Elucidating the global elapid (Squamata) richness pattern under metabolic theory of ecology

Environmental determinants of global patterns in species richness are still uncertain. The Metabolic Theory of Ecology (MTE) proposes that species richness patterns can be explained by environmental temperature acting on the metabolism of ectothermic organisms. However, the generality of this theory has been questioned due to its low fit to the geographic variation in species richness of different taxonomic groups. Here, we investigated whether the MTE drives elapid richness, testing the non-stationarity of the relationship between the natural logarithm of species richness (ln S) and the inverse function of temperature (1/kT) using a geographically weighted regression (GWR). The relationship between ln S and 1/kT varied systematically over space and showed non-stationarity. Few tropical locations were consistent with MTE predictions, whereas other regions fitted differently. Although the slope of the GWR model ranged from low to high, the temperature did not predict species richness strongly on average and did not limit the upper values of richness. The response of richness to temperature in some areas might reflect a recent history of colonization and diversification of species across tropical and subtropical regions. In regions not affected by temperature, species richness should be structured by other biotic and abiotic interactions. This scenario reveals that the non-stationarity of the relationship would be linked to idiosyncrasies in the sample sites, which can drift the magnitude or change the relationship between species richness and temperature throughout space.     

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.     

Altitude modifies species richness–nutrient indicator value relationships in a country-wide survey of grassland vegetation

Nutrient enrichment is a threat to botanical diversity in Europe, and its assessment is part of biodiversity monitoring schemes. In Switzerland, this is done by calculating the average nutrient (N) indicator value of the vegetation based on a country-wide systematic vegetation survey. However, it is questionable whether N values indicate eutrophication and resulting species loss equally well across an entire country, which includes wide topographic gradients and distinct biogeographic regions. Here we analyze vascular plant species lists from 415 grassland plots (10 m²) between 365 and 2770 m a.s.l. throughout Switzerland to investigate how the relationship between N value and species richness differs with altitude and among regions. The N value strongly decreased with altitude (piecewise regression: r² = 0.77), particularly between 800 and 2000 m a.s.l., where this decrease was related to a decreasing proportion of fertilized grasslands. In the alpine belt, lower N values were associated with a greater frequency of acidic soils and a restricted species pool. Vascular plant species richness was maximal at intermediate altitude (piecewise regression: r² = 0.33) and intermediate N value (polynomial regression: r² = 0.46). When analyzed separately by altitudinal belt, the relationship between species richness and N value was negative in the lowlands and montane belt but unimodal in the subalpine belt. In the alpine belt, soil pH (R indicator values) explained most of the variation in species richness. Two indices of between-plot diversity (floristic dissimilarity and the contribution of individual plots to total species richness) were negatively related to N values from the lowlands to the subalpine belt but not in the alpine belt. All relationships differed little among the biogeographic regions of Switzerland, but they might be modified by changes in management and by the expansion of common lowland species into mountain grasslands.     

Effects of plant diversity on microbial biomass and community metabolic profiles in a full-scale constructed wetland

There has been less understanding of relations of microbial community patterns with plant diversity in constructed wetlands. We conducted a single full-scale subsurface vertical flow constructed wetland (SVFCW, 1000 m²) study focusing on domestic wastewater processing. This study measured the size and structure of microbial community using fumigation extraction and BIOLOG Ecoplate? techniques, to examine the effects of macrophyte diversity on microbial communities that are critical in treatment efficiency of constructed wetlands. We also determined the relationship of plant diversity (species richness) with its biomass production under disturbance of the same wastewater supply. Linear regression analysis showed that plant biomass production strongly correlated with plant species richness (R = 0.407, P < 0.001). Increase in plant species richness increased microbial biomass carbon and nitrogen (R = 0.494, P < 0.001; R = 0.465, P < 0.001) and utilization of amino acids on Ecoplates (R = 0.235, P = 0.03), but limited the utilization of amine/amides (R = ?0.338, P = 0.013). Principal components analysis (PCA) showed that the diversity and community-level physiological profiles (CLPP) of microbial community at 168 h of incubation strongly depended on the presence or absence of plant species in the SVFCW system, but not on the species richness. This is the first step toward understanding relations of plant diversity with soil microbial community patterns in constructed wetlands, but the effect of species diversity on microbial community should be further studied.     

