Predicting reference assemblages for freshwater bioassessment with limiting environmental difference analysis

Chessman, Bruce C.

doi:10.1086/678701

Cited by 4 publications

(5 citation statements)

References 36 publications

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“…This type of classification is a prerequisite for assessing whether human activity has altered ecosystems, because assemblages can exhibit marked natural variability (Gibson et al 1996). Some bioassessment methods do not depend on a classification approach but instead model how biota naturally vary across continuous environmental gradients (e.g., Hawkins et al 2010, Bailey et al 2014, Chessman 2014, Reynoldson et al 2014). However, landscape and river type classifications are still being tested in different regions.…”

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confidence: 99%

Correspondence between stream benthic macroinvertebrate assemblages and ecoregions in northwestern Argentina

et al. 2019

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The use of ecoregions to classify stream and river environments has been extensively tested in North America and Europe, but few such studies have been conducted in South America. In this study we tested whether taxonomic richness, composition, and organism abundance within benthic macroinvertebrate assemblages were associated with ecoregions in northwestern Argentina at the genus and family levels. We included 3 ecoregions and their respective subecoregions in this study: the Yungas subtropical cloud forest, the Western Chaco subtropical dry forest, and the Monte xeric shrublands. We used nonmetric multidimensional scaling, analysis of similarity, and rank-abundance curves to assess how assemblages varied among ecoregions and subecoregions. We used principal components analysis to describe how environmental factors varied among sites and regions. Most aspects of invertebrate assemblages were associated with both ecoregions and subecoregions. The structure of the macroinvertebrate assemblages was generally concordant with ecoregional classification at the genus level, although concordance was not evident at the subecoregion level of resolution, especially for family-level data. The segregation of assemblages was most strongly related to environmental variables associated with topography and less strongly related to physiochemical variables. Our results confirm that ecoregions may effectively predict the invertebrate biota inhabiting streams in northwestern Argentina, but it was difficult to delineate discrete assemblages. Future work should assess the effectiveness of modeling approaches that would better account for the gradual changes in assemblage composition that occur along environmental gradients and test how well both classification and modeling approaches partition biotic variation in other parts of South America.

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confidence: 99%

Correspondence between stream benthic macroinvertebrate assemblages and ecoregions in northwestern Argentina

et al. 2019

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“…Many of these environmental predictors are subject to anthropogenic alteration, for example, alkalinity, discharge, stream depth and width, substratum composition and vegetation. The values of such predictors input to the AUSRIVAS models are the measured values, not the values that would occur in the absence of human influence, and this practice is likely to cause model predictions to deviate from natural expectations (Clarke et al 1996;Hargett et al 2007;Chessman 2014). For example, faunal predictions for an assessment site with unnaturally high alkalinity as a result of anthropogenic salinisation may be derived from reference sites with naturally high alkalinity, whereas reference sites with naturally low alkalinity would have been the appropriate comparison (Metzeling et al 2006;Schäfer et al 2011).…”

Section: Variable Reference-site Statusmentioning

confidence: 99%

What’s wrong with the Australian River Assessment System (AUSRIVAS)?

Chessman¹

2021

Mar. Freshwater Res.

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The Australian River Assessment System (AUSRIVAS or AusRivAS) is a national biomonitoring scheme that supposedly assesses the 'biological health' of rivers. AUSRIVAS outputs observed-over-expected (O/E) indices derived from macroinvertebrate survey data obtained both at a site to be assessed and at designated reference sites. However, AUSRIVAS reference sites lack any consistent or quantified status, and, therefore, AUSRIVAS O/E indices have no particular meaning. Moreover, many studies have found AUSRIVAS O/E to be a weak or inconsistent indicator of exposure to anthropogenic or human-influenced stressors. Poor performance by AUSRIVAS may relate to numerous factors including the following: (1) variable reference-site status, (2) inappropriate model predictors, (3) limitations of O/E indices, (4) inconstant sampling methods, and (5) neglect of non-seasonal temporal variability. The indices Ephemeroptera-Plecoptera-Trichoptera (EPT) and stream invertebrate grade number-average level (SIGNAL) provide alternatives that have often outperformed AUSRIVAS O/E in comparative tests. In addition, bioassessment of Australian rivers might be advanced by the development of diagnostic methods to identify the stressors causing ecological impact rather than merely to infer impact intensity and assign quality ratings to assessment sites.

