Predicting potential ecological effects of flow alterations using quantitative flow preferences of stream macroinvertebrates

The river flow regime is one of the key parameters in river ecosystems as it controls physical habitat conditions, biological and ecological processes and river ecosystem functioning. River flow conditions have been substantially altered globally due to water regulation and climatic changes resulting in detrimental impacts on the functioning and health of river ecosystems. Given its importance, several investigations have been conducted to increase the knowledge and improve the understanding of ecological effects of flow alterations. Species of stream macroinvertebrates are a major organism group in river ecosystems that are highly sensitive to environmental changes. Current knowledge regarding the flow preferences of stream macroinvertebrates is mostly based on species’ qualitative ecological traits stemming from expert knowledge or literature analyses. These established qualitative data are difficult to be linked to e.g. quantitative discharge data that could be used in predictive modelling of species diversity in space and over time. This research deficit, make it difficult to quantitatively predict the effects of climate-induced flow changes on river biota. To fill this research gap, it is crucial to better understand the quantitative changes in e.g. species’ abundance to environmental stressors such as flow alterations. Empirically-driven predictive relationships might be established for individual species by linking their abundance along wide ranges of environmental gradients to any environmental variables, e.g. different flow conditions. Any changes in flow can be described by indicators of hydrologic alterations (IHA metrics) that provide information on duration, frequency, magnitude, rate and timing of flow events. These predictive relationships can be used to assess species responses to climate-change-induced flow alterations. In this thesis, potential changes in the abundance of stream macroinvertebrates due to the effects from climate-change-induced flow alterations are analysed. The thesis is divided into three parts: Firstly, a non-linear modelling approach is applied for a German-wide dataset which enabled to link the abundance of species to river flow to quantify flow preferences of stream macroinvertebrates along the range of a variety of flow conditions, i.e. various IHA metrics. Secondly, this approach is used in two contrasting river catchments in the lowland and lower mountainous region of Germany to quantitatively assess potential changes in species’ abundance due to projected changes in flow conditions under the climate scenario RCP 8.5. Thirdly, potential variability in projected abundance of individual species under 16 climate models derived from various combinations of global and regional climate models are examined. The effects of variability in climate model predictions on species’ abundance and functional trait composition are tested. Based on these results, the ecological effects of changes in species’ abundance of sampling sites are assessed. The response relationships derived from the German-wide dataset showed that on average one-third (18-40% of 120 taxa depending on the IHA metric) of stream macroinvertebrates can be considered as ubiquitous with a broad hydrological tolerance, while about two-thirds of the taxa (35-53% of 120 taxa depending on the IHA metric) respond to either specific ranges of flow conditions with detectable optima for their occurrence or show monotone increasing/decreasing trends (23-41% of 120 taxa depending on the IHA metric). The habitat suitability for the taxa that showed preferences to specific ranges of flow conditions may be potentially affected by climate-change-induced flow alterations. The results from the catchment-scale study revealed that climate change would most strongly affect the low-flow conditions, which can lead to decreasing abundance of individual species as far as 42%. However, due to strong increasing abundance of generalist taxa, the average response of all species over all metrics indicated increasing overall species assemblage abundance in 98% of the studied river reaches. The predictions of climate models showed more increasing trends in flow conditions within the lowland area (11 of 16 climate models) compared to the lower mountainous region (6 of 16 climate models). Furthermore, the predicted species’ abundance differed significantly depending on the climate model used, especially in the lower mountainous region. This high variability lead to less significant changes in the overall abundance of species and functional groups in the lower mountainous region compared to the lowland area. The projected changes in species’ abundance showed more significant ecological alterations in the lower mountainous region compared to the lowlands. We argue that the causes lie, on the one hand, with stronger climate-change impacts on rivers with higher flows, which leads to homogenisation of physical habitat conditions. On the other hand, it is due to the higher number of specialists in the lower mountainous region (26 of 134 species) compared to the lowland area (5 of 60 species). The results provide empirical evidence that the functional trait compositions will be affected by flow alterations, but the effects would be regionally different. For example, flow alterations lead to increasing abundance of rheophilic and tolerant rhithral species in the lowland area, which is referred to as “rhithralisation effect”. The rather large number of stream macroinvertebrates with clear flow preferences in both the German-wide (35-53% of 120 taxa depending on the IHA metric, Chapter 2) and the catchment-scale studies (75-91% of 134 taxa in the lower mountainous region, and 85-98% of 60 taxa in the lowland area depending on the IHA metric, Chapter 3 and 4) reveal the potentially strong influence of climate-change-induced flow alterations on these species. However, among a variety of causes such as inherent uncertainties in ecological models induced by e.g. data availability, the ability to predict these changes is also limited by the uncertainty in predicting climate change itself. These results go one step further than the qualitative assessment of species responses to environmental changes and support the current knowledge that flow alterations and their effects on species’ abundance might be a global phenomenon. The main findings of this thesis underline the high susceptibility of stream macroinvertebrates to ongoing climate-change-induced flow alterations. Concerning the methodology, a clear recommendation for future predictions is to reduce uncertainty inherent in climate change models and thus to improve future predictability of e.g. species’ abundance. The analyses applied in this thesis are applicable to forecast climate change impacts at different spatial and temporal scales as well as for different stressors or species