Influence of plant species and wastewater strength on constructed wetland methane emissions and associated microbial populations

Wastewater and treatment processes have been regarded as large contributions to sources of methane (CH₄). The flux rate of CH₄ in constructed wetlands (CWs) was evaluated to test the influence of plant species. Methane emission data showed large temporal and spatial variation ranging from 0 to 16.76 g CH₄ m⁻² day⁻¹. The highest CH₄ flux rate was obtained in the Zizania latifolia systems and higher emission was found with higher influent load. The methanogenic and methanotrophic microbial populations were studied to clarify the mechanisms of CH₄ emission. FISH analysis showed highest amounts of methanogens and methanotrophs in the Z. latifolia and Tytha latifolia systems. Linear regression between CH₄ emission and environmental parameters showed that the regression lines were not forced to pass through the origin, and the slopes of the lines of different systems were allowed to vary between vegetation cover.     

Evaluating the performance of multiple remote sensing indices to predict the spatial variability of ecosystem structure and functioning in Patagonian steppes

Assessing the spatial variability of ecosystem structure and functioning is an important step towards developing monitoring systems to detect changes in ecosystem attributes that could be linked to desertification processes in drylands. Methods based on ground-collected soil and plant indicators are being increasingly used for this aim, but they have limitations regarding the extent of the area that can be measured using them. Approaches based on remote sensing data can successfully assess large areas, but it is largely unknown how the different indices that can be derived from such data relate to ground-based indicators of ecosystem health. We tested whether we can predict ecosystem structure and functioning, as measured with a field methodology based on indicators of ecosystem functioning (the landscape function analysis, LFA), over a large area using spectral vegetation indices (VIs), and evaluated which VIs are the best predictors of these ecosystem attributes. For doing this, we assessed the relationship between vegetation attributes (cover and species richness), LFA indices (stability, infiltration and nutrient cycling) and nine VIs obtained from satellite images of the MODIS sensor in 194 sites located across the Patagonian steppe. We found that NDVI was the VI best predictor of ecosystem attributes. This VI showed a significant positive linear relationship with both vegetation basal cover (R² = 0.39) and plant species richness (R² = 0.31). NDVI was also significantly and linearly related to the infiltration and nutrient cycling indices (R² = 0.36 and 0.49, respectively), but the relationship with the stability index was weak (R² = 0.13). Our results indicate that VIs obtained from MODIS, and NDVI in particular, are a suitable tool for estimate the spatial variability of functional and structural ecosystem attributes in the Patagonian steppe at the regional scale.     

Extinction thresholds and negative responses of Afrotropical ant-following birds to forest cover loss in oil palm and agroforestry landscapes

Afrotropical ant-following birds are vulnerable to forest loss and disturbance, but critical habitat thresholds regarding their abundance and species richness in human-dominated landscapes, including industrial oil palm plantations, have never been assessed. We measured forest cover through Landsat imagery and recorded species richness and relative abundance of 20 ant-following birds in 48 plots of 1-km², covering three landscapes of Southwest Cameroon: Korup National Park, smallholder agroforestry areas (with farms embedded in forest), and an industrial oil palm plantation. We evaluated differences in encounter frequency and species richness among landscapes, and the presence of critical thresholds through enhanced adaptive regression through hinges. All species were detected in Korup National Park and the agroforestry landscape, which had similar forest cover (>85%). Only nine species were found in the oil palm plantation (forest cover = 10.3 ± 3.3%). At the 1-km² scale, the number of species and bird encounters were comparable in agroforests and the protected area: mean species richness ranged from 12.2 ± 0.6 in the park and 12.2 ± 0.6 in the agroforestry matrix to 1.0 ± 0.4 in the industrial oil palm plantation; whereas encounters decreased from 34.4 ± 3.2 to 26.1 ± 2.9 and 1.3 ± 0.4, respectively. Bird encounters decreased linearly with decreasing forest cover, down to an extinction threshold identified at 24% forest cover. Species richness declined linearly by ca. one species per 7.4% forest cover lost. We identified an extinction threshold at 52% forest cover for the most sensitive species (Criniger chloronotus, Dicrurus atripennis, and Neocossyphus poensis). Our results show that substantial proportions of forests are required to sustain complete ant-following bird assemblages in Afrotropical landscapes and confirm the high sensitivity of this bird guild to deforestation after industrial oil palm development. Securing both forest biodiversity and food production in an Afrotropical production landscape may be best attained through a combination of protected areas and wildlife-friendly agroforestry.     

