The linkage of trait responses to stressor gradients has potential to expand biomonitoring approaches beyond traditional taxonomically based assessments that identify ecological effect to provide a causal diagnosis. Traits-based information may have several advantages over taxonomically based methods. These include providing mechanistic linkages of biotic responses to environmental conditions, consistent descriptors or metrics across broad spatial scales, more seasonal stability compared with taxonomic measures, and seamless integration of traits-based analysis into assessment programs. A traits-based biomonitoring approach does not require a new biomonitoring framework, because contemporary biomonitoring programs gather the basic site-by-species composition matrices required to link community data to the traits database. Impediments to the adoption of traits-based biomonitoring relate to the availability, consistency, and applicability of existing trait data. For example, traits generalizations among taxa across biogeographical regions are rare, and no consensus exists relative to the required taxonomic resolution and methodology for traits assessment. Similarly, we must determine if traits form suites that are related to particular stressor effects, and whether significant variation of traits occurs among allopatric populations. Finally, to realize the potential of traits-based approaches in biomonitoring, a concerted effort to standardize terminology is required, along with the establishment of protocols to ease the sharing and merging of broad, geographical trait information.
GenGIS is free and open source software designed to integrate biodiversity data with a digital map and information about geography and habitat. While originally developed with microbial community analyses and phylogeography in mind, GenGIS has been applied to a wide range of datasets. A key feature of GenGIS is the ability to test geographic axes that can correspond to routes of migration or gradients that influence community similarity. Here we introduce GenGIS version 2, which extends the linear gradient tests introduced in the first version to allow comprehensive testing of all possible linear geographic axes. GenGIS v2 also includes a new plugin framework that supports the development and use of graphically driven analysis packages: initial plugins include implementations of linear regression and the Mantel test, calculations of alpha-diversity (e.g., Shannon Index) for all samples, and geographic visualizations of dissimilarity matrices. We have also implemented a recently published method for biomonitoring reference condition analysis (RCA), which compares observed species richness and diversity to predicted values to determine whether a given site has been impacted. The newest version of GenGIS supports vector data in addition to raster files. We demonstrate the new features of GenGIS by performing a full gradient analysis of an Australian kangaroo apple data set, by using plugins and embedded statistical commands to analyze human microbiome sample data, and by applying RCA to a set of samples from Atlantic Canada. GenGIS release versions, tutorials and documentation are freely available at http://kiwi.cs.dal.ca/GenGIS, and source code is available at https://github.com/beiko-lab/gengis.
Widespread alteration of flow regimes requires guidelines for the protection of river ecosystems based on sound science. Preservation of the biodiversity within river ecosystems and sustaining natural ecological functions are key aspects of their management. However, the relationship between the biota and flow-related phenomena is poorly understood and, as a consequence, over-simplistic hydrologybased guidelines for river management have been adopted without establishing clear indicators of success. In the present paper, we aim to support the improvement of guidelines for flow (current velocity) management by developing a flow sensitivity index based on macroinvertebrates for Canadian rivers. Using benthic macroinvertebrate (BMI) samples collected by the Canadian Aquatic Biomonitoring Network (CABIN), current velocity preferences for the 55 most common invertebrate taxa across a range of reference and potential reference sites were derived. A Canadian Ecological Flow Index (CEFI) was developed based on these preferences. By testing the index against independent data, CEFI was found to respond mainly to changes in hydraulic conditions, and was minimally influenced by confounding factors (e.g. stream type, organic enrichment). The index was further validated using two independent data sets from the west and east of Canada, suggesting countrywide applicability of the method. In conclusion, we have developed a practical approach to evaluate relationships between hydrological regime and an important component of the river biota, permitting the development of an index which has good potential as an indicator for the effects of flow alteration. Moreover, we outline how the CEFI could be used as a tool for the development of holistic guidelines for the estimation of riverine flow needs.
Hydromorphological features are crucial in structuring habitats for freshwater organisms. The quantification of these variables is often performed through accurate measuring or detailed estimation, but their assessment is not always feasible for river management purposes. Economic and time constraints often lead to difficulty in creating simple summaries of collected data for practical use. The Lentic-lotic River Descriptor (LRD) was developed to identify the character of a river site in terms of local hydraulic conditions. Information about the presence of flow types, channel substrates, in-stream vegetation, organic debris and artificial features is included in its calculation. The main aim of this paper is to investigate whether the lentic-lotic character of a river site, as summarized with the LRD descriptor, is relevant to aquatic invertebrate communities in nearly natural river sites. Invertebrate data were collected with multi-habitat, proportional sampling and hydromorphological information was gained by applying the CARAVAGGIO method (river habitat survey technique) in the field. The dataset was generated from High or Good ecological status river sites located in Mediterranean areas of Italy. Correspondence Analysis was performed to relate the invertebrate community structure to a set of catchment-scale, reach-scale and chemical environmental variables. The results of the multivariate analysis indicate that LRD provides a persuasive explanation of the most important axis of variation in benthic data. This paper also presents the optimal LRD range for a set of invertebrate taxa, accompanied by a short discussion of their potential use in conservation issues.
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