Habitat fragmentation determines diversity of annual plant communities at landscape and fine spatial scales

The aim of this study was to disentangle the effects of landscape configuration (i.e., fragment area, connectivity, and proximity to a busy highway) on the assembly of annual plant communities at different spatial scales. Our main hypothesis was that larger and more connected fragments would have higher species densities per plot and this may result in differences in turnover and nestedness patterns at the fine spatial scales where plants interact. Specifically, since Mediterranean annuals are known to form strong competitive hierarchies, we expected to find a nested pattern of beta diversity due to sequential species loss. The study area was a fragmented gypsum habitat in central Spain with a semiarid climate where two fragmentation drivers coexist: agricultural practices and a roadway. Larger fragments had higher species densities per plot (20 × 20 m). Nevertheless, we detected no effect on the species assembly at fine spatial scales (30 × 30 cm). However, when the fragment connectivity was high the species that appeared in poor quadrats (30 × 30 cm) comprised a subset of the species in rich quadrats. These results agree well with the establishment of strong competitive hierarchies among annual species. The distance to the highway influenced the identity of the species established in the community (i.e., species composition) at fine spatial scales, but we detected no effect on species turnover, nestedness, or species densities. The main conclusion of our study is that the effects of habitat fragmentation extend beyond the landscape scale and they determine the spatial assembly at fine spatial scales.     

Host–parasite nestedness: A result of co-evolving trait-values

Nestedness is an intriguing feature of ecological networks, where those species found in species-depauperate communities are subsets of those found in communities with greater species richness. For bipartite interaction networks, a “community” of species may be thought of as all those pollinating a particular plant, or infecting a particular host, for example. While there is much clear evidence for nestedness in mutualistic webs, host–parasite webs have proven more contentious. There have been a number of suggested causes for nestedness, including an association between the abundance of individuals and the resulting number of species interactions, and the matching of phenotypic traits between species. Questions remain as to the relative importance of these driving factors, especially as host–parasite and mutualistic webs contain completely different interaction types.We propose a model motivated by both of the above factors, considering a trade-off in resources that a species faces in optimizing its transmission or defense. We construct a multi-species model in which both hosts and parasites have limited resources with which to attack or defend themselves from each other. We analyze the evolution of the manner in which they use these resources using adaptive dynamics, to arrive at a final species interaction matrix, which we then test for nestedness. A general model with m hosts and n microparasite species is described here, but results are given for m = n = 5, chosen to be a large enough system for patterns to be identified, but not so large that computational time becomes prohibitive.Our results demonstrate that this co-evolution leads to an unusual amount of nestedness when the trade-offs in transmission for parasites are concave, and an unusual amount of anti-nestedness when they are convex. This enables us to predict the circumstances under which we would expect to observe nestedness in real networks.     

Remote sensing improves prediction of tropical montane species diversity but performance differs among taxa

Texture information from passive remote sensing images provides surrogates for habitat structure, which is relevant for modeling biodiversity across space and time and for developing effective ecological indicators. However, the applicability of this information might differ among taxa and diversity measures. We compared the ability of indicators developed from texture analysis of remotely sensed images to predict species richness and species turnover of six taxa (trees, pyraloid moths, geometrid moths, arctiinae moths, ants, and birds) in a megadiverse Andean mountain rainforest ecosystem. Partial least-squares regression models were fitted using 12 predictors that characterize the habitat and included three topographical metrics derived from a high-resolution digital elevation model and nine texture metrics derived from very high-resolution multi-spectral orthophotos. We calculated image textures derived from mean, correlation, and entropy statistics within a relatively broad moving window (102 m × 102 m) of the near infra-red band and two vegetation indices. The model performances of species richness were taxon dependent, with the lowest predictive power for arctiinae moths (4%) and the highest for ants (78%). Topographical metrics sufficiently modeled species richness of pyraloid moths and ants, while models for species richness of trees, geometrid moths, and birds benefited from texture metrics. When more complexity was added to the model such as additional texture statistics calculated from a smaller moving window (18 m × 18 m), the predictive power for trees and birds increased significantly from 12% to 22% and 13% to 27%, respectively. Gradients of species turnover, assessed by non-metric two-dimensional scaling (NMDS) of Bray-Curtis dissimilarities, allowed the construction of models with far higher predictability than species richness across all taxonomic groups, with predictability for the first response variable of species turnover ranging from 64% (birds) to 98% (trees) of the explained change in species composition, and predictability for the second response variable of species turnover ranging from 33% (trees) to 74% (pyraloid moths). The two NMDS axes effectively separated compositional change along the elevational gradient, explained by a combination of elevation and texture metrics, from more subtle, local changes in habitat structure surrogated by varying combinations of texture metrics. The application of indicators arising from texture analysis of remote sensing images differed among taxa and diversity measures. However, these habitat indicators improved predictions of species diversity measures of most taxa, and therefore, we highly recommend their use in biodiversity research.     

