Methane indicator values for peatlands: a comparison of species and functional groups

Previous studies have shown a correspondence between the abundance of particular plant species and methane flux. Here, we apply multivariate analyses, and weighted averaging, to assess the suitability of vegetation composition as a predictor of methane flux. We developed a functional classification of the vegetation, in terms of a number of plant traits expected to influence methane production and transport, and compared this with a purely taxonomic classification at species level and higher. We applied weighted averaging and indirect and direct ordination approaches to six sites in the United Kingdom, and found good relationships between methane flux and vegetation composition (classified both taxonomically and functionally). Plant species and functional groups also showed meaningful responses to management and experimental treatments. In addition to the United Kingdom, we applied the functional group classification across different geographical regions (Canada and the Netherlands) to assess the generality of the method. Again, the relationship appeared good at the site level, suggesting some general applicability of the functional classification. The method seems to have the potential for incorporation into large‐scale (national) greenhouse gas accounting programmes (in relation to peatland condition/management) using vegetation mapping schemes. The results presented here strongly suggest that robust predictive models can be derived using plant species data (for use in national‐scale studies). For trans‐national‐scale studies, where the taxonomic assemblage of vegetation differs widely between study sites, a functional classification of plant species data provides an appropriate basis for predictive models of methane flux.     

Quantifying tolerance indicator values for common stream fish species of the United States

The classification of fish species tolerance to environmental disturbance is often used as a means to assess ecosystem conditions. Its use, however, may be problematic because the approach to tolerance classification is based on subjective judgment. We analyzed fish and physicochemical data from 773 stream sites collected as part of the U.S. Geological Survey's National Water-Quality Assessment Program to calculate tolerance indicator values for 10 physicochemical variables using weighted averaging. Tolerance indicator values (TIVs) for ammonia, chloride, dissolved oxygen, nitrite plus nitrate, pH, phosphorus, specific conductance, sulfate, suspended sediment, and water temperature were calculated for 105 common fish species of the United States. Tolerance indicator values for specific conductance and sulfate were correlated (rho = 0.87), and thus, fish species may be co-tolerant to these water-quality variables. We integrated TIVs for each species into an overall tolerance classification for comparisons with judgment-based tolerance classifications. Principal components analysis indicated that the distinction between tolerant and intolerant classifications was determined largely by tolerance to suspended sediment, specific conductance, chloride, and total phosphorus. Factors such as water temperature, dissolved oxygen, and pH may not be as important in distinguishing between tolerant and intolerant classifications, but may help to segregate species classified as moderate. Empirically derived tolerance classifications were 58.8% in agreement with judgment-derived tolerance classifications. Canonical discriminant analysis revealed that few TIVs, primarily chloride, could discriminate among judgment-derived tolerance classifications of tolerant, moderate, and intolerant. To our knowledge, this is the first empirically based understanding of fish species tolerance for stream fishes in the United States.     

Iteratio: calculating environmental indicator values for species and relevés

Question: Is it possible to translate vegetation maps into reliable thematic maps of site conditions? Method: This paper presents a new method, called Iteratio, by which a coherent spatial overview of specific environmental conditions can be obtained from a comprehensive vegetation survey of a specific area. Iteratio is a database application which calculates environmental indicator values for vegetation samples (relevés) on the basis of known indicator values of a limited number of plant species. The outcome is then linked to a digitalized vegetation map (map of plant communities) which results in a spatial overview of site conditions. Iteratio requires the indicator values of a minimum of 10–20% of the species occurring. The species are given a relative weight according to their amplitudes: species with a narrow range are weighted stronger, species with a broad range are weighted weaker. Conclusion: The method presented here enables a coherent assessment of site conditions on the basis of a vegetation survey and the indicator values of a limited number of plant species.     

Prolonged nitrate exhaustion and diatom mortality: a comparison of polar and temperate Thalassiosira species

