Evaluation of approaches for measuring taxonomic completeness of lake profundal macroinvertebrate assemblages

1. Benthic macroinvertebrates (MI) are commonly used to assess freshwater ecosystems with the reference condition approach. Such assessments necessitate control for natural community variation, either by categorical typologies or by predictive models that have been widely and successfully developed for running water biota but not previously for lake profundal invertebrates. 2. We evaluated four modelling techniques [multivariate regression tree (MRT), limiting environmental differences, nonparametric multiplicative regression (NPMR) and River Invertebrate Prediction And Classification System (RIVPACS) and the operative Finnish lake typology for assessing taxonomic completeness (observed‐to‐expected number of taxa, O/E) of profundal MI assemblages. We used data from 74 and 33 minimally disturbed reference lake basins for calibration and validation of the approaches, respectively, and 72 test basins subject to various anthropogenic pressures to evaluate sensitivity to detect impact. Either all predicted taxa (threshold probability of capture P_t = 0+) or only those predicted to be captured with ≥0.25 probability were used to calculate O/E. 3. With P_t = 0.25, all four modelling approaches were accurate (mean O/E = 0.966–1.053) but imprecise (SD of O/E = 0.279–0.304) in predicting the fauna actually observed in validation sites. All models were subtly more precise than a null model (mean 1.038, SD 0.343) or the typology (1.046, 0.327). The taxon‐specific NPMR model was slightly more precise than the other three models based on site groupings. 4. The O/E values correlated relatively weakly (r = 0.55–0.86) among the approaches, which thus produced contrasting lake‐specific assessments, despite their seemingly comparable performances. Indeed, typology, suggesting that MI assemblages were impaired in 56% of test sites, was more sensitive than the other approaches (26–46%) as an indicator of human‐induced deterioration. However, this greater ostensible sensitivity seemed to be biased, as lake morphometry, a main driver of natural community variation, remained uncontrolled by the typology. 5. Generally, our exercise illustrates the inconclusiveness of the common validation criteria for the assessment methods. The apparent poor predictability of the profundal fauna, irrespective of the method, may partly stem from large observation error, which could be alleviated by more intensive sampling. However, instead of an O/E‐taxa index, some other metric encompassing quantitative aspects might be preferable for assessing these species‐poor communities.     

Effects of locally rare taxa on the precision and sensitivity of RIVPACS bioassessment of freshwaters

1. An overall aim in freshwater bioassessment is to use biological methods, metrics and forms of indices which are precise, in that they give repeatable results between replicate samples, but which are also sensitive to changes in environmental impacts and stresses. Here we studied the effects of excluding taxa with site‐specific River Invertebrate Prediction and Classification System (RIVPACS)‐type model expected probabilities less than (or equal to) a threshold P_t (0.0, 0.1, 0.2,…,0.9) on the value, precision and power to detect biological effects of environmental stress using the observed to expected ratios (O/E) of biotic indices used to assess the ecological status of U.K. river sites. 2. Amongst the 614 high quality GB RIVPACS reference sites, excluding taxa with low expected probabilities of occurrence gave less total variation (i.e. lower SD) in the estimates O/E for number of taxa (O/E_TAXA) and the average score per taxon (O/E_ASPT). 3. A separate analysis of a replicated sampling study of sites from a wide range of physical types and qualities revealed that sampling variances in O/E for reference condition sites decreased as more locally rare taxa were excluded (but only up to P_t = 0.5 for O/E_ASPT). However, for moderately impacted and poor quality sites, estimates of both O/E_TAXA and O/E_ASPT based on all (P_t = 0.0) or most taxa (i.e. P_t ≤ 0.3) had lower sampling variances and were more precise. 4. Within a very large independent set of test sites with a wide range of perceived levels of environmental stress, increasing the threshold P_t led to systematic compression of the realised O/E scale towards unity. Specifically, with increasing threshold, O/E values >1 are on average reduced, while O/E values <1 have a tendency to be higher and closer to unity (with the exception of O/E_ASPT for the most severely stressed sites). 5. Accuracy and statistical power to detect environmental stress (measured by the percentage of stressed sites with O/E below the lower 10‐percentile value for reference sites) was very similar using O/E_TAXA for P_t up to 0.7. Using O/E_ASPT, power to detect overall general stress decreased slowly as P_t was increased; the rate of fall in power was slightly faster when restricted to sites subject to moderate or severe stress from organic inputs. 6. Taxa which are more sensitive to (organic) stresses [i.e. have high Biological Monitoring Working Party (BMWP) scores] tend to be naturally less widespread (i.e. amongst reference sites) and thus were found to have considerably lower average site‐specific expected probabilities; this may explain why the use of higher thresholds P_t can exclude more such sensitive taxa and lead to underestimation of the extent of impacts. 7. The standard U.K. RIVPACS sampling and sample processing procedures aim to identify all taxa within a sample. This may lead to a longer distribution tail of rarer (low probability) taxa than sampling methods based on a fixed count subsample and influence the practical effects of excluding rare taxa with low expected probabilities from bioassessments.     