Diversity and spatial clustering of shade trees affect cacao yield and pathogen pressure in Costa Rican agroforests

The importance of the spatial organisation of individuals in explaining species coexistence within a community is widely recognised. However, few analyses of spatial structure have been performed on tropical agroforests.The main objective of this study was to highlight the links between spatial organisation of shade trees on the one hand, and shade tree species richness and cacao yield on the other, using data from 29 cacao agroforests in Costa Rica.A method of spatial statistics, Ripley's K-function, was used to analyse the spatial organisation of shade and cacao trees in the study plots. For each stand, the X and Y coordinates of ≥2.5-m-tall trees were recorded. In each plot we also assessed shade tree species richness and cacao yield (with total number of pods = number of pods damaged by frosty pod rot + number of healthy pods).Three types of stands were identified: the first was characterised by significant clustering of shade trees, the highest shade tree species richness (S = 6), and the highest number of damaged pods (139 pods ha^?1 year^?1). The second type was characterised by random spatial organisation of shade trees. The third type showed a trend towards regular organisation. Species richness of shade trees did not differ significantly between the last two types (S = 4 for both), nor did the number of damaged pods (56 pods ha^?1 year^?1 and 67 pods ha^?1 year^?1 respectively).Although the trends were not statistically significant for all the variables in our data set, the clustered spatial structure appears to favour a synergy between environmental (tree species richness), and provisioning (cacao production) services.     

Rodent endemism,turnover and biogeographical transitions on elevation gradients in the northwestern Argentinian Andes

The aim of this research is to relate patterns of endemism and turnover along a local elevation gradient in northwest Argentina with continental biogeographical transitions. Specimen based records constituted the principal source of information to infer rodent distribution along the elevation gradient. I assessed elevational variation of richness, endemism and turnover by means of non-linear regression analysis. Then I identified five distributional patterns based on the overlap of species geographic range. Their frequency along elevation was used to validate biogeographical boundaries inferred by turnover rates. Eleven species out of 37 (30%) are endemic to the study area. Species richness and endemism were hump-shaped. The rate of endemism reached its maximum value at the upper limit of the forest (2500 m). By contrast, species turnover was U-shaped, with a small peak at 1500 m and a maximum at 3500 m. The species’ geographic range patterns were not randomly distributed along elevation but agglomerated at specific elevation. Species turnover and chorological analysis suggest two biogeographical boundaries, a weaker at 1500 m and a stronger at 3500 m. The 1500 m boundary marks the transition from assemblages dominated by Lowland-widespread fauna at lower elevation to Montane (Andean eastern slopes) species at middle elevation. This boundary is characterized by moderate species turnover and high species richness. The strong turnover rate at 3500 and the dominance of highland Andean and Andean-Patagonian species above this elevation suggest the occurrence of the transition between the Neotropical and Andean regions; which is characterised by an almost complete species replacement.     

