molluscan assemblages of circalittoral and bathyal soft bottoms of the northern Alboran Sea were studied using an experimental otter trawl. Samples of fauna were collected from 190 hauls during four MEDITS surveys carried out in spring between 2012 and 2015 at depths ranging from 30 to 800 m. Measurements of water column variables (temperature and salinity) and sediment samples were taken in the same locations where faunistic sampling was carried out. A total of 101 species grouped in 55 families were recorded. Cephalopods were the most abundant group, with Abralia veranyi dominating in abundance, Octopus vulgaris in biomass and Illex coindetii and Todarodes sagittatus being the most frequently collected species. Multivariate analyses carried out separately with abundance data of demersal species, benthic species, bivalves, gastropods and cephalopods as well as of all molluscs, generally resulted in three main molluscan assemblages corresponding to a shelf assemblage (30-200 m depth), an upper slope assemblage (201-350 m depth), and a middle slope assemblage (351-800 m depth). PERMANOVA test revealed that significant differences of different groups of molluscs in relation to depth were more acute than to geographical sectors of the Alboran Sea (eastern, central, eastern and insular sectors). Abundance, biomass and species richness decreased with depth with a clear dominance of cephalopods in the slope. Significant geographical differences were mainly detected for demersal and benthic species as well as for gastropods and cephalopods between the insular sector (Alboran Island) and the western and eastern continental sectors. Both depth and temperature were the most influencing variables in the different CCA analyses using datasets of molluscs with different life styles and from different classes, but sedimentological variables displayed a more acute significant relationship with the benthic molluscs than with the demersal ones.

A family of (dis)similarity measures based on evenness and its relationship with beta diversity

In this paper, I propose a new evenness-based method for calculating plot-to-plot (dis)similarity coefficients. The method is very flexible, as (dis)similarity can be calculated for any kind of species abundance data (also including functional or phylogenetic differences between species), and can be easily generalized to multiple sites. To show how the proposed method works in practice, the behavior of two similarity coefficients based on Pielou's and Williams’ evenness is examined with simulated data representing an ideal ecological gradient. Being derived from classical evenness indices, which have been used in ecology for decades, this new family of measures has a great potential for future research in community ecology and multivariate analysis.

Regional surveys of macrobenthic shelf invertebrate communities in Onslow Bay, North Carolina, U.S.A.

Despite its importance for quantifying ecosystem responses to environmental and anthropogenic drivers, our understanding of spatial heterogeneity in marine communities remains inadequate. Studies in coastal marine benthic habitats are sparse, and predominantly target single higher taxonomic groups. Here we describe macrobenthic marine invertebrate community surveys from 52 localities in Onslow Bay (Beaufort, North Carolina, U.S.A.), over an extensive geographic area (~200 km2). The data consist of 11,467 individuals, 175 species, and 7 phyla. The data include species abundance data for each sample at all localities, and corresponding species lists and locality information. The metadata describe the sampling protocols and localities. The data provided here will facilitate examination of assemblage heterogeneity with regards to spatial and temporal patterns, and depth gradient analyses.

Responses to Prescribed Fire at Big Thicket National Preserve, Texas, USA

US Federal land managers have utilized hand ignited prescribed fire at Big Thicket National Preserve in efforts to restore the structure and diversity of the longleaf pine (Pinus palustris) forest. A fire ecology study was initiated by Rice University in the early 1990’s and the National Park Service has continued monitoring the plots. Ordination was applied to species abundance data to examine changes in vegetation communities from a variety of prescribed fire treatments and controls. The vegetation data was separated by size class to include overstory, small tree, large sapling and seedling data. Across the size classes and treatments, the sandhill and wetland savanna vegetation types remained less effected by fire treatments and only the upland pine responded to changes in the overstory. Upon reviewing fire return interval histories, it became evident that prescribed fire alone was not changing vegetation communities. Most of the plots did not have longleaf pine trees or seedlings present and only two plots that were mechanical treated showed distinction among other treatment regimes. Restoration treatments including the mechanical and chemical application and seedling plantings are necessary to ensure restoration of the longleaf pine forest structure and diverse understory vegetation.

Gbm.auto: A software tool to simplify spatial modelling and Marine Protected Area planning.

Boosted Regression Trees. Excellent for data-poor spatial management but hard to useMarine resource managers and scientists often advocate spatial approaches to manage data-poor species. Existing spatial prediction and management techniques are either insufficiently robust, struggle with sparse input data, or make suboptimal use of multiple explanatory variables. Boosted Regression Trees feature excellent performance and are well suited to modelling the distribution of data-limited species, but are extremely complicated and time-consuming to learn and use, hindering access for a wide potential user base and therefore limiting uptake and usage.BRTs automated and simplified for accessible general use with rich feature setWe have built a software suite in R which integrates pre-existing functions with new tailor-made functions to automate the processing and predictive mapping of species abundance data: by automating and greatly simplifying Boosted Regression Tree spatial modelling, the gbm.auto R package suite makes this powerful statistical modelling technique more accessible to potential users in the ecological and modelling communities. The package and its documentation allow the user to generate maps of predicted abundance, visualise the representativeness of those abundance maps and to plot the relative influence of explanatory variables and their relationship to the response variables. Databases of the processed model objects and a report explaining all the steps taken within the model are also generated. The package includes a previously unavailable Decision Support Tool which combines estimated escapement biomass (the percentage of an exploited population which must be retained each year to conserve it) with the predicted abundance maps to generate maps showing the location and size of habitat that should be protected to conserve the target stocks (candidate MPAs), based on stakeholder priorities, such as the minimisation of fishing effort displacement.Gbm.auto for management in various settingsBy bridging the gap between advanced statistical methods for species distribution modelling and conservation science, management and policy, these tools can allow improved spatial abundance predictions, and therefore better management, decision-making, and conservation. Although this package was built to support spatial management of a data-limited marine elasmobranch fishery, it should be equally applicable to spatial abundance modelling, area protection, and stakeholder engagement in various scenarios.

