Influence of human pressures on large river structure and function

A large river study was conducted as part of the Cross Departmental Research Pool (CDRP) ecological integrity project to (i) provide an overview of the macroinvertebrate faunas of large rivers, including those in deep-water habitats, and (ii) to elucidate links between these faunas, river function and anthropogenic stressors. Eleven sites on 6th-order or 7th-order rivers were sampled; four in the South Island and seven in the North Island. We measured (i) macroinvertebrate communities colonising wood, riffles (where present), littoral habitats (1.5 m deep) (ii) ecosystem metabolism using a single-station open-channel approach based on natural changes in dissolved oxygen concentration over a 24-hour period, and (iii) wood and cellulose breakdown. Relationships were investigated between these response variables and reach-scale assessments of habitat quality, underlying upstream and segment environmental variables provided in the Freshwater Environments of New Zealand (FWENZ) database, and anthropogenic pressure variables provided by the Waters of National Importance (WONI) database

Measures of nutrient processes as indicators of stream ecosystem health

To better understand how freshwater ecosystems respond to changes in catchment land-use, it is important to develop measures of ecological health that include aspects of both ecosystem structure and function. This study investigated measures of nutrient processes as potential indicators of stream ecosystem health across a land-use gradient from relatively undisturbed to highly modified. A total of seven indicators (potential denitrification; an index of denitrification potential relative to sediment organic matter; benthic algal growth on artificial substrates amended with (a) N only, (b) P only, and (c) N and P; and delta N-15 of aquatic plants and benthic sediment) were measured at 53 streams in southeast Queensland, Australia. The indicators were evaluated by their response to a defined gradient of agricultural land-use disturbance as well as practical aspects of using the indicators as part of a monitoring program. Regression models based on descriptors of the disturbance gradient explained a large proportion of the variation in six of the seven indicators. Denitrification index, algal growth in N amended substrate, and delta N-15 of aquatic plants demonstrated the best regression. However, the delta N-15 value of benthic sediment was found to be the best indicator overall for incorporation into a monitoring program, as samples were relatively easy to collect and process, and were successfully collected at more than 90% of the study sites

How good are Bayesian belief networks for environmental management? A test with data from an agricultural river catchment

1. The ecological health of rivers worldwide continues to decline despite increasing effort and investment in river science and management. Bayesian belief networks (BBNs) are increasingly being used as a mechanism for decision-making in river management because they provide a simple visual framework to explore different management scenarios for the multiple stressors that impact rivers. However, most applications of BBN modelling to resource management use expert knowledge and/or limited real data, and fail to accurately assess the ability of the model to make predictions. 2. We developed a BBN to model ecological condition in a New Zealand river using field/GIS data (from multiple rivers), rather than expert opinion, and assessed its predictive ability on an independent dataset. The developed BBN performed moderately better than a number of other modelling techniques (e.g., artificial neural networks, classification trees, random forest, logistic regression), although model construction was more time3consuming. Thus the predictive ability of BBNs is (in this case at least) on a par with other modelling methods but the approach is distinctly better for its ability to visually present the data linkages, issues and potential outcomes of management options in real time. 3. The BBN suggested management of habitat quality, su ch as riparian planting, along with the current management focus on limiting nutrient leaching from agricultural land may be most effective in improving ecological condition. 4. BBNs can be a powerful and accurate method of effectively portraying the multiple interacting drivers of environmental condition in an easily understood manner. However, most BBN applications fail to appropriately test the model fit prior to use. We believe this lack of testing may seriously undermine their long-term effectiveness in resource management, and recommend that BBNs should be used in conjunction with some measure of uncertainty about model predictions. We have demonstrated this for a BBN of ecological condition in a New Zealand river, shown that model fit is better than that for other modelling techniques, and that improving habitat would be equally effective to reducing nutrients to improve ecological condition

Habitat-specific benthic metabolism in a Mediterranean-type intermittent stream

A modified flow-through chamber method was used to measure gross primary production (GPP), net primary production (NPP), community respiration (CR) and associated environmental variables in an intermittent Mediterranean-type stream in Southern Portugal. Three common types of in stream habitats were targeted: cobble (C), cobble covered with filamentous algae (C+A) and leaf litter (LL). NPP, GPP and CR differed significantly among all three habitats. GPP increased with chlorophyll a and, less strongly, with photosynthetic active radiation and, therefore, was highest in C+A habitat. The highest CR was in LL and its variation was best determined by ash-free dry mass (AFDM) of plant litter. Higher respiration in LL was related to heterotrophic activity and, to a lesser extent, to autotrophic respiration associated with periphyton. We observed a decrease of production efficiency of primary producers with AFDM in C+A and C habitats. Our results demonstrate that each habitat type should be considered as a discrete metabolic entity and that particular sets of environmental factors are responsible for habitat specific metabolic responses. Scaling up measurements from discrete habitat patches to the entire reach or stream should not be done by extrapolating the results of a single habitat type and will require quantification of habitat coverage, at the appropriate scale