Partitioning multiple-site tree-like beta diversity into turnover and nestedness components without pairwise comparisons

In this letter, I extend a species-level partitioning framework for a multiple-site dissimilarity index established by Ricotta and Pavoine (2015) to account for tree-like information (i.e., evolutionary history, taxonomic classification or functional divergence of species). This novel framework can be applied to evaluate the relative contribution of turnover versus nestedness to total multiple-site tree-like beta diversity in empirical settings. The feature of the framework is to account for expectedly and unexpectedly absence of species in the sites without pairwise comparisons between sites. Simple examples with step-by-step calculation details and corresponding R computing code are provided to better understand and apply the proposed framework.     

The reliability of a composite biodiversity indicator in predicting bird species richness at different spatial scales

Several biodiversity features can be linked to landscape heterogeneity, that, in turn, can be informative for management and conservation purposes. Usually, the more the landscape is complex the more the biodiversity increases. Biodiversity indicators can be a useful tool to assess biodiversity status, in function of landscape heterogeneity. In this study, we developed a biodiversity indicator, based on Shannon diversity index and built from distribution maps of protected species. With such an approach, we seek to evaluate the feasibility of using a combination of target species as a surrogate for assessing the status of the whole bird community. Our approach was spread over multiple spatial scales, to determine which was the most informative. We selected four species protected by European regulation and generated a presence-absence map from species distribution modelling. We, therefore, used the FRAGSTATS biodiversity metric to calculate Shannon index for the overlapped presence-absence maps, at two spatial scales (500 m and 1000 m). Then, the relationships with the whole community was assessed through generalised least square models, at the spatial scale of 4 ha, 9 ha and 25 ha. Results showed that the higher rate of variability of community was explained by the biodiversity indicator at 1000 m scale. Indeed, the more informative spatial scale for the whole bird community was 9 ha. In addition, a pattern emerged about the relationships between biodiversity indicator and community richness, that is worth of further research. Our study demonstrates that the usefulness of surrogate species for biodiversity and community assessment can become clear only at a certain spatial scales. Indeed, they can be highly predictive of the whole community, and highly informative for conservation planning. Moreover, their use can optimize biodiversity monitoring and conservation, focusing on a small number of noteworthy species.     

Sampling effort and common species: Optimizing surveys of understorey fruit-feeding butterflies in the Central Amazon

Surveys on tropical invertebrates must gather as much information as possible over the shortest period, mainly because of financial limitations and hyperdiversity. Fruit-feeding butterflies in the subfamilies Biblidinae, Charaxinae, Nymphalinae and Satyrinae (Nymphalidae) are attracted to decaying material and can be sampled with standardized methodologies, but (1) some groups can be difficult to collect, despite being quite common in Amazonian forest understorey; moreover, (2) the duration of the sampling period is not consistent among studies and (3) the sufficient effort for financially limited projects remains unknown. With this study, we aimed to fulfill points 1–3 in order to recommend a less costly protocol for monitoring purposes in the Amazon. In 25 km² of rainforest in the state of Amazonas, Brazil, we evaluated the performance of sampling schemes for these butterflies (four, three, two and one visit in 250 m-long plots), using both nets and bait traps, while considering reductions in sampling effort and the removal of rare and infrequent taxa to optimize field and laboratory work. Reduced-effort schemes are only validated if they reflect both taxonomic and ecological information provided by the maximum effort. Procrustes superimposition was used to estimate the dissimilarity in the spatial distribution of species between schemes. Spatial turnover in herb, liana, palm tree and diameter-at-breast-height > 10 cm tree species composition was used as predictor for the butterfly community through linear regressions. The three-visit scheme was sufficient to retrieve high species similarity and the ecological patterns observed with maximum effort. The two-visit scheme lost a significant amount of information on species composition similarity, but recovered stronger environmental relationships than those observed with the four-visit scheme. The removal of uncommon species did not affect the ecological response of the community, thereby suggesting that common species are driving the spatial patterns of the studied butterflies. Thus, large reductions in costs by reducing sampling effort could be achieved with relatively little loss of information on the species turnover of butterflies and their relationships with the environment. The proposed sampling protocols with reduced effort will allow projects to use their time and financial supply more effectively, showing that cost-effective shortcuts for biodiversity assessments can be useful for conservation, biomonitoring and land use management.     

