Evaluating anthropogenic impacts on naturally stressed ecosystems: Revisiting river classifications and biomonitoring metrics along salinity gradients

Gutiérrez‐Cánovas, Cayetano; Arribas, Paula; Naselli-Flores, Luigi; Bennas, Nard; Finocchiaro, Marta; Millán, Andrés; Velasco, Josefa

doi:10.1016/j.scitotenv.2018.12.253

Cited by 20 publications

(19 citation statements)

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“…Recent studies applying advanced statistical approaches to understand the interactions between multiple stressor gradients on ecological outcomes in real‐world catchments (e.g., Feld et al, 2016; Gieswein et al, 2017; Villeneuve et al, 2018; Segurado et al, 2018; Gutiérrez‐Cánovas et al, 2019; Wu et al, 2019; Rankinen et al, 2019; Meissner et al, 2019) typically evaluated the hierarchy and compared the weight and effect size of individual stressors and stressor interactions (Segurado et al, 2018). As models are imperfect representation of reality based on limited observational data, different modeling approaches commonly result in different answers.…”

Section: Discussionmentioning

confidence: 99%

“…Such advanced statistical approaches are increasingly applied to regulatory monitoring data to understand the interactions between multiple stressor gradients on ecological outcomes in real‐world catchments (Feld et al, 2016; Gieswein et al, 2017; Segurado et al, 2018; Villeneuve et al, 2018; Gutiérrez‐Cánovas et al, 2019; Meissner et al, 2019; Rankinen et al, 2019; Wu et al, 2019). While a range of statistical approaches are available, here we present a combined approach (i) to understand the potential associations between catchment‐specific ecological responses and multiple stressors, while accounting for unmeasured sources of variability between locations, (ii) to derive overall relationships from available regulatory data that are generalizable to unmonitored locations, and (iii) to understand the importance of the absolute magnitude of individual stressors as well as the balances between them to maximize the complementary insights into these complex relationships based on low‐resolution regulatory data.…”

mentioning

confidence: 99%

“…The stressor–response relationship between diatoms, chemical stressors, soluble reactive P (SRP) loads, land cover, and catchment hydrological characteristics was examined using a novel combination of statistical modeling approaches, including random‐effects regression trees and compositional and ordinary mixed models, all considering the clustered nature of the data according to catchment. In addition to ordinary linear mixed models applied in previous ecological studies (Segurado et al, 2018; Gutiérrez‐Cánovas et al, 2019; Wu et al, 2019), we introduce novel compositional mixed models to understand the interplay and relative influence of water chemistry and land cover stressors on the ecological response through trade‐offs between them. Specifically, we address the following questions: (i) What is the association between P and diatom status in the context of multiple stressors in running waters?…”

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confidence: 99%

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Modeling the Ecological Impact of Phosphorus in Catchments with Multiple Environmental Stressors

et al. 2019

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The broken phosphorus (P) cycle has led to widespread eutrophication of freshwaters. Despite reductions in anthropogenic nutrient inputs that have led to improvement in the chemical status of running waters, corresponding improvements in their ecological status are often not observed. We tested a novel combination of complementary statistical modeling approaches, including random‐effect regression trees and compositional and ordinary linear mixed models, to examine the potential reasons for this disparity, using low‐frequency regulatory data available to catchment managers. A benthic Trophic Diatom Index (TDI) was linked to potential stressors, including nutrient concentrations, soluble reactive P (SRP) loads from different sources, land cover, and catchment hydrological characteristics. Modeling suggested that SRP, traditionally considered the bioavailable component, may not be the best indicator of ecological impacts of P, as shown by a stronger and spatially more variable negative relationship between total P (TP) concentrations and TDI. Nitrate‐N (p < 0.001) and TP (p = 0.002) also showed negative relationship with TDI in models where land cover was not included. Land cover had the strongest influence on the ecological response. The positive effect of seminatural land cover (p < 0.001) and negative effect of urban land cover (p = 0.030) may be related to differentiated bioavailability of P fractions in catchments with different characteristics (e.g., P loads from point vs. diffuse sources) as well as resilience factors such as hydro‐morphology and habitat condition, supporting the need for further research into factors affecting this stressor–response relationship in different catchment types. Advanced statistical modeling indicated that to achieve desired ecological status, future catchment‐specific mitigation should target P impacts alongside multiple stressors. Core Ideas Soluble reactive P (SRP) alone was not the best indicator of diatom response. Total P (TP) association with diatoms was more spatially variable than SRP. Nitrate‐N and TP have a combined negative effect on the ecological response. Seminatural land use had the most important influence on ecological response. We recommend catchment‐specific mitigation of multiple stressors.