A Statistical Model for Estimating Maternal-Zygotic Interactions and Parent-of-Origin Effects of QTLs for Seed Development

Proper development of a seed requires coordinated exchanges of signals among the three components that develop side by side in the seed. One of these is the maternal integument that encloses the other two zygotic components, i.e., the diploid embryo and its nurturing annex, the triploid endosperm. Although the formation of the embryo and endosperm contains the contributions of both maternal and paternal parents, maternally and paternally derived alleles may be expressed differently, leading to a so-called parent-of-origin or imprinting effect. Currently, the nature of how genes from the maternal and zygotic genomes interact to affect seed development remains largely unknown. Here, we present a novel statistical model for estimating the main and interaction effects of quantitative trait loci (QTLs) that are derived from different genomes and further testing the imprinting effects of these QTLs on seed development. The experimental design used is based on reciprocal backcrosses toward both parents, so that the inheritance of parent-specific alleles could be traced. The computing model and algorithm were implemented with the maximum likelihood approach. The new strategy presented was applied to study the mode of inheritance for QTLs that control endoreduplication traits in maize endosperm. Monte Carlo simulation studies were performed to investigate the statistical properties of the new model with the data simulated under different imprinting degrees. The false positive rate of imprinting QTL discovery by the model was examined by analyzing the simulated data that contain no imprinting QTL. The reciprocal design and a series of analytical and testing strategies proposed provide a standard procedure for genomic mapping of QTLs involved in the genetic control of complex seed development traits in flowering plants

Global patterns and drivers of ecosystem functioning in rivers and riparian zones

River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth's biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented "next-generation biomonitoring" by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.peerReviewe

Towards a simple global-standard bioassay for a key ecosystem process: organic-matter decomposition using cotton strips

Cotton-strip bioassays are increasingly used to assess ecosystem integrity because they provide a standardized measure of organic-matter decomposition – a fundamental ecosystem process. However, several different cotton- strip assays are routinely used, complicating the interpretation of results across studies, and hindering broader synthesis. Here, we compare the decay rates and assemblages of bacteria and fungi colonizing the three most commonly used cotton materials: Artist’s canvas, Calico cloth, and Empa fabric. Cotton strips from each material type were incubated in 10 streams that span a wide range of physicochemical properties across five ecoregions. Additionally, to evaluate responses to environmental stress without potentially confounding biogeographical effects, we deployed identical bioassays in five streams across an acidification gradient within a single ecoregion. Across all streams decomposition rates (as tensile strength loss [TSL]) differed among the three cotton ma- terials; Calico cloth decomposed fastest (time to 50% TSL [T50]=16.7d), followed by the Empa fabric (T50 = 18.3 d) and then Artist’s canvas (T50 = 21.4 d). Despite these differences, rates of TSL of the three cotton materials responded consistently to variation in environmental conditions; TSL of each fabric increased with stream temperature, dissolved-nutrient concentrations and acid-neutralizing capacity, although Artist’s canvas and Calico cloth were more sensitive than Empa fabric. Microbial communities were similar among the mate- rials, and values of community structure (e.g., phylotype richness and diversity) were comparable to those reported for decaying leaves in streams from the same region, the major natural basal carbon resource in forested-stream ecosystems. We present linear calibrations among pairs of assays so that past and future studies can be expressed in a “common currency” (e.g., Artist’s-fabric equivalents) ‘past and future studies’ repeated two times in the sentence. Lastly, given its relatively low within-site variability, and the large number of streams where it has been used (> 700 across the globe), we recommend Artist’s fabric for future work. These results show that cotton provides an effective and realistic standardized substrate for studying heterotrophic microbial assemblages, and acts as a reasonable proxy for more chemically complex forms of detritus. These findings add to growing evidence that cotton-strip bioassays are simple, effective and easily standardized indicators of het- erotrophic microbial activity and the ecosystem processes that result