A habitat quality indicator for common birds in Europe based on species distribution models

The EU 2020 Biodiversity Strategy requires the gathering of information on biodiversity to aid in monitoring progress towards its main targets. Common species are good proxies for the diversity and integrity of ecosystems, since they are key elements of the biomass, structure, functioning of ecosystems, and therefore of the supply of ecosystem services. In this sense, we aimed to develop a spatially-explicit indicator of habitat quality (HQI) at European level based on the species included in the European Common Bird Index, also grouped into their major habitat types (farmland and forest). Using species occurrences from the European Breeding Birds Atlas (at 50 km × 50 km) and the maximum entropy algorithm, we derived species distribution maps using refined occurrence data based on species ecology. This allowed us to cope with the limitations arising from modelling common and widespread species, obtaining habitat suitability maps for each species at finer spatial resolution (10 km × 10 km grid), which provided higher model accuracy. Analysis of the spatial patterns of local and relative species richness (defined as the ratio between species richness in a given location and the average richness in the regional context) for the common birds analysed demonstrated that the development of a HQI based on species richness needs to account for the regional species pool in order to make objective comparisons between regions. In this way, we proved that relative species richness compensated for the bias caused by the inherent heterogeneous patterns of the species distributions that was yielding larger local species richness in areas where most of the target species have the core of their distribution range. The method presented in this study provides a robust and innovative indicator of habitat quality which can be used to make comparisons between regions at the European scale, and therefore potentially applied to measure progress towards the EU Biodiversity Strategy targets. Finally, since species distribution models are based on breeding birds, the HQI can be also interpreted as a measure of the capacity of ecosystems to provide and maintain nursery/reproductive habitats for terrestrial species, a key maintenance and regulation ecosystem service.     

Microhabitat variations and seed bank-vegetation relationships in a desert wadi ecosystem

Due to extreme variability in patterns of rainfall, plant seed banks are an important component of desert habitats. Here I report on effects of standing vegetation and three different microhabitats (channel, bank and terrace) on the soil seed bank of a desert wadi ecosystem in the Eastern Desert of Egypt. A total of 450 soil samples at 45 stands were collected to represent the different wadi microhabitats. The germinable seed bank was estimated by controlled counts of seedling emergence. The floristic composition, functional properties and diversity of the soil seed bank, as well as its similarity with the standing vegetation varied among wadi microhabitats. Such variation could be attributed to differences in disturbance intensity among microhabitats (terrace < bank < channel) and variation of soil factors along the microtopographic gradient. Channel showed the highest species richness and size of soil seed bank, followed by bank and then terrace. Moreover the Shannon index of diversity of the seed bank and its similarity with standing vegetation were significantly greater in both channel and bank microhabitats than in terrace. At the level of plant functional groups, number of seeds of annuals was higher in both channel and bank than in terrace. Shrubs were more abundant in seed banks of channel compared to terrace. The size and species richness of seed bank were increased with the total plant cover, annual/perennial ratio and species richness of the standing vegetation.     

Geographic position of sample grid and removal of uncommon species affect multivariate analyses of diverse assemblages: The case of oribatid mites (Acari: Oribatida)