Does using species abundance data improve estimates of species diversity from remotely sensed spectral heterogeneity?

Different approaches for the assessment of biodiversity by means of remote sensing were developed over the last decades. A new approach, based on the spectral variation hypothesis, proposes that the spectral heterogeneity of a remotely sensed image is correlated with landscape structure and complexity which also reflects habitat heterogeneity which itself is known to enhance species diversity. In this context, previous studies only applied species richness as a measure of diversity. The aim of this paper was to analyze the relationship of richness and abundance-based diversity measures with spectral variability and compare the results at two scales. At three different test sites in Central Namibia, measures of vascular plant diversity was sampled at two scales – 100 m² and 1000 m². Hyperspectral remote sensing data were collected for the study sites and spectral variability, was calculated at plot level. Ordinary least square regression was used to test the relationship between species richness and the abundance-based Shannon Index and spectral variability. We found that Shannon Index permanently achieved better results at all test sites especially at 1000 m², Even when all sites where pooled together, Shannon Index was still significantly related with spectral variability at 1000 m². We suggest incorporating abundance-based diversity measures in studies of relationships between ecological and spectral variability. The contribution made by the high spectral and spatial resolution of the hyperspectral sensor is discussed.     

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.     

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.     

Net primary productivity and seasonality of temperature and precipitation are predictors of the species richness of the Damselflies in the Amazon

Several hypotheses have been proposed to explain the mechanisms that generate temporal and spatial species richness patterns. We tested four common hypotheses (water, energy, climatic heterogeneity and net primary productivity) to evaluate which factors best explain patterns of Zygoptera species richness. Of these, we predicted that climatic heterogeneity would be the most important predictor for Zygoptera richness patterns. We sampled communities of adult Zygoptera in 100 small Amazonian streams. Based on generalized linear mixed models (GLMM), we found that net primary productivity and climatic heterogeneity comprised the best model of Zygoptera species richness in Amazonian streams, with an pseudo r² of 39.5%. Results indicate that species richness increases by one species per 1 kg of biomass per square meter in NPP, or with an increase of 2 °C in air temperature variability. Our work corroborates a recent study with other taxa in Brazilian Bioms. This suggests that temporal variation in climate and net primary productivity are important predictors of the macroecological patterns of richness for aquatic organisms in tropical regions.     

Effects of plant diversity on biomass production and substrate nitrogen in a subsurface vertical flow constructed wetland

Most biodiversity experiments have been conducted in grassland ecosystems with nitrogen limitation, while little research has been conducted on relationships between plant biomass production, substrate nitrogen retention and plant diversity in wetlands with continuous nitrogen supply. We conducted a plant diversity experiment in a subsurface vertical flow constructed wetland for treating domestic wastewater in southeastern China. Plant aboveground biomass production ranged from 20 to 3121 g m^?2 yr^?1 across all plant communities. In general, plant biomass production was positively correlated with species richness (P = 0.001) and functional group richness (P = 0.001). Substrate nitrate concentration increased significantly with increasing plant species richness (P = 0.046), but not with functional group richness (P = 0.550). Furthermore, legumes did not affect biomass production (P = 0.255), retention of substrate nitrate (P = 0.280) and ammonium (P = 0.269). Compared to the most productive of the corresponding monocultures, transgressive overyielding of mixed plant communities did not occur in most polycultures. Because greater diversity of plant community led to higher biomass production and substrate nitrogen retention, thus we recommend that plant biodiversity should be incorporated in constructed wetlands to improve wastewater treatment efficiency.     