Development of a RIVPACS-type predictive model for bioassessment of wadeable streams in Wyoming

RIVPACS models produce a community-level measure of biological condition known as O/E, which is derived from a comparison of the observed (O) biota with those expected (E) to occur in the absence of anthropogenic stress. We used benthic macroinvertebrate and environmental data collected at 925 stream monitoring stations, from 1993 to 2001, to develop, validate, and apply a RIVPACS model to assess the biological condition of wadeable streams in Wyoming. From this dataset, 296 samples were identified as reference, 157 of which were used to calibrate the model, 46 to validate it, and 93 to examine temporal variability in reference site O/E-values. We used cluster analyses to group the model development reference sites into biologically similar classes of streams and multiple discriminant function analysis to determine which environmental variables best discriminated among reference groups. A suite of 14 categorical and continuous environmental variables best discriminated among 15 reference groups and explained a large proportion of the natural variability in biota within the reference dataset. Eleven of the predictor variables were derived from GIS. As expected, mean O/E-values for reference sites used in model development and validation were near unity and statistically similar. Temporal variability in O/E-values for reference sites was low. Test site values ranged from 0 to 1.45 (mean = 0.73). The model was accurate in both space and time and precise enough (S.D. of O/E-values for calibration data = 0.17) to detect modest alteration in biota associated with anthropogenic stressors. Our model was comparable in performance to other RIVPACS models developed in the United States and can produce effective assessments of biological condition over a broad, ecologically diverse region. We also provide convincing evidence that RIVPACS models can be developed primarily with GIS-based predictor variables. This framework not only simplifies the extraction of predictor variable information while potentially reducing expenditures of time and money in the collection of predictor variable information, but opens the door for development and/or application of RIVPACS models in regions where there is a paucity of local-scale, abiotic information.     

ANNA: A new prediction method for bioassessment programs

1. Cluster analysis of reference sites with similar biota is the initial step in creating River Invertebrate Prediction and Classification System (RIVPACS) and similar river bioassessment models such as Australian River Assessment System (AUSRIVAS). This paper describes and tests an alternative prediction method, Assessment by Nearest Neighbour Analysis (ANNA), based on the same philosophy as RIVPACS and AUSRIVAS but without the grouping step that some people view as artificial. 2. The steps in creating ANNA models are: (i) weighting the predictor variables using a multivariate approach analogous to principal axis correlations, (ii) calculating the weighted Euclidian distance from a test site to the reference sites based on the environmental predictors, (iii) predicting the faunal composition based on the nearest reference sites and (iv) calculating an observed/expected (O/E) analogous to RIVPACS/AUSRIVAS. 3. The paper compares AUSRIVAS and ANNA models on 17 datasets representing a variety of habitats and seasons. First, it examines each model's regressions for Observed versus Expected number of taxa, including the r², intercept and slope. Second, the two models’ assessments of 79 test sites in New Zealand are compared. Third, the models are compared on test and presumed reference sites along a known trace metal gradient. Fourth, ANNA models are evaluated for western Australia, a geographically distinct region of Australia. The comparisons demonstrate that ANNA and AUSRIVAS are generally equivalent in performance, although ANNA turns out to be potentially more robust for the O versus E regressions and is potentially more accurate on the trace metal gradient sites. 4. The ANNA method is recommended for use in bioassessment of rivers, at least for corroborating the results of the well established AUSRIVAS‐ and RIVPACS‐type models, if not to replace them.     