The survival of two diatom species. Thalassiosira antarcticaComber isolated from the Southern Ocean and Thalassiosira rotulaMeunier isolated from the North Sea. was investigated duringa 21 day nitrate-exhaustion period, both in the light and indarkness. Both species endured 3 weeks of nitrate exhaustionin the light by forming a physiological resting state, characterizedby the development of shrunken, chlorotic protoplasts, a decreasein photosynthetic capacity and the accumulation of particulateorganic carbon (POC). These resting cells of both species stillresumed growth after 21 days of nitrate exhaustion, althoughthe viability of the cells decreased with time of nitrate exhaustion.Growth rates during subsequent growth experiments decreasedwith lengthening pre-incubation time in nitrate exhaustion.The viability of T.antarctica resting cells was lower than thatof T.rotula. After 21 days in nitrate exhaustion, T.antarcticagrew at 31% of the initial division rate, whereas the growthrate of T.rotula was 61%. When growth was resumed, accumulatedPOC decreased and paniculate organic nitrogen (PON), chlorophylla and photosynthetic carbon assimilation increased during thesubsequent 5 day growth periods, but never reached initial values.Darkness had no effect on cellular POC. PON and chlorophylla content of both species. In T.rotula, the capacity for photosyntheticcarbon assimilation decreased to almost zero during the 21 daydark period, although survival capacity was not affected. Aftera lag phase of 1–5 days, growth was resumed at initialgrowth rates, indicating that the bulk of cells of both diatomspecies were still viable. Thus, in the dark, both Thalassiosiraspecies survived nutrient exhaustion without physiological impairment.     

Quantifying sexual selection: a comparison of competing indices with mating system data from a terrestrially breeding salamander

Calculations for quantifying the potential for sexual selection remain controversial. Many indices have been promoted in the literature, but each has unique sets of advantages and disadvantages. Using marbled salamanders, I evaluated the performance of several measures by manipulating intensity of sexual selection in experimental breeding replicates of varying operational sex ratio. Theory predicts that sexual selection among males will be higher when sex ratio is male‐biased and lower when female‐biased. I used microsatellite data to assign hatchling parentage, estimate adult fitness, and calculate several indices of inequality for quantifying sexual selection. Opportunity for selection and Morisita index always conformed to theoretical expectations, which was not the case for index of resource monopolization, standardized Morisita index, or binomial skew index. Although I conclude that opportunity for selection is advantageous in sexual selection studies because of its link to formal theory, this should be tested against the null hypothesis of random variation in ambiguous cases. In the present study, although variation in both reproductive and mating success was high when quantified using opportunities for selection, it was only significantly greater than random expectations for reproductive success. This study provides further empirical support for the continued use of opportunity for selection in sexual selection studies. © 2010 The Linnean Society of London, Biological Journal of the Linnean Society, 2010, 99 , 73–83.     

Relation of abundance-weighted averages of diatom indicator values to measured environmental conditions in standing freshwaters

Abundance-weighted averages of diatom indicator values for pH, salinity, organic nitrogen availability, oxygen saturation, saprobity and trophic status according to van Dam et al. [Neth. J. Aquat. Ecol. 28 (1994) 117] were calculated for surface sediment and epiphytic diatom assemblages in 186 standing waters distributed throughout Flanders, Belgium, and tested against environmental variables measured in the water column, covering water chemistry, trophic status and organic load. With exception of the pH indication, most scores related rather poorly to variables which they are assumed to reflect and correlated even more strongly to non-target variables. For instance, the trophic indication provided a measure of pH and base status rather than of nutrient levels or phytoplankton productivity. Relations to measured variables differed according to the pH regime. Correction for uneven distribution of indicator values in the species pool usually yielded little improvement and was detrimental in some cases. Compared to epiphyton, weighted averages of species indicator values derived from sediment assemblages tended to be higher in water bodies yielding the most elevated indication scores. Except for the pH and salinity indication, differences between weighted averages pertaining to these different habitats were often considerable. Limitations to the use of abundance-weighted averages of diatom indicator values for environmental monitoring and assessment of lentic waters are discussed.     

Reliability of Ellenberg indicator values for moisture,nitrogen and soil reaction: a comparison with field measurements

Abstract. Ellenberg indicator values for moisture, nitrogen and soil reaction were correlated with measured soil and vegetation parameters. Relationships were studied through between‐species and between‐site comparisons, using data from 74 roadside plots in 14 different plant communities in The Netherlands forming a wide range. Ellenberg moisture values correlated best with the average lowest moisture contents in summer. Correlations with the annual average groundwater level and the average spring level were also good. Ellenberg N‐values appeared to be only weakly correlated with soil parameters, including N‐mineralization and available mineral N. Instead, there was a strong relation with biomass production. We therefore endorse Hill & Carey's (1997) suggestion that the term N‐values be replaced by ‘productivity values'. For soil reaction, many species values appeared to need regional adjustment. The relationship with soil pH was unsatisfactory; mean indicator values were similar for all sites at pH > 4.75 because of wide species tolerances for intermediate pH levels. Site mean reaction values correlated best (r up to 0.92) with the total amount of calcium (exchangeable Ca²⁺ plus Ca from carbonates). It is therefore suggested that reaction values are better referred to as ‘calcium values'. Using abundance values as weights when calculating mean indicator values generally improved the results, but, over the wide range of conditions studied, differences were small. Indicator values for bryophytes appeared well in line with those for vascular plants. It was noted that the frequency distributions of indicator values are quite uneven. This creates a tendency for site mean values to converge to the value most common in the regional species pool. Although the effect on overall correlations is small, relationships tended to be less linear. Uneven distributions also cause the site mean indicator values at which species have their optimum to deviate from the actual Ellenberg values of these species. Suggestions for improvements are made. It is concluded that the Ellenberg indicator system provides a very valuable tool for habitat calibration, provided the appropriate parameters are considered.     