Grazing and an invasive grass confound spatial pattern of exotic and native grassland plant species richness

Previous work has shown exotic and native plant species richness are negatively correlated at fine spatial scales and positively correlated at broad spatial scales. Grazing and invasive plant species can influence plant species richness, but the effects of these disturbances across spatial scales remain untested. We collected species richness data for both native and exotic plants from five spatial scales (0.5–3000 m²) in a nested, modified Whittaker plot design from severely grazed and ungrazed North American tallgrass prairie. We also recorded the abundance of an abundant invasive grass, tall fescue (Schedonorus phoenix (Scop.) Holub), at the 0.5-m² scale. We used linear mixed-effect regression to test relationships between plant species richness, tall fescue abundance, and grazing history at five spatial scales. At no scale was exotic and native species richness linearly related, but exotic species richness at all scales was greater in grazed tracts than ungrazed tracts. Native species richness declined with increasing tall fescue abundance at all five spatial scales, but exotic species richness increased with tall fescue abundance at all but the broadest spatial scales. Severe grazing did not reduce native species richness at any spatial scale. We posit that invasion of tall fescue in this working landscape of originally native grassland plants modifies species richness-spatial scale relationships observed in less disturbed systems. Tall fescue invasion constitutes a unique biotic effect on plant species richness at broad spatial scales.     

Anuran species richness,complementarity and conservation conflicts in Brazilian Cerrado

Broad-scale correlations between species richness and human population suggest that processes driving species richness, mainly related to high ecological productivity, may also drive human populations. However, it is still under debate if this coincidence implies conflicts between biodiversity conservation and human development. In this paper, we analyzed the relationships among human population size, species richness and irreplaceability in Brazilian Cerrado. We analyzed a dataset with 131 species of anurans distributed in 181 cells with 1° of spatial resolution covering the biome. We found a positive correlation between human population size and anuran species richness (r = 0.46; P = 0.033 with 19.5 geographically effective degrees of freedom, v*), but the irreplaceability of each cell was poorly correlated with human population size (r = 0.075; P = 0.323; v* = 173.9). The 17 cells in the 97 optimal reserve networks contained a total human population ranging from 2942,195 to 4319,845 people, representing on average 11.8% of the human population in the entire Cerrado grid. The comparison of these observed values with 10,000 values from randomly generated networks suggests a relatively high flexibility in optimal complementarity sets for reserve selection. Our results indicated that correlation between richness and human population does not necessarily result in conflicts, given the opportunities for conciliating conservation and development. However, the analyses performed here are initial explorations within the framework of conservation biogeography, so more detailed studies are necessary to establish conservation planning at regional and local scales.     

Biased richness and evenness relationships within Shannon–Wiener index values

The purpose of this analysis was to empirically model and graphically illustrate the numerical relationships between richness (S, 4–35 species) and evenness (E) with respect to Shannon–Wiener index (H′, log_e-based) values. Thirty-two richness-based third-order polynomial regression models (R > 0.99, P < 0.001, n = 28–71) were constructed to characterize these relationships. A composite diagram showed richness varied curvilinearly, with steepness increasing and the spacing between curves decreasing with greater evenness and H′. Maximum H′ values for each richness curve were equal to log_e S (when E = 1), whereas minima were approximated by evenness values of ∼1/S (when H′ = 0). It was concluded from multiple and polynomial regression analyses that: (i) evenness contributed more than richness (E:S ≥3:1) to determining H′, based on standardized partial beta-coefficients; (ii) the differential in E:S ratios increased with greater richness; (iii) the patterns of H′ sample variation between maximum unevenness and perfect evenness was convexo-concave shaped; and (iv) richness as an explanatory variable of H′ was likely an artifact of evenness (0–1 scale) being rescaled according to individual H′ maxima. H′ was redefined as a logarithm-weighted measure of evenness at a given level of richness, which means H′ is either an imperfect index of diversity or a biased measure of evenness. It was also found that the fundamental components of the Shannon–Wiener index measure dominance concentration rather than evenness, with the reversal in emphasis due to multiplication of the H′ equation by −1. H′-derived effective species numbers (exp H′, D) increasingly deviated from those of the diversity model D = S × E in response to increasing richness (up to 69% for 35 species), particularly when evenness was between 0.15 and 0.40. Of two cross-validated H′ prediction methods (P < 0.001, n = 325), the collective use of individual richness-based polynomial regression equations (r = 0.954) was better than a single multiple regression model that incorporated a broad spectrum of richness levels (r = 0.882). A simple graphic model was constructed to illustrate patterns of evenness variation as a function of changing richness and H′ values. Based on the identified biases, particularly E:S ratios, it was recommended that use of H′ be discontinued as a basis for assessing diversity in ecological research or, at the very least, accompanied by independent analyzes of richness and evenness.     