River condition assessment may depend on the sub-sampling method: field live-sort versus laboratory sub-sampling of invertebrates for bioassessment

Aquatic macroinvertebrates are commonly used biological indicators for assessing the health of freshwater ecosystems. However, counting all the invertebrates in the large samples that are usually collected for rapid site assessment is time-consuming and costly. Therefore, sub-sampling is often done with fixed time or fixed count live-sorting in the field or with preserved material using sample splitters in the laboratory. We investigate the differences between site assessments provided when the two sub-sampling approaches (Live-sort and Lab-sort) were used in conjunction with predictive bioassessment models. The samples showed a method bias. The Live-sort sub-samples tended to have more large, conspicuous invertebrates and often fewer small and, or cryptic animals that were more likely to be found in Lab-sort samples where a microscope was used. The Live-sort method recovered 4–6 more taxa than Lab-sorting in spring, but not in autumn. The magnitude of the significant differences between Live-sort and Lab-sort predictive model outputs, observed to expected (O/E) taxa scores, for the same sites ranged from 0.12 to 0.53. These differences in the methods resulted in different assessments of some sites only and the number of sites that were assessed differently depended on the season, with spring samples showing most disparity. The samples may differ most in spring because many of the invertebrates are larger at that time (and thus are more conspicuous targets for live-sorters). The Live-sort data cannot be run through a predictive model created from Lab-sort data (and vice versa) because of the taxonomic differences in sub-sample composition and the sub-sampling methods must be standardized within and among studies if biological assessment is to provide valid comparisons of site condition. Assessments that rely on the Live-sorting method may indicate that sites are ‘less impaired’ in spring compared to autumn because more taxa are retrieved in spring when they are larger and more visible. Laboratory sub-sampling may return fewer taxa in spring, which may affect assessments relying on taxonomic richness.     

Additive impacts of deoxygenation and acidification threaten marine biota

Deoxygenation in coastal and open‐ocean ecosystems rarely exists in isolation but occurs concomitantly with acidification. Here, we first combine meta‐data of experimental assessments from across the globe to investigate the potential interactive impacts of deoxygenation and acidification on a broad range of marine taxa. We then characterize the differing degrees of deoxygenation and acidification tested in our dataset using a ratio between the partial pressure of oxygen and carbon dioxide (pO₂/pCO₂) to assess how biological processes change under an extensive, yet diverse range of pO₂ and pCO₂ conditions. The dataset comprised 375 experimental comparisons and revealed predominantly additive but variable effects (91.7%, additive; 6.0%, synergistic; and 2.3%, antagonistic) of the dual stressors, yielding negative impacts across almost all responses examined. Our data indicate that the pO₂/pCO₂‐ratio offers a simplified metric to characterize the extremity of the concurrent stressors and shows that more severe impacts occurred when ratios represented more extreme deoxygenation and acidification conditions. Importantly, our analysis highlights the need to assess the concurrent impacts of deoxygenation and acidification on marine taxa and that assessments considering the impact of O₂ depletion alone will likely underestimate the impacts of deoxygenation events and their ecosystem‐wide consequences.     

Regional and local drivers of macroinvertebrate assemblages in boreal springs

Aim To identify the most important environmental drivers of benthic macroinvertebrate assemblages in boreal springs at different spatial scales, and to assess how well benthic assemblages correspond to terrestrially derived ecoregions. Location Finland. Methods Benthic invertebrates were sampled from 153 springs across four boreal ecoregions of Finland, and these data were used to analyse patterns in assemblage variation in relation to environmental factors. Species data were classified using hierarchical divisive clustering (twinspan ) and ordinated using non‐metric multidimensional scaling. The prediction success of the species and environmental data into a priori (ecoregions) and a posteriori (twinspan ) groups was compared using discriminant function analysis. Indicator species analysis was used to identify indicator taxa for both a priori and a posteriori assemblage types. Results The main patterns in assemblage clusters were related to large‐scale geographical variation in temperature. A secondary gradient in species data reflected variation in local habitat structure, particularly abundance of minerogenic spring brooks. Water chemistry variables were only weakly related to assemblage variation. Several indicator species representing southern faunistic elements in boreal springs were identified. Discriminant function analysis showed poorer success in classifying sites into ecoregions based on environmental than on species data. Similarly, when classifying springs into the twinspan groups, classification based on species data vastly outperformed that based on environmental data. Main conclusions A latitudinal zonation pattern of spring assemblages driven by regional thermal conditions is documented, closely paralleling corresponding latitudinal patterns in both terrestrial and freshwater assemblages in Fennoscandia. The importance of local‐scale environmental variables increased with decreasing spatial extent. Ecoregions provide an initial stratification scheme for the bioassessment of benthic macroinvertebrates of North European springs. Our results imply that climate warming, landscape disturbance and degradation of spring habitat pose serious threats to spring biodiversity in northern Europe, especially to its already threatened southern faunistic elements.     