In view of the rapid loss of biodiversity, large-scale environmental monitoring programs are urgently needed, over a range of local, regional and global scales. These programs can be made more efficient and cost-effective through shortcuts such as reduction of sampling effort and the use of low-cost surrogates. We revisited a large-scale dataset composed by 161 species recorded in 72 plots of 250 m, distributed over an 8 m × 8 m sampling grid in the tropical rainforest. Samples of litter and soil were collected and oribatid mites were extracted with a Berlese–Tullgren apparatus. Using a “moving window” procedure, we delimited smaller 5 km × 5 km grids in 16 possible positions within the larger grid. We first evaluated which fraction was more important to explain environmental and spatial patterns in the species composition: known environmental or spatial filters representing unknown causes of aggregation, and the confounded variance that might be associated with either or both. We used soil clay content, litter quantity, soil pH, number of trees, and distance to the nearest stream as environmental predictors. The spatial filters were generated using Moran Eigenvector mapping through the Principal Coordinates of Neighbor Matrices technique. To evaluate the influence of these fractions on the species composition, we used partial Redundancy Analysis. Using Principal Coordinates Analysis for abundance and presence/absence data, we evaluated if reduced matrices, discarding sets of less-frequent species, could identify the relationships captured with the complete dataset. All smaller grids contained more than 100 species. The effect of environmental variables on oribatid-mite community composition was always low, and each smaller grid position produced different results. Soil clay content and pH were the main factors associated with oribatid-mite distributions. The effects of unknown spatial patterns were greater than the environmental ones. Independently of the grid position, similar results were obtained for analyses with all oribatid-mite species, to the results obtained from analyses of only the most frequent species. Sets of more frequent and easily identifiable species proved to be a reliable surrogate for the complete assemblage. Omitting identifications of most species will improve the cost-effectiveness of monitoring programs. More emphasis should be placed on investigating the role of spatial heterogeneity and the effects of grid position in relation to patterns in species associations. Efficient biomonitoring could target surrogate species, to enable rapid tracking of environmental change while enlarging the sampling area to provide data for conservation strategies.     

The relationship between species replacement,dissimilarity derived from nestedness,and nestedness

Aim Beta diversity can be partitioned into two components: dissimilarity due to species replacement and dissimilarity due to nestedness ( Baselga, 2010 , Global Ecology and Biogeography, 19 , 134–143). Several contributions have challenged this approach or proposed alternative frameworks. Here, I review the concepts and methods used in these recent contributions, with the aim of clarifying: (1) the rationale behind the partitioning of beta diversity into species replacement and nestedness‐resultant dissimilarity, (2) how, based on this rationale, numerators and denominators of indices have to match, and (3) how nestedness and nestedness‐resultant dissimilarity are related but different concepts. Innovation The rationale behind measures of species replacement (turnover) dictates that the number of species that are replaced between sites (numerator of the index) has to be relativized with respect to the total number of species that could potentially be replaced (denominator). However, a recently proposed partition of Jaccard dissimilarity fails to do this. In consequence, this partition underestimates the contribution of species replacement and overestimates the contribution of richness differences to total dissimilarity. I show how Jaccard dissimilarity can be partitioned into meaningful turnover and nestedness components, and extend these new indices to multiple‐site situations. Finally the concepts of nestedness and nestedness‐resultant dissimilarity are discussed. Main conclusions Nestedness should be assessed using consistent measures that depend both on paired overlap and matrix filling, e.g. NODF, whereas beta‐diversity patterns should be examined using measures that allow the total dissimilarity to be separated into the components of dissimilarity due to species replacement and dissimilarity due to nestedness. In the case of multiple‐site dissimilarity patterns, averaged pairwise indices should never be used because the mean of the pairwise values is unable to accurately reflect the multiple‐site attributes of dissimilarity.     

Testing the effectiveness of surrogates for assessing biological diversity of arthropods in cereal agricultural landscapes