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Section: Discussionmentioning

confidence: 99%

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Modeling the Ecological Impact of Phosphorus in Catchments with Multiple Environmental Stressors

et al. 2019

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“…These metrics underpin biomonitoring programmes that aim to halt and reverse biodiversity loss, to maintain and enhance the quality of ecosystems, and to assess the effectiveness of conservation and restoration measures, such as the Water Framework Directive (WFD; European Commission, ), the Convention on Biological Diversity (CBD, ) or the International Union for Conservation of Nature (IUCN, ). Problematically, few current metrics integrate the effects of natural disturbances, which can confound the assessment of anthropogenic impacts and thus lead to inappropriate management actions (Gutiérrez‐Cánovas et al, ; Pitacco et al, ; Tockner, Pusch, Borchard, & Lorang, ).…”

Section: Introductionmentioning

confidence: 99%

Natural disturbances can produce misleading bioassessment results: Identifying metrics to detect anthropogenic impacts in intermittent rivers

Soria

Gutiérrez‐Cánovas

Bonada

et al. 2019

Journal of Applied Ecology

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1. Ecosystems experience natural disturbances and anthropogenic impacts that affect biological communities and ecological processes. When natural disturbance modifies anthropogenic impacts, current widely used bioassessment metrics can prevent accurate assessment of biological quality.2. Our aim was to assess the ability of biomonitoring metrics to detect anthropogenic impacts at both perennial and intermittent sites, and in the latter including both flowing and disconnected pool aquatic phases. Specifically, aquatic macroinvertebrates from 20 rivers were sampled along gradients of natural flow intermittence (natural disturbance) and anthropogenic impacts to investigate their combined effects on widely used river biomonitoring metrics (i.e. taxonomic richness and standard biological indices) and novel functional metrics, including functional redundancy (i.e. the number of taxa contributing similarly to an ecosystem function, here a trophic function) and response diversity (i.e. how functionally similar taxa respond to natural disturbance and anthropogenic impacts). Only the widely used IBMWP index (Iberian Biological Monitoring Working Party)was able to detect anthropogenic impacts in intermittent rivers when used during flowing phases. Several functional metrics also detected anthropogenic impacts regardless of flow intermittence. Besides, functional redundancy of the entire community remained effective even in disconnected pools. Synthesis and applications.Our results show that natural flow intermittence can confound river bioassessment, and that a set of new functional metrics could be used as effective alternatives to standard metrics in naturally disturbed intermittent rivers. Our findings suggest that water managers should incorporate alternative functional metrics in the routine biomonitoring of naturally disturbed rivers. K E Y W O R D Sbioassessment, functional diversity, intermittent rivers, intermittent streams, macroinvertebrates, multiple stressors, natural stress, temporary rivers 284 | Journal of Applied Ecology SORIA et Al.

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“…Classical biomonitoring techniques (Table 1) have focused primarily on measures linked to various biodiversity metrics (e.g., species richness, beta diversity; Li et al, 2010;Gutiérrez-Cánovas et al, 2019) and indicator species (but see Vandewalle et al, 2010;Culhane et al, 2014;Saito et al, 2015 for other approaches). Nextgeneration biomonitoring (NGB) describes a suite of tools and approaches that allow the examination of a broader spectrum of organizational levels-from genes to entire ecosystems.…”

Section: Introductionmentioning

confidence: 99%

Key Questions for Next-Generation Biomonitoring

Makiola

Compson

Baird

et al. 2020

Front. Environ. Sci.

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Classical biomonitoring techniques have focused primarily on measures linked to various biodiversity metrics and indicator species. Next-generation biomonitoring (NGB) describes a suite of tools and approaches that allow the examination of a broader spectrum of organizational levels-from genes to entire ecosystems. Here, we frame 10 key questions that we envisage will drive the field of NGB over the next decade. While Makiola et al. Questions for Next-Generation Biomonitoring not exhaustive, this list covers most of the key challenges facing NGB, and provides the basis of the next steps for research and implementation in this field. These questions have been grouped into current-and outlook-related categories, corresponding to the organization of this paper.

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Evaluating anthropogenic impacts on naturally stressed ecosystems: Revisiting river classifications and biomonitoring metrics along salinity gradients

Cited by 20 publications

References 61 publications

Modeling the Ecological Impact of Phosphorus in Catchments with Multiple Environmental Stressors

Modeling the Ecological Impact of Phosphorus in Catchments with Multiple Environmental Stressors

Natural disturbances can produce misleading bioassessment results: Identifying metrics to detect anthropogenic impacts in intermittent rivers

Key Questions for Next-Generation Biomonitoring

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