Quantifying the contribution of immigration to population dynamics: a review of methods,evidence and perspectives in birds and mammals

The demography of a population is often reduced to the apparent (or local) survival of individuals and their realised fecundity within a study area defined according to logistical constraints rather than landscape features. Such demographics are then used to infer whether a local population contributes positively to population dynamics across a wider landscape context. Such a simplistic approach ignores a fundamental process underpinning population dynamics: dispersal. Indeed, it has long been accepted that immigration contributed by dispersers that emigrated from neighbouring populations may strongly influence the net growth of a local population. To date however, we lack a clear picture of how widely immigration rate varies both among and within populations, in relation to extrinsic and intrinsic ecological conditions, even for the best‐studied avian and mammalian populations. This empirical knowledge gap precludes the emergence of a sound conceptual framework that ought to inform conservation and population ecology. This review, conducted on both birds and mammals, has thus three complementary objectives. First, we describe and evaluate the relative merits of methods used to quantify immigration and how they relate to widely applicable metrics. We identify two simple and unifying metrics to measure immigration: the immigration rate i_t defined as the ratio of the number of immigrants present in the population at time t + 1 and the total breeding population in year t, and π_t , the proportion of immigrants among new recruits (i.e. new breeders). Two recently developed methods are likely to provide the most valuable data on immigration in the near future: individual parentage (rather than population) assignments based on genetic sampling, and spatially explicit integrated population models combining multiple sources of demographic data (survival, fecundity and population counts). Second, we report on a systematic literature review of studies providing a quantitative measure of immigration. Although the diversity of methods employed precludes detailed analyses, it appears that the number of immigrants exceeds locally born individuals in recruitment for most avian populations (median π_t  = 0.57, N = 45 estimates from 37 studies), a figure twofold higher than estimated for mammalian populations (median π_t  = 0.26, N = 33 estimates from 11 studies). Third, recent quantitative studies reveal that immigration can be the main driver of temporal variation in population growth rates, across a wide array of demographic and spatial contexts. To what extent immigration acts as a regulatory process has however been considered only rarely to date and deserves more attention. Overall, it is likely that most populations benefit from immigrants without necessarily being sink populations. Furthermore, we suggest that quantitative estimates of immigration should be core to future demographic studies and plead for more empirical evidence about the ways in which immigration interacts with local demographic processes to shape population dynamics. Finally, we discuss how to tackle spatial population dynamics by exploring, beyond the classical source–sink framework, the extent to which populations exchange individuals according to spatial scale and type of population distribution throughout the landscape.     

Natural flow regime,temperature and the composition and richness of invertebrate assemblages in streams of the western United States

1. We tested how strongly aquatic macroinvertebrate taxa richness and composition were associated with natural variation in both flow regime and stream temperatures across streams of the western United States. 2. We used long‐term flow records from 543 minimally impacted gauged streams to quantify 12 streamflow variables thought to be ecologically important. A principal component analysis reduced the dimensionality of the data from 12 variables to seven principal component (PC) factors that characterised statistically independent aspects of streamflow: (1) zero flow days, (2) flow magnitude, (3) predictability, (4) flood duration, (5) seasonality, (6) flashiness and (7) base flow. K‐means clustering was used to group streams into 4–8 hydrologically different classes based on these seven factors. 3. We also used empirical models to estimate mean annual, mean summer and mean winter stream temperatures at each stream site. We then used invertebrate data from 63 sites to develop Random Forest models to predict taxa richness and taxon‐specific probabilities of capture at a site from flow and temperature. We used the predicted taxon‐specific probabilities of capture to estimate how well predicted assemblages matched observed assemblages as measured by RIVPACS‐type observed/expected (O/E) indices and Bray–Curtis dissimilarities. 4. Macroinvertebrate taxon richness was only weakly associated with streamflow and temperature variables, implying that other factors more strongly influenced taxa richness. 5. In contrast to taxa richness, taxa composition was strongly associated with streamflow and temperature. Predictions of taxa composition (O/E and Bray–Curtis) were most precise when both temperature and streamflow PC factors were used, although predictions based on either streamflow PC factors or temperature alone were also better than null model predictions. Of the seven aspects of the streamflow regime we examined, variation in baseflow conditions appeared to be most directly associated with invertebrate biotic composition. We were also able to predict assemblage composition from the conditional probabilities of hydrological class membership nearly as well as Random Forests models that were based directly on continuous PC factors. 6. Our results have direct implication for understanding the relative importance of streamflow and temperature in regulating the structure and composition of stream assemblages and for improving the accuracy and precision of biological assessments.     