Agricultural intensification is altering biodiversity patterns worldwide. Rapid and effective methods are needed to monitor these changes in farmland biodiversity, but it becomes both a cost- and time-prohibitive task, particularly for hyper-diverse groups such as arthropods. We evaluated the effectiveness of surrogates in irrigated and rainfed wheat fields in a Mediterranean farmland in NW Spain in order to get a rapid tool to assess arthropod biodiversity. We studied six groups with different ecological needs (i.e. Aphididae, Aphidiinae, Coccinellidae, Formicidae, Heteroptera and Syrphidae) at species level (147 species), genus (105), family (10, only Heteroptera) and order (19) level. Higher taxa, cross-taxa and subset-taxa or total richness approaches were tested as well as the correlation in composition between levels for the selected groups, and the influence of farming regime. Genus richness was a good surrogate of species richness in all six groups studied (R² = 0.38–0.60), like family and order were for Heteroptera (R² = 0.37 and 0.29, respectively). Cross-taxa analyses showed that Aphididae and Aphidiinae genera (R² = 0.19 and 0.30, respectively) and species (R² = 0.20 and 0.28, respectively) were good surrogates for Aphidiinae and Aphididae species respectively. Coccinellidae genera (R² = 0.26) and species (R² = 0.25) were good surrogates for Heteroptera species. Finally, Aphididae and Coccinellidae both at genera (R² = 0.14 and 0.20, respectively) and at species levels (R² = 0.12–0.22, respectively) were good surrogates for total species richness of all groups. Genera composition was the best surrogate for the species composition within each group. Farming regime had no influence on the relationships between surrogates and species patterns in most cases. Our results suggest that genera level is a useful surrogate for all the studied groups and family is appropriate for Heteroptera. Genus level provided a saving of 15% of identification time in Aphididae and 80% for Coccinellidae. This proves its usefulness to asses and monitor biodiversity in wheat croplands and the possibility to reduce costs.     

Purification of recombinant mandelate racemase: Improved catalytic activity

Mandelate racemase (MR, E.C. 5.1.2.2) from Pseudomonas putida catalyzes the Mg²⁺-dependent 1,1-proton transfer that interconverts the enantiomers of mandelate and has been studied extensively as a model for understanding how enzymes catalyze the deprotonation of carbon acid substrates with relatively high pK_a values. Purification of recombinant MR as a fusion protein with an N-terminal hexahistidine tag using immobilized-nickel ion affinity chromatography and elution with a linear gradient of EDTA revealed three enzyme species (mrI, mrII, and mrIII). While mrIII was catalytically inactive, both mrI and mrII catalyzed the racemization of (S)-mandelate with turnover numbers (k_cat) of 190 ± 22 and 940 ± 24 s^?1, respectively. Circular dichroism analysis suggested that mrIII was a partially unfolded or misfolded form of the enzyme. Replacement of the N-terminal hexahistidine tag by a StrepII-tag appeared to ameliorate the folding problem yielding a single enzyme species with a turnover number of 1124 ± 43 s^?1. The MR fusion protein bearing an N-terminal StrepII-tag and a C-terminal decahistidine tag also exhibited reduced turnover (k_cat = 472 ± 37 s^?1). These results highlight a potential problem that may be encountered when producing fusion enzymes bearing a polyhistidine tag: soluble, active enzyme may be obtained but care must be taken to ensure that it is free of minor misfolded forms that can alter the apparent activity of the enzyme.     

Effect Factors for marine eutrophication in LCIA based on species sensitivity to hypoxia

Hypoxia is an important environmental stressor to marine species, especially in benthic coastal waters. Increasing anthropogenic emissions of nutrients and organic matter contribute to the depletion of dissolved oxygen (DO). Biotic sensitivity to low levels of DO is determined by the organisms’ ability to use DO as a respiratory gas, a process depending on oxygen partial pressure. A method is proposed to estimate an indicator of the intensity of the effects caused by hypoxia on exposed marine species. Sensitivity thresholds to hypoxia of an exposed ecological community, modelled as lowest-observed-effect-concentrations (LOEC), were compiled from literature for 91 benthic, demersal and benthopelagic species of fish, crustaceans, molluscs, echinoderms, annelids, and cnidarians, and converted to temperature-specific benthic (100 m depth) LOEC values. Species distribution and LOEC values were combined using a species sensitivity distribution (SSD) methodology to estimate the DO concentration at which the potentially affected fraction (PAF) of the community's species having their LOEC exceeded is 50% (HC50_LOEC). For the purpose of effect modelling in Life Cycle Impact Assessment (LCIA), Effect Factors (EF [(PAF) m³ kgO₂⁻¹]) were derived for five climate zones (CZ) to represent the change in effect due to a variation of the stressor intensity, or EF = ΔPAF/ΔDO = 0.5/HC50_LOEC. Results range from 218 (PAF) m³ kgO₂⁻¹ (polar CZ) to 306 (PAF) m³ kgO₂⁻¹ (tropical CZ). Variation between CZs was modest so a site-generic global EF of 264 (PAF) m³ kgO₂⁻¹ was also estimated and may be used to represent the average impact on a global ecological community of marine species exposed to hypoxia. The EF indicator is not significantly affected by the major sources of uncertainty in the underlying data suggesting valid applicability in characterisation modelling of marine eutrophication in LCIA.     