A probability distribution model of small -scale species richness in plant communities

We devised a probability distribution model that best expressed species richness per quadrat in grassland communities, and clarified the mechanism by which the mean richness per quadrat was always larger than the variance among quadrats. Our model will aid in the understanding of community structures, and allow comparisons among different communities. The model was constructed based on relatively simple theoretical assumptions about the mechanisms in play in target communities. We assumed in the model that the number of species occurring in an actual quadrat, j, is the sum of “the fundamental number of species”, k (constant), and “a fluctuating number of species”, i (a Poisson variate with the mean of μ); that is, j = k + i, where i, j and k are non-negative integers. The probability that j species occur in a quadrat is given by a Poisson-like distribution (extended Poisson), with two parameters k and μ. The mean species richness in the probability distribution is expressed by λ (= k + μ), and the variance is λ − k. The proposed model afforded a good fit for the observed frequency distribution of species richness per quadrat. If even one species is common among many quadrats, the mean number of species per quadrat is greater than the variance. The greater the number of common species among quadrats is, the larger is the value of k, and then the more pronounced is the difference between the mean and the variance (although the variance does not change). We fitted the model to 55 datasets collected by ourselves from grasslands in various locations (Tibet, Inner Mongolia, Slovakia, or Japan), with varying quadrat size (0.25, 0.0625, or 0.01 m²), and under differing management status (various stocking densities).     

The effect of plant succession on slope stability

The aim of this field investigation was to study the enrichment of biodiversity of the slope at an early phase of succession, initiated by selected pioneers, and to study how this enrichment related to enhancement of the slope stability. Four experimental plots, with differing plant pioneers and number of species (diversity), were designed in order to assess the effects of plant succession on slope stability. Plant growth pattern was assessed by observing the increment in species diversity (number), species frequency and plant biomass. Higher vegetation biomass in a mixed culture situation (LLSS) in the field with Leucaena leucocephala as a pioneer, marked an increase in species diversity after 24 months of observation. In contrast, G (grasses and legume creepers) plot revealed the slowest rate of succession and the lowest above-ground biomass amongst the plots. The mixed-culture plot without L. leucocephala (SS) had also shown a lower biomass, a similar phenomenon observed in a plot grown by L. leucocephala (LL) with low plant diversity. Consequently, these plant growth patterns gave a positive effect on slope stability where the regression study showed that the shear strength was much affected by plant biomass. Meanwhile, throughout the succession process in LLSS plot, root length density reached the highest value amongst the plots, 23 Km m^?3. In relation to this, the saturation level of the slope indicates the unsaturated condition of the soil which resulted in the enhancement of both soil penetrability and soil shear strength of the plot. These attributes reveal a strong positive relationship between the process of natural succession and the stability of slopes.     