Relative contribution of neutral and deterministic processes in shaping fruit-feeding butterfly assemblages in Afrotropical forests.

The unified neutral theory of biodiversity and biogeography has gained the status of a quantitative null model for explaining patterns in ecological (meta)communities. The theory assumes that individuals of trophically similar species are functionally equivalent. We empirically evaluate the relative contribution of neutral and deterministic processes in shaping fruit‐feeding butterfly assemblages in three tropical forests in Africa, using both direct (confronting the neutral model with species abundance data) and indirect approaches (testing the predictions of neutral theory using data other than species abundance distributions). Abundance data were obtained by sampling butterflies using banana baited traps set at the forest canopy and understorey strata. Our results indicate a clear consistency in the kind of species or species groups observed at either the canopy or understorey in the three studied communities. Furthermore, we found significant correlation between some flight‐related morphological traits and species abundance at the forest canopy, but not at the understorey. Neutral theory's contribution to explaining our data lies largely in identifying dispersal limitation as a key process regulating fruit‐feeding butterfly community structure. Our study illustrates that using species abundance data alone in evaluating neutral theory can be informative, but is insufficient. Species‐level information such as habitat preference, host plants, geographical distribution, and phylogeny is essential in elucidating the processes that regulate biodiversity community structures and patterns.

Abundance of small mammals in the Atlantic Forest (ASMAF): adata set for analyzing tropical community patterns.

Local abundance results from the interaction between populational and environmental processes. The abundance of the species in a community is also one of the most basic descriptors of its structure. Despite its importance, information about species abundances is fragmentary, creating a knowledge gap about species abundances known as the Prestonian Shortfall. Here we present a comprehensive data set of small mammal abundance in the Atlantic Forest. Data were extracted from 114 published sources and from unpublished data collected by our research groups spanning from 1943 to 2017. The data set includes 1,902 records of at least 111 species in 155 localities, totaling 42,617 individuals represented. We selected studies that (1) were conducted in forested habitats of the Atlantic Forest, (2) had a minimum sampling effort of at least 500 trap-nights, and (3) contained species abundance data in detail. For each study, we recorded (1) latitude and longitude, (2) name of the locality, (3) employed sampling effort, (4) type of traps used, (5) study year, (6) country, and (7) species name with (8) its respective abundances. For every locality, we also obtained information regarding its (9) ecoregion, (10) predominant vegetation type, and (11) biogeographic subdivision. Whenever necessary, we also (12) updated the species names as new species were described and some genera suffered taxonomic revision since the publication. The localities are spread across the Atlantic Forest and most of the small mammal species known to occur in Atlantic Forest are present in the data set, making it representative of communities of the entire biome. This data set can be used to address various patterns in community ecology and geographical ecology, as the relation between local abundance and environmental suitability, hypothesis regarding local and regional factors on community structuring, species abundance distributions (SAD), functional and phylogenetic mechanisms on community assembling.

Can tree species diversity be assessed with Landsat data in a temperate forest?

The diversity of forest trees as an indicator of ecosystem health can be assessed using the spectral characteristics of plant communities through remote sensing data. The objectives of this study were to investigate alpha and beta tree diversity using Landsat data for six dates in the Gönen dam watershed of Turkey. We used richness and the Shannon and Simpson diversity indices to calculate tree alpha diversity. We also represented the relationship between beta diversity and remotely sensed data using species composition similarity and spectral distance similarity of sampling plots via quantile regression. A total of 99 sampling units, each 20m×20m, were selected using geographically stratified random sampling method. Within each plot, the tree species were identified, and all of the trees with a diameter at breast height (dbh) larger than 7cm were measured. Presence/absence and abundance data (tree species number and tree species basal area) of tree species were used to determine the relationship between richness and the Shannon and Simpson diversity indices, which were computed with ground field data, and spectral variables derived (2×2 pixels and 3×3 pixels) from Landsat 8 OLI data. The Shannon-Weiner index had the highest correlation. For all six dates, NDVI (normalized difference vegetation index) was the spectral variable most strongly correlated with the Shannon index and the tree diversity variables. The Ratio of green to red (VI) was the spectral variable least correlated with the tree diversity variables and the Shannon basal area. In both beta diversity curves, the slope of the OLS regression was low, while in the upper quantile, it was approximately twice the lower quantiles. The Jaccard index is closed to one with little difference in both two beta diversity approaches. This result is due to increasing the similarity between the sampling plots when they are located close to each other. The intercept differences between two investigated beta diversity were strongly related to the development stage of a number of sampling plots in the tree species basal area method. To obtain beta diversity, the tree basal area method indicates better result than the tree species number method at representing similarity of regions which are located close together. In conclusion, NDVI is helpful for estimating the alpha diversity of trees over large areas when the vegetation is at the maximum growing season. Beta diversity could be obtained with the spectral heterogeneity of Landsat data. Future tree diversity studies using remote sensing data should select data sets when vegetation is at the maximum growing season. Also, forest tree diversity investigations can be identified by using higher-resolution remote sensing data such as ESA Sentinel 2 data which is freelyavailablesince June2015.

Biocrust ecology: unifying micro- and macro-scales to confront global change.

Biocrust ecology: unifying micro- and macro-scales to confront global change.