A sediment-specific family-level biomonitoring tool to identify the impacts of fine sediment in temperate rivers and streams

AbstractAnthropogenic modifications of sediment load can cause ecological degradation in stream and river ecosystems. However, in practice, identifying when and where sediment is the primary cause of ecological degradation is a challenging task. Biological communities undergo natural cycles and variation over time, and respond to a range of physical, chemical and biological pressures. Furthermore, fine sediments are commonly associated with numerous other pressures that are likely to influence aquatic biota. The use of conventional, non-biological monitoring to attribute cause and effect would necessitate measurement of multiple parameters, at sufficient temporal resolution, and for a significant period of time. Biomonitoring tools, which use low-frequency measurements of biota to gauge and track changes in the environment, can provide a valuable alternative means to detecting the effects of a given pressure. In this study, we develop and test an improved macroinvertebrate, family-level and mixed-level biomonitoring tool for fine sediment. Biologically-based classifications of sediment sensitivity were supplemented by using empirical data of macroinvertebrate abundance and percentage fine sediment, collected across a wide range of temperate river and stream ecosystems (model training dataset n=2252) to assign detailed individual sensitivity weights to taxa. An optimum set of weights were identified by non-linear optimisation, as those that resulted in the highest Spearman’s rank correlation coefficient between the index (called the Empirically-weighted Proportion of Sediment-sensitive Invertebrates index; E-PSI) scores and deposited fine sediment in the model training dataset. The family and mixed-level tools performed similarly, with correlations with percentage fine sediment in the test dataset (n=84) of rs=−0.72 and rs=−0.70 p<0.01. Testing of the best performing family level version, over agriculturally impacted sites (n=754) showed similar correlations to fine sediment (rs=−0.68 p<0.01). The tools developed in this study have retained their biological basis, are easily integrated into contemporary monitoring agency protocols and can be applied retrospectively to historic datasets. Given the challenges of non-biological conventional monitoring of fine sediments and determining the biological relevance of the resulting data, a sediment-specific biomonitoring approach is highly desirable and will be a useful addition to the suite of pressure-specific biomonitoring tools currently used to infer the causes of ecological degradation

Disentangling responses to natural stressor and human impact gradients in river ecosystems across Europe

1. Rivers are dynamic ecosystems in which both human impacts and climate-driven drying events are increasingly common. These anthropogenic and natural stressors interact to influence the biodiversity and functioning of river ecosystems. Disentangling ecological responses to these interacting stressors is necessary to guide management actions that support ecosystems adapting to global change. 2. We analysed the independent and interactive effects of human impacts and natural drying on aquatic invertebrate communities—a key biotic group used to assess the health of European freshwaters. We calculated biological response metrics representing communities from 406 rivers in eight European countries: taxonomic richness, functional richness and redundancy, and biomonitoring indices that indicate ecological status. We analysed metrics based on the whole community and on a group of taxa with traits promoting resistance and/or resilience (‘high RR’) to drying. We also examined how responses vary across Europe in relation to climatic aridity. 3. Most community metrics decreased independently in response to impacts and drying. A richness-independent biomonitoring index (the average score per taxon; ASPT) showed particular potential for use in biomonitoring, and should be considered alongside new metrics representing high RR diversity, to promote accurate assessment of ecological status. 4. High RR taxonomic richness responded only to impacts, not drying. However, these predictors explained little variance in richness and other high RR metrics, potentially due to low taxonomic richness. Metric responsiveness could thus be enhanced by developing region-specific high RR groups comprising sufficient taxa with sufficiently variable impact sensitivities to indicate ecological status. 5. Synthesis and applications. Metrics are needed to assess the ecological status of dynamic river ecosystems—including those that sometimes dry—and thus to identify priority sites requiring action to tackle the causes of environmental degradation. Our results inform recommendations guiding the development of such metrics. We propose concurrent use of richness-independent ‘average score per taxon’ indices and metrics that characterize the richness of resistant and resilient taxa. We observed interactions between aridity, impacts and drying, highlighting that these new metrics should be region specific, river type specific and adaptable, promoting their ability to inform management actions that protect biodiversity in river ecosystems responding to climate change.European Cooperation in Science and Technology. Grant Number: CA1511