A comparison of statistical approaches for modelling fish species distributions

SUMMARY 1. The prediction of species distributions is of primary importance in ecology and conservation biology. Statistical models play an important role in this regard; however, researchers have little guidance when choosing between competing methodologies because few comparative studies have been conducted. 2. We provide a comprehensive comparison of traditional and alternative techniques for predicting species distributions using logistic regression analysis, linear discriminant analysis, classification trees and artificial neural networks to model: (1) the presence/absence of 27 fish species as a function of habitat conditions in 286 temperate lakes located in south‐central Ontario, Canada and (2) simulated data sets exhibiting deterministic, linear and non‐linear species response curves. 3. Detailed evaluation of model predictive power showed that approaches produced species models that differed in overall correct classification, specificity (i.e. ability to correctly predict species absence) and sensitivity (i.e. ability to correctly predict speciespresence) and in terms of which of the study lakes they correctly classified. Onaverage, neural networks outperformed the other modelling approaches, although all approaches predicted species presence/absence with moderate to excellent success. 4. Based on simulated non‐linear data, classification trees and neural networks greatly outperformed traditional approaches, whereas all approaches exhibited similar correct classification rates when modelling simulated linear data. 5. Detailed evaluation of model explanatory insight showed that the relative importance of the habitat variables in the species models varied among the approaches, where habitat variable importance was similar among approaches for some species and very different for others. 6. In general, differences in predictive power (both correct classification rate and identity of the lakes correctly classified) among the approaches corresponded with differences in habitat variable importance, suggesting that non‐linear modelling approaches (i.e. classification trees and neural networks) are better able to capture and model complex, non‐linear patterns found in ecological data. The results from the comparisons using simulated data further support this notion. 7. By employing parallel modelling approaches with the same set of data and focusing on comparing multiple metrics of predictive performance, researchers can begin to choose predictive models that not only provide the greatest predictive power, but also best fit the proposed application.     

Preliminary results of a classification of fifty-one selected northeastern Wisconsin Lakes (USA) using indicator diatom species

Diatom species lists were generated for 51 lakes in northeastern Wisconsin, and then classified by two-way indicator species analysis (TWINSPAN). The lakes were initially divided into two main groupings: Group I lakes which were alkaline lakes of moderate to high productivity, and Group II lakes which were acid lakes of low productivity. Group I lakes were further divided into two subgroupings, and four levels. In total, twelve indicator diatom species were recognized during the TWINSPAN lake classification, these were: Achnanthes exigua Grun., A. lanceolata var. dubia Grun., Amphora ovalis var. Affinis (Kütz.) V.H. ex Det., A. perpusilla (Grun.) Grun., Cymbella cistula (Ehrenb.) Kirch., Diploneis elliptica (Kütz.) Cl., Eunotia pectinalis (O.F. Mull.) Rabh., Fragilaria vaucheriae (Kütz.) Peters., Frustulia rhomboides var. crassinervia (Bréb. ex W. Sm.) Ross, Navicula capitata Ehrenb., N. decussis Østr., and N. scutelloides W.Sm. ex Gregory.     

Homologous somatic association in Crepis species: a critical comparison of several statistical approaches

Somatic association of homologous chromosomes has been quantitatively studied in root tips of Crepis capillaris (2n=6), C. taraxicifolia (2n=8) and C. rubra (2n=10). Statistical analyses have been carried out on scattered metaphase plates. Homologous somatic association has been analyzed by applying two statistical approaches: the method of corrected distances and the method of generalized distances. Their validity and proper utilization are discussed on the basis of a comparison of results obtained when both methods are applied to the same scattered metaphase plates of material of which previous evidence of homologous somatic association had been obtained in radial metaphases. The following conclusions have been drawn: (i) in the case of the method of corrected distances the contradictory results can be attributed to an improper use of the statistical approach since the theoretical model requires the chromosomes (centromeres) to be uniformly distributed throughout a circle, (ii) since the theoretical model of the generalized distance method does not have any requirement, serious doubts about its validity arise from the negative results obtained.     