The growth–mortality relationship in larval cohorts of Sardinops melanostictus,revealed by using two new approaches to analyse longitudinal data from otoliths

The growth–mortality relationship was assessed for larval cohorts of the Japanese sardine Sardinops melanostictus using two new approaches: (1) repeat measures in general linear model (RM‐GLMs) and (2) the autoregressive‐individual method (AIM). Both methods were compared to the traditional approach in which repeat‐measure ANOVA was used to compare the changes in increment width (W_I) at age and otolith radii (R_O) at age between individuals from an original population and survivors. In RM‐GLMs, both the W_I at age and R_O at age (i.e. at 5, 10, 15 and 20 days) were used as the dependent variables, and the standardized residuals of both regressions R_O and age and R_O and total length (L_T), age class, and day of the year as independent variables. A significant increase in W_I at age and R_O at age from younger to older age classes was seen as indicative of growth‐dependent selection. In AIM, the R_O‐at‐age relationship for each fish was fitted for the first 20 days, using autoregression, and then the growth traits (i.e. slopes) between the original cohorts and survivors were compared using ANOVA. In the traditional approach, the W_I at age and R_O at age for the first 20 days of an original population were compared with those of survivors sampled in later stages. GLMs and traditional approaches supported the growth rate (i.e. the faster an individual grows, the higher its probability of survival) and bigger is better (i.e. larger individuals at any given age will have lower probability of mortality than smaller individuals of the same age) mechanisms. Furthermore, AIM showed that individuals from original cohorts had lower otolith growth rates than those from survivors, giving further support for the growth–mortality hypothesis for the larval stage of this clupeid.     

Experimental evidence for negative turgor pressure in small leaf cells of Robinia pseudoacacia L versus large cells of Metasequoia glyptostroboides Hu et W.C. Cheng. 2. Höfler diagrams below the volume of zero turgor and the theoretical implication for pressure‐volume curves of living cells

The physiological advantages of negative turgor pressure, P_t, in leaf cells are water saving and homeostasis of reactants. This paper advances methods for detecting the occurrence of negative P_t in leaves. Biomechanical models of pressure‐volume (PV) curves predict that negative P_t does not change the linearity of PV curve plots of inverse balance pressure, P_B, versus relative water loss, but it does predict changes in either the y‐intercept or the x‐intercept of the plots depending on where cell collapse occurs in the P_B domain because of negative P_t. PV curve analysis of Robinia leaves revealed a shift in the x‐intercept (x‐axis is relative water loss) of PV curves, caused by negative P_t of palisade cells. The low x‐intercept of the PV curve was explained by the non‐collapse of palisade cells in Robinia in the P_B domain. Non‐collapse means that P_t smoothly falls from positive to negative values with decreasing cell volume without a dramatic change in slope. The magnitude of negative turgor in non‐collapsing living cells was as low as ?1.3 MPa and the relative volume of the non‐collapsing cell equaled 58% of the total leaf cell volume. This study adds to the growing evidence for negative P_t.     

Limited transferability of stream‐fish distribution models among river catchments: reasons and implications

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Untangling associations between chironomid taxa in Neotropical streams using local and landscape filters