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“…That is, we assumed that the impacts of stressors included in the model, such as urbanization, require long-term extensive mitigation planning, whereas stressors associated with deviations from model predictions can be mitigated in the short-term by applying focused actions. These assumptions are not unique to our model and have been used in other applications that have evaluated biological potential (Paul et al 2008, Chessman 2014, Waite et al 2014). However, many stressors excluded from the model can have long-lasting impacts, leading to management scenarios where long-term recovery may only be possible with sustained and costly application of resources.…”

Section: Model Assumptions and Limitationsmentioning

confidence: 99%

“…many biological indices provides a broad context for interpreting observed biological condition relative to that occurring in unaltered habitats for a particular region (Reynoldson et al 1997, Stoddard et al 2006). However, achieving a reference condition of biological integrity (i.e., having structure and function comparable to natural habitat for the same region; Karr et al 1986) may be challenging if landscape conditions (e.g., watershed imperviousness) limit the spatial and temporal scales that can be effectively managed (Chessman andRoyal 2004, Chessman 2014). Resource management decisions could be improved if information is available that describes these limitations.…”

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confidence: 99%

“…A predictive model of bioassessment scores that is based on landscape metrics (e.g., imperviousness) could identify likely constraints on biological integrity, particularly for factors that are difficult to manage and are often associated with instream stressors. Analysis methods that characterize biotic and abiotic factors that limit assemblage composition have been explored by others (i.e., limiting factor theory; Chessman et al 2008, Chessman 2014). Similar concepts have been applied in a landscape context to describe variation in biological communities and metrics at different spatial scales (Waite 2013, Waite et al 2014), although they have not been developed to identify constraints as defined above.…”

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confidence: 99%

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Prioritizing management goals for stream biological integrity within the developed landscape context

et al. 2019

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Stream management goals for biological integrity may be difficult to achieve in developed landscapes where channel modification and other factors constrain in-stream conditions. To evaluate potential constraints on biological integrity, we developed a statewide landscape model for California that estimates ranges of likely scores for a macroinvertebrate-based index that are typical at a site with the observed level of landscape alteration. This context can support prioritization decisions for stream management, like identifying reaches for restoration or enhanced protection based on how observed scores relate to model predictions. Median scores were accurately predicted by the model for all sites in California with bioassessment data (Pearson correlation r 5 0.75 between observed and predicted for calibration data, r 5 0.72 for validation). The model also predicted that 15% of streams statewide are constrained for biological integrity within their present developed landscape, particularly for urban and agricultural areas in the South Coast, Central Valley, and Bay Area regions. We worked with a local stakeholder group from the San Gabriel River watershed (Los Angeles County, California) to evaluate how the statewide model could support local management decisions. To achieve this purpose, we created an interactive application, the Stream Classification and Priority Explorer, that compares observed scores with predictions from the landscape model to assign priorities. We observed model predictions consistent with the land-use gradient from the upper to lower watershed, where potential limits to achieving biological integrity were more common in the heavilyurbanized lower watershed. However, most of the sites in the lower watershed scored within their predicted ranges, and were therefore given a low priority for restoration. In contrast, 2 low-scoring sites in the undeveloped upper watershed were prioritized for causal assessment and possible future restoration, whereas 3 high-scoring sites were prioritized for protection. The availability of geospatial and bioassessment data at the national level suggests that these tools can easily be applied to inform management decisions at other locations where altered landscapes may limit biological integrity.

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Predicting reference assemblages for freshwater bioassessment with limiting environmental difference analysis

Cited by 4 publications

References 36 publications

Correspondence between stream benthic macroinvertebrate assemblages and ecoregions in northwestern Argentina

Correspondence between stream benthic macroinvertebrate assemblages and ecoregions in northwestern Argentina

What’s wrong with the Australian River Assessment System (AUSRIVAS)?

Prioritizing management goals for stream biological integrity within the developed landscape context

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