Vegetation mapping and multivariate approach to indicator species of a forest ecosystem: A case study from the Thandiani sub Forests Division (TsFD) in the Western Himalayas

QuestionsDoes the plant species composition of Thandiani sub Forests Division (TsFD) correlate with edaphic, topographic and climatic variables? Is it possible to identify different plant communities in relation to environmental gradients with special emphasis on indicator species? Can this approach to vegetation classification support conservation planning?LocationThandiani sub Forests Division, Western Himalayas.MethodsQuantitative and qualitative characteristics of species along with environmental variables were measured using a randomly stratified design to identify the major plant communities and indicator species of the Thandiani sub Forests Division. Species composition was recorded in 10 × 2.5 × 2 and 0.5 × 0.5 m square plots for trees, shrubs and herbs, respectively. GPS, edaphic and topographic data were also recorded for each sample plot. A total of 1500 quadrats were established in 50 sampling stations along eight altitudinal transects encompassing eastern, western, northern and southern aspects (slopes). The altitudinal range of the study area was 1290 m to 2626 m above sea level using. The relationships between species composition and environmental variables were analyzed using Two Way Cluster Analysis (TWCA) and Indicator Species Analysis (ISA) via PCORD version 5.ResultsA total of 252 plant species belonging to 97 families were identified. TWCA and ISA recognized five plant communities. ISA additionally revealed that mountain slope aspect, soil pH and soil electrical conductivity were the strongest environmental factors (p ≤ 0.05) determining plant community composition and indicator species in each habitat. The results also show the strength of the environment-species relationship using Monte Carlo procedures.ConclusionsAn analysis of vegetation along an environmental gradient in the Thandiani sub Forests Division using the Braun-Blanquet approach confirmed by robust tools of multivariate statistics identified indicators of each sort of microclimatic zones/vegetation communities which could further be used in conservation planning and management not only in the area studied but in the adjacent regions exhibit similar sort of environmental conditions.     

Rethinking the relationship between nestedness and beta diversity: a comment on Baselga (2010)

Baselga [Partitioning the turnover and nestedness components of beta diversity. Global Ecology and Biogeography, 19 , 134–143, 2010] proposed pairwise (β_nes) and multiple‐site (β_NES) beta‐diversity measures to account for the nestedness component of beta diversity. We used empirical, randomly created and idealized matrices to show that both measures are only partially related to nestedness and do not fit certain fundamental requirements for consideration as true nestedness‐resultant dissimilarity measures. Both β_nes and β_NES are influenced by matrix size and fill, and increase or decrease even when nestedness remains constant. Additionally, we demonstrate that β_NES can yield high values even for matrices with no nestedness. We conclude that β_nes and β_NES are not true measures of the nestedness‐resultant dissimilarity between sites. Actually, they quantify how differences in species richness that are not due to species replacement contribute to patterns of beta diversity. Finally, because nestedness is a special case of dissimilarity in species composition due to ordered species loss (or gain), the extent to which differences in species composition is due to nestedness can be measured through an index of nestedness.