1. Analyses of species association have major implications for selecting indicators for freshwater biomonitoring and conservation, because they allow for the elimination of redundant information and focus on taxa that can be easily handled and identified. These analyses are particularly relevant in the debate about using speciose groups (such as the Chironomidae) as indicators in the tropics, because they require difficult and time‐consuming analysis, and their responses to environmental gradients, including anthropogenic stressors, are poorly known. 2. Our objective was to show whether chironomid assemblages in Neotropical streams include clear associations of taxa and, if so, how well these associations could be explained by a set of models containing information from different spatial scales. For this, we formulated a priori models that allowed for the influence of local, landscape and spatial factors on chironomid taxon associations (CTA). These models represented biological hypotheses capable of explaining associations between chironomid taxa. For instance, CTA could be best explained by local variables (e.g. pH, conductivity and water temperature) or by processes acting at wider landscape scales (e.g. percentage of forest cover). 3. Biological data were taken from 61 streams in Southeastern Brazil, 47 of which were in well‐preserved regions, and 14 of which drained areas severely affected by anthropogenic activities. We adopted a model selection procedure using Akaike’s information criterion to determine the most parsimonious models for explaining CTA. 4. Applying Kendall’s coefficient of concordance, seven genera (Tanytarsus/Caladomyia, Ablabesmyia, Parametriocnemus, Pentaneura, Nanocladius, Polypedilum and Rheotanytarsus) were identified as associated taxa. The best‐supported model explained 42.6% of the total variance in the abundance of associated taxa. This model combined local and landscape environmental filters and spatial variables (which were derived from eigenfunction analysis). However, the model with local filters and spatial variables also had a good chance of being selected as the best model. 5. Standardised partial regression coefficients of local and landscape filters, including spatial variables, derived from model averaging allowed an estimation of which variables were best correlated with the abundance of associated taxa. In general, the abundance of the associated genera tended to be lower in streams characterised by a high percentage of forest cover (landscape scale), lower proportion of muddy substrata and high values of pH and conductivity (local scale). 6. Overall, our main result adds to the increasing number of studies that have indicated the importance of local and landscape variables, as well as the spatial relationships among sampling sites, for explaining aquatic insect community patterns in streams. Furthermore, our findings open new possibilities for the elimination of redundant data in the assessment of anthropogenic impacts on tropical streams.     

Nrf2‐Mediated Resistance to Oxidant‐Induced Redox Disruption in Embryos

Events that control developmental changes occur during specific windows of gestation and if disrupted, can lead to dysmorphogenesis or embryolethality. One largely understudied aspect of developmental control is redox regulation, where the untimely disruption of intracellular redox potentials (E_h) may alter development, suggesting that tight control of developmental‐stage–specific redox states is necessary to support normal development. In this study, mouse gestational day 8.5 embryos in whole embryo culture were treated with 10 μM dithiole‐3‐thione (D3T), an inducer of nuclear factor (erythroid‐derived 2)‐like 2 (Nrf2). After 14 hr, D3T‐treated and ‐untreated conceptuses were challenged with 200 μM hydrogen peroxide (H₂O₂) to induce oxidant‐induced change to intracellular E_hs. Redox potentials of glutathione (GSH), thioredoxin‐1 (Trx1), and mitochondrial thioredoxin‐2 (Trx2) were then measured over a 2‐hr rebounding period following H₂O₂ treatment. D3T treatment increased embryonic expression of known Nrf2‐regulated genes, including those responsible for redox regulation of major intracellular redox couples. Exposure to H₂O₂ without prior D3T treatment produced significant oxidation of GSH, Trx1, and Trx2, based on E_h values, where GSH and Trx2 E_h recovered, reaching to pre‐H₂O₂ E_h ranges, but Trx1 E_h remained oxidized. Following H₂O₂ addition in culture to embryos that received D3T pretreatments, GSH, Trx1, and Trx2 were insulated from significant oxidation. These data show that Nrf2 activation may serve as a means to protect the embryo from chemically induced oxidative stress through the preservation of intracellular redox states during development, allowing normal morphogenesis to ensue.     

Allozyme variation of seed embryos and mating system in relict populations of scots pine (<Emphasis Type="Italic">Pinus sylvestris</Emphasis> L.) from the Kremenets Hill Ridge and Maloe Poles’e

Allozyme variation at ten polymorphic loci and mating system was studied in three small isolated relict populations (4.4 to 22 ha) and in three artificial stands of Pinus sylvestris from the Kremenets Hill Ridge and Maloe Poles’e. It was established that the mean heterozygosity of 130 to 140 year-old trees from natural populations (H _O = 0.288; H _E = 0.277) was substantially lower, compared to 30 to 40 year-old trees from artificial stands (H _O = 0.358; H _E = 0.330). The observed heterozygosity of seed embryos (H _O = 0.169 and 0.180) was substantially lower than of the mature trees from populations and artificial stands, respectively. In the embryo samples, irrespectively of the forest stand origin, substantial hetedrozygote deficiency was observed (at six to eight loci), compared to the Hardy-Weinberg expectations. The proportion of cross pollination in the populations and artificial stands was low, t _m = 0.588 to 0.721; and t _m = 0.455 to 0.837, respectively.     