Ecological niche modelling of the distribution of cold-water coral habitat using underwater remote sensing data

Despite a growing appreciation of the need to protect sensitive deep sea ecosystems such as cold-water corals, efforts to map the extent of their distribution are limited by their remoteness. Here we develop ecological niche models to predict the likely distributions of cold-water corals based on occurrence records and data describing environmental parameters (e.g. seafloor terrain attributes and oceanographic conditions). This study has used bathymetric data derived from ship-borne multibeam swath systems, species occurrence data from remotely operated vehicle video surveys and oceanographic parameters from hydrodynamic models to predict coral locations in regions where there is a paucity of direct observations. Predictions of the locations of the scleractinian coral, Lophelia pertusa are based primarily upon ecological niche modelling using a genetic algorithm. Its accuracy has been quantified at local (~ 25 km²) and regional scales (~ 4000 km²) along the Irish continental slope using a variety of error assessment techniques and a comparison with another ecological niche modelling technique. With appropriate choices of parameters and scales of analyses, ecological niche modelling has been effective in predicting the distributions of species at local and regional scales. Refinements of this approach have the potential to be particularly useful for ocean management given the need to manage areas of sensitive habitat where survey data are often limited.     

Spatial pattern model of herbaceous plant mass at species level

Individual plant species distribute according to their own spatial pattern in a community. In this study, we proposed an index for measuring the spatial heterogeneity in mass (dry weight) of individual plant species. First, we showed that the frequency distributions for mass of individual plant species per quadrat in a plant community are expressed using the gamma distribution with two parameters of λ (mean) and p. The parameter p is a measure indicating the level of spatial heterogeneity of plant mass as follows: (1) when p = 1, the plant mass per quadrat has a random pattern; (2) when p > 1, the plant mass has a spatial pattern with a lower heterogeneity than would be expected in the random pattern; and (3) when p < 1, the plant mass has a spatial pattern with a higher heterogeneity than would be expected in the random pattern. The p value for a given species can easily be calculated by the following equation if we use the moment method: (mean plant mass among quadrats)² / (variance of plant mass among quadrats). The scatter diagram of (λ, p) for individual plant species, exhibits the spatial characteristics of each species in the community. We illustrated two examples of the (λ, p) diagram from data for individual species composing actual communities in a semi-natural grassland and a weedy grassland. Frequency distributions for the plant mass of individual species per quadrat followed the gamma distribution, and indi vidual species exhibited an inherent level of spatial heterogeneity.     

Defining quantitative stream disturbance gradients and the additive role of habitat variation to explain macroinvertebrate taxa richness

Most studies dealing with the use of ecological indicators and other applied ecological research rely on some definition or concept of what constitutes least-, intermediate- and most-disturbed condition. Currently, most rigorous methodologies designed to define those conditions are suited to large spatial extents (nations, ecoregions) and many sites (hundreds to thousands). The objective of this study was to describe a methodology to quantitatively define a disturbance gradient for 40 sites in each of two small southeastern Brazil river basins. The assessment of anthropogenic disturbance experienced by each site was based solely on measurements strictly related to the intensity and extent of anthropogenic pressures. We calculated two indices: one concerned site-scale pressures and the other catchment-scale pressures. We combined those two indices into a single integrated disturbance index (IDI) because disturbances operating at both scales affect stream biota. The local- and catchment-scale disturbance indices were weakly correlated in the two basins (r = 0.21 and 0.35) and both significantly (p < 0.05) reduced site EPT (insect orders Ephemeroptera, Plecoptera, Trichoptera) richness. The IDI also performed well in explaining EPT richness in the basin that presented the stronger disturbance gradient (R² = 0.39, p < 0.001). Natural habitat variability was assessed as a second source of variation in EPT richness. Stream size and microhabitats were the key habitat characteristics not related to disturbances that enhanced the explanation of EPT richness over that attributed to the IDI. In both basins the IDI plus habitat metrics together explained around 50% of EPT richness variation. In the basin with the weaker disturbance gradient, natural habitat explained more variation in EPT richness than did the IDI, a result that has implications for biomonitoring studies. We conclude that quantitatively defined disturbance gradients offer a reliable and comprehensive characterization of anthropogenic pressure that integrates data from different spatial scales.