Variation in the predictability of lake plankton metric types

Statistical and climate models are frequently used for biodiversity projections under future climatic changes, but their predictive capacity for freshwater plankton may vary among different species and community metrics. Here, we used random forests to model plankton species and community metrics as a function of biological, climatic, physical, and chemical data from long-term (2000–2017) monitoring data collected from Lake Müggelsee Berlin, Germany. We (1) compared the predictability of well-known lake plankton metric types (biomass, abundance, taxonomic diversity, Shannon diversity, Simpson diversity, evenness, taxonomic distinctness, and taxonomic richness) and (2) assessed how the relative influence of different environmental drivers varies across lake plankton metric models. Overall, the metric predictability was highest for biomass and abundance followed by taxonomic richness. The biomass of dominant phytoplankton taxonomic groups such as cyanobacteria (adjusted-R2 = 0.53) and the abundance of dominant zooplankton taxonomic groups such as rotifers (adjusted-R2 = 0.59) and daphnids (adjusted-R2 = 0.51) were more predictable than other metric types. The plankton metric predictability increased when grouping phytoplankton species according to their functional traits (adjusted-R2 = 0.37 ± 0.14, mean ± SD, n = 36 functional groups) compared to higher taxonomic units (adjusted-R2 = 0.25 ± 0.15, n = 22 taxonomic groups). Light, nutrients, water temperature, and seasonality for phytoplankton and food resources for zooplankton were the main drivers of both taxonomic and functional groups, giving confidence that our models captured the expected major environmental drivers. Our quantitative analyses highlight the multidimensionality of lake planktonic responses to environmental drivers and have implications for our capacity to select appropriate metrics for forecasting the future of lake ecosystems under global change scenarios

When is a hydrological model sufficiently calibrated to depict flow preferences of riverine species?

Riverine species have adapted to their environment, particularly to the hydrological regime. Hydrological models and the knowledge of species preferences are used to predict the impact of hydrological changes on species. Inevitably, hydrological model performance impacts how species are simulated. From the example of macroinvertebrates in a lowland and a mountainous catchment, we investigate the impact of hydrological model performance and the choice of the objective function based on a set of 36 performance metrics for predicting species occurrences. Besides species abundance, we use the simulated community structure for an ecological assessment as applied for the Water Framework Directive. We investigate when a hydrological model is sufficiently calibrated to depict species abundance. For this, we postulate that performance is not sufficient when ecological assessments based on the simulated hydrology are significantly different (analysis of variance, p < .05) from the ecological assessments based on observations. The investigated range of hydrological model performance leads to considerable variability in species abundance in the two catchments. In the mountainous catchment, links between objective functions and the ecological assessment reveal a stronger dependency of the species on the discharge regime. In the lowland catchment, multiple stressors seem to mask the dependence of the species on discharge. The most suitable objective functions to calibrate the model for species assessments are the ones that incorporate hydrological indicators used for the species prediction

Climate model variability leads to uncertain predictions of the future abundance of stream macroinvertebrates