Analysis of the electrochemistry of hemes with Ems spanning 800 mV

The free energy of heme reduction in different proteins is found to vary over more than 18 kcal/mol. It is a challenge to determine how proteins manage to achieve this enormous range of E_ms with a single type of redox cofactor. Proteins containing 141 unique hemes of a‐, b‐, and c‐type, with bis‐His, His‐Met, and aquo‐His ligation were calculated using Multi‐Conformation Continuum Electrostatics (MCCE). The experimental E_ms range over 800 mV from ?350 mV in cytochrome c₃ to 450 mV in cytochrome c peroxidase (vs. SHE). The quantitative analysis of the factors that modulate heme electrochemistry includes the interactions of the heme with its ligands, the solvent, the protein backbone, and sidechains. MCCE calculated E_ms are in good agreement with measured values. Using no free parameters the slope of the line comparing calculated and experimental E_ms is 0.73 (R² = 0.90), showing the method accounts for 73% of the observed E_m range. Adding a +160 mV correction to the His‐Met c‐type hemes yields a slope of 0.97 (R² = 0.93). With the correction 65% of the hemes have an absolute error smaller than 60 mV and 92% are within 120 mV. The overview of heme proteins with known structures and E_ms shows both the lowest and highest potential hemes are c‐type, whereas the b‐type hemes are found in the middle E_m range. In solution, bis‐His ligation lowers the E_m by ≈205 mV relative to hemes with His‐Met ligands. The bis‐His, aquo‐His, and His‐Met ligated b‐type hemes all cluster about E_ms which are ≈200 mV more positive in protein than in water. In contrast, the low potential bis‐His c‐type hemes are shifted little from in solution, whereas the high potential His‐Met c‐type hemes are raised by ≈300 mV from solution. The analysis shows that no single type of interaction can be identified as the most important in setting heme electrochemistry in proteins. For example, the loss of solvation (reaction field) energy, which raises the E_m, has been suggested to be a major factor in tuning in situ E_ms. However, the calculated solvation energy vs. experimental E_m shows a slope of 0.2 and R² of 0.5 thus correlates weakly with E_ms. All other individual interactions show even less correlation with E_m. However the sum of these terms does reproduce the range of observed E_ms. Therefore, different proteins use different aspects of their structures to modulate the in situ heme electrochemistry. This study also shows that the calculated E_ms are relatively insensitive to different heme partial charges and to the protein dielectric constant used in the simulation. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

Comparing concentration‐based (AOT40) and stomatal uptake (PODY) metrics for ozone risk assessment to European forests

Tropospheric ozone (O₃) produces harmful effects to forests and crops, leading to a reduction of land carbon assimilation that, consequently, influences the land sink and the crop yield production. To assess the potential negative O₃ impacts to vegetation, the European Union uses the Accumulated Ozone over Threshold of 40 ppb (AOT40). This index has been chosen for its simplicity and flexibility in handling different ecosystems as well as for its linear relationships with yield or biomass loss. However, AOT40 does not give any information on the physiological O₃ uptake into the leaves since it does not include any environmental constraints to O₃ uptake through stomata. Therefore, an index based on stomatal O₃ uptake (i.e. PODY), which describes the amount of O₃ entering into the leaves, would be more appropriate. Specifically, the PODY metric considers the effects of multiple climatic factors, vegetation characteristics and local and phenological inputs rather than the only atmospheric O₃ concentration. For this reason, the use of PODY in the O₃ risk assessment for vegetation is becoming recommended. We compare different potential O₃ risk assessments based on two methodologies (i.e. AOT40 and stomatal O₃ uptake) using a framework of mesoscale models that produces hourly meteorological and O₃ data at high spatial resolution (12 km) over Europe for the time period 2000–2005. Results indicate a remarkable spatial and temporal inconsistency between the two indices, suggesting that a new definition of European legislative standard is needed in the near future. Besides, our risk assessment based on AOT40 shows a good consistency compared to both in‐situ data and other model‐based datasets. Conversely, risk assessment based on stomatal O₃ uptake shows different spatial patterns compared to other model‐based datasets. This strong inconsistency can be likely related to a different vegetation cover and its associated parameterizations.     