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches

Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S‐SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient. Location Two study areas in the Alps of Switzerland. Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S‐SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways – summing binary predictions, summing random draws of binomial trials and summing predicted probabilities – to obtain a final species count. Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S‐SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump‐shaped pattern of SR observed along the elevational gradient. The S‐SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S‐SDM approaches – the summed binomial trials based on predicted probabilities and summed predicted probabilities – do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S‐SDM approaches fail to appropriately reproduce the observed hump‐shaped patterns of SR along the elevational gradient. Main conclusions Macroecological approach and S‐SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S‐SDM by MEM predictions.     

Quantifying biodiversity: procedures and pitfalls in the measurement and comparison of species richness

Species richness is a fundamental measurement of community and regional diversity, and it underlies many ecological models and conservation strategies. In spite of its importance, ecologists have not always appreciated the effects of abundance and sampling effort on richness measures and comparisons. We survey a series of common pitfalls in quantifying and comparing taxon richness. These pitfalls can be largely avoided by using accumulation and rarefaction curves, which may be based on either individuals or samples. These taxon sampling curves contain the basic information for valid richness comparisons, including category–subcategory ratios (species-to-genus and species-to-individual ratios). Rarefaction methods – both sample-based and individual-based – allow for meaningful standardization and comparison of datasets. Standardizing data sets by area or sampling effort may produce very different results compared to standardizing by number of individuals collected, and it is not always clear which measure of diversity is more appropriate. Asymptotic richness estimators provide lower-bound estimates for taxon-rich groups such as tropical arthropods, in which observed richness rarely reaches an asymptote, despite intensive sampling. Recent examples of diversity studies of tropical trees, stream invertebrates, and herbaceous plants emphasize the importance of carefully quantifying species richness using taxon sampling curves.     

Evaluating the ecological realism of plant species distribution models with ecological indicator values

Species distribution models (SDMs) are routinely applied to assess current as well as future species distributions, for example to assess impacts of future environmental change on biodiversity or to underpin conservation planning. It has been repeatedly emphasized that SDMs should be evaluated based not only on their goodness of fit to the data, but also on the realism of the modeled ecological responses. However, possibilities for the latter are hampered by limited knowledge on the true responses as well as a lack of quantitative evaluation methods. Here we compared modeled niche optima obtained from European-scale SDMs of 1476 terrestrial vascular plant species with empirical ecological indicator values indicating the preferences of plant species for key environmental conditions. For each plant species we first fitted an ensemble SDM including three modeling techniques (GLM, GAM and BRT) and extracted niche optima for climate, soil, land use and nitrogen deposition variables with a large explanatory power for the occurrence of that species. We then compared these SDM-derived niche optima with the ecological indicator values by means of bivariate correlation analysis. We found weak to moderate correlations in the expected direction between the SDM-derived niche optima and ecological indicator values. The strongest correlation occurred between the modeled optima for growing degree days and the ecological indicator values for temperature. Correlations were weaker for SDM-derived niche optima with a more distal relationship to ecological indicator values (notably precipitation and soil moisture). Further, correlations were consistently highest for BRT, followed by GLM and GAM. Our method gives insight into the ecological realism of modeled niche optima and projected core habitats and can be used to improve SDMs by making a more informed selection of environmental variables and modeling techniques.     

A comparison of indices and measured values of eggshell thickness of different shell regions using museum eggs of 230 European bird species

The thickness of avian eggshells is used to assess shell quality in wild and domestic species, as an indicator of environmental pollution and as an adaptive explanation for shell maculation. Both direct measurements and calculated eggshell thickness indices (ETI) are used in such research, yet this is the first study to quantify, across a large spectrum of bird families (and thus egg shapes), the correlation between measured thicknesses and ETI. Furthermore, few studies have quantified thickness variation across the entire length of the shell, although this variation may influence both gas transfer and embryonic development. We measured the thickness of 942 eggshells of 230 European bird species from the Class II material at the Natural History Museum, Tring, UK, both in the conventional manner, at the equator through the blowhole and, uniquely, after a single longitudinal, cut at its equator at the blunt and pointed ends. Over half of the samples revealed shell defects, cautioning against the indiscriminate use of museum specimens. Strong positive associations were found between species‐specific means of shell thickness with each other and also with ETI, especially those derived from Schönwetter's ‘Handbuch der Oologie’ method, validating the interspecific comparative use of ETI. Thickness measurements and ETI factors are provided for all 230 species. Eggshells were usually thinner at the blunt end (the location of the air sac) than at the equator, but of equal thickness in passerine eggs. This difference was greatest in species producing elongate eggs and suggests that there is a functional significance of shell thickness variation among species that requires further investigation.