Transpiration rate relates to within‐ and across‐species variations in effective path length in a leaf water model of oxygen isotope enrichment

Stable oxygen isotope ratio of leaf water (δ¹⁸O_L) yields valuable information on many aspects of plant–environment interactions. However, current understanding of the mechanistic controls on δ¹⁸O_L does not provide complete characterization of effective path length (L) of the Péclet effect, – a key component of the leaf water model. In this study, we collected diurnal and seasonal series of leaf water enrichment and estimated L in six field‐grown angiosperm and gymnosperm tree species. Our results suggest a pivotal role of leaf transpiration rate (E) in driving both within‐ and across‐species variations in L. Our observation of the common presence of an inverse scaling of L with E in the different species therefore cautions against (1) the conventional treatment of L as a species‐specific constant in leaf water or cellulose isotope (δ¹⁸O_p) modelling; and (2) the use of δ¹⁸O_p as a proxy for g_s or E under low E conditions. Further, we show that incorporation of a multi‐species L‐E scaling into the leaf water model has the potential to both improve the prediction accuracy and simplify parameterization of the model when compared with the conventional approach. This has important implications for future modelling of oxygen isotope ratios.     

RATE OF O2 PRODUCTION DERIVED FROM PULSE‐AMPLITUDE‐MODULATED FLUORESCENCE: TESTING THREE BIOOPTICAL APPROACHES AGAINST MEASURED O2‐PRODUCTION RATE1

Light absorption by phytoplankton is both species specific and affected by photoacclimational status. To estimate oxygenic photosynthesis from pulse‐amplitude‐modulated (PAM) fluorescence, the amount of quanta absorbed by PSII needs to be quantified. We present here three different biooptical approaches to estimate the fraction of light absorbed by PSII: (1) the factor 0.5, which implies that absorbed light is equally distributed among PSI and PSII; (2) the fraction of chl a in PSII, determined as the ratio between the scaled red‐peak fluorescence excitation and the red absorption peak; and (3) the measure of light absorbed by PSII, determined from the scaling of the fluorescence excitation spectra to the absorption spectra by the “no‐overshoot” procedure. Three marine phytoplankton species were used as test organisms: Prorocentrum minimum (Pavill.) J. Schiller (Dinophyceae), Prymnesium parvum cf. patelliferum (J. C. Green, D. J. Hibberd et Pienaar) A. Larsen (Haptophyceae), and Phaeodactylum tricornutum Bohlin (Bacillariophyceae). Photosynthesis versus irradiance (P vs. E) parameters calculated using the three approaches were compared with P versus E parameters obtained from simultaneously measured rates of oxygen production. Generally, approach 1 underestimated, while approach 2 overestimated the gross O₂‐production rate calculated from PAM fluorescence. Approach 3, in principle the best approach to estimate quanta absorbed by PSII, was also superior according to observations. Hence, we recommend approach 3 for estimation of gross O₂‐production rates based on PAM fluorescence measurements.     

Use of meta‐analysis to predict degradation of carbaryl and malathion in freshwater for exposure assessment

Carbaryl (1‐naphthyl methylcarbamate) and malathion (diethyl mercaptosuccinate, S‐ester with O, O‐dimethyl phosphorodithioate) are insecticides used to control grasshopper infestations on rangeland. Insecticides used to control grasshopper infestations pose a hazard to aquatic organisms because although no‐spray buffer zones are observed around aquatic habitats, pesticide may be deposited by drift or mobilized from upland areas by runoff. A number of processes may affect the fate of carbaryl and malathion in the aquatic environment, but no method is available for estimating degradation over the range of conditions that occur in the field. We used results of published studies in meta‐analyses to estimate degradation models that predict half‐life of carbaryl and malathion in freshwater over temperature and pH ranges relevant to western grasshopper‐management programs. Estimated degradation models were:

In (half‐life carbaryl) = 24.3 ‐ 2.36(pH) ‐ 0.0788(t)

and In (half‐life malathion) = 5.98 + 2.84(pH) ‐ 0.326(pH ²) ‐ 0.202(t) + 0.00135(t ²)

where half‐life has units of hours, and temperature (t) has units °C. Both models accounted for a significant amount of total variation (P<0.0001) and had r²>0.97. Accuracy of these degradation models was evaluated by comparing predicted degradation of carbaryl and malathion to field and laboratory data. We suggest that use of these degradation models be restricted to conditions where water has 7 ≤. pH ≤. 10 for carbaryl, and 7 ≤ pH ≤ 8.2 for malathion.