Climate change has the potential to alter the flow regimes of rivers and consequently affect the taxonomic and functional diversity of freshwater organisms. We modeled future flow regimes for the 2050 and 2090 time horizons and tested how flow regimes impact the abundance of 150 macroinvertebrate species and their functional trait compositions in one lowland river catchment (Treene) and one mountainous river catchment (Kinzig) in Europe. We used all 16 global circulation models (GCMs) and regional climate models (RCMs) of the CORDEX dataset under the RCP 8.5 scenario to calculate future river flows. The high variability in relative change of flow among the 16 climate models cascaded into the ecological models and resulted in substantially different predicted abundance values for single species. This variability also cascades into any subsequent analysis of taxonomic or functional freshwater biodiversity. Our results showed that flow alteration effects are different depending on the catchment and the underlying species pool. Documenting such uncertainties provides a basis for the further assessment of potential climate-change impacts on freshwater taxa distributions

A high-resolution streamflow and hydrological metrics dataset for ecological modeling using a regression model

Hydrological variables are among the most influential when analyzing or modeling stream ecosystems. However, available hydrological data are often limited in their spatiotemporal scale and resolution for use in ecological applications such as predictive modeling of species distributions. To overcome this limitation, a regression model was applied to a 1 km gridded stream network of Germany to obtain estimated daily stream flow data (m3 s−1) spanning 64 years (1950–2013). The data are used as input to calculate hydrological indices characterizing stream flow regimes. Both temporal and spatial validations were performed. In addition, GLMs using both the calculated and observed hydrological indices were compared, suggesting that the predicted flow data are adequate for use in predictive ecological models. Accordingly, we provide estimated stream flow as well as a set of 53 hydrological metrics at 1 km grid for the stream network of Germany. In addition, we provide an R script where the presented methodology is implemented, that uses globally available data and can be directly applied to any other geographical region

Quantitative hydrological preferences of benthic stream invertebrates in Germany

Current knowledge regarding the flow preferences of benthic stream invertebrates is mostly based on qualitative data or expert knowledge and literature analysis. These established flow preferences are difficult to use in predictions of the effects of global change on aquatic biota. To complement the existing categories, we performed a large-scale analysis on the distribution of stream invertebrates at stream monitoring sites in order to determine their responses to various hydrological conditions. We used 325 invertebrate surveys from environmental agencies at 238 sites paired to 217 gauges across Germany covering a broad range of hydrological conditions. Based on these data, we modelled the respective probabilities of occurrences for 120 benthic invertebrate taxa within this hydrological range using hierarchical logistic regression models. Our analyses revealed that more than one-third of the taxa (18–40%) can be considered as ubiquitous and having a broad hydrological tolerance. Furthermore, 22–41% of the taxa responded to specific ranges of flow conditions with detectable optima. “Duration high flow event” represented the flow parameter that correlated best with the abundance of individual taxa, followed by “rate of change average event”, with 41 and 38% of the taxa showing a peak in their probability of occurrence at specific ranges of these metrics, respectively. The habitat suitability for these taxa may be potentially affected by global change-induced hydrological changes. Quantified hydrological traits of individual taxa might therefore support stream management and enable the prediction of taxa responses to flow alteration. The hydrological traits of stream benthic invertebrates may be used in forecasting studies in central Europe, and the methods used in this study are suitable for application in other regions with different flow regimes

Variation in the predictability of lake plankton metric types

Statistical and climate models are frequently used for biodiversity projections under future climatic changes, but their predictive capacity for freshwater plankton may vary among different species and community metrics. Here, we used random forests to model plankton species and community metrics as a function of biological, climatic, physical, and chemical data from long‐term (2000–2017) monitoring data collected from Lake Müggelsee Berlin, Germany. We (1) compared the predictability of well‐known lake plankton metric types (biomass, abundance, taxonomic diversity, Shannon diversity, Simpson diversity, evenness, taxonomic distinctness, and taxonomic richness) and (2) assessed how the relative influence of different environmental drivers varies across lake plankton metric models. Overall, the metric predictability was highest for biomass and abundance followed by taxonomic richness. The biomass of dominant phytoplankton taxonomic groups such as cyanobacteria (adjusted‐R2 = 0.53) and the abundance of dominant zooplankton taxonomic groups such as rotifers (adjusted‐R2 = 0.59) and daphnids (adjusted‐R2 = 0.51) were more predictable than other metric types. The plankton metric predictability increased when grouping phytoplankton species according to their functional traits (adjusted‐R2 = 0.37 ± 0.14, mean ± SD, n = 36 functional groups) compared to higher taxonomic units (adjusted‐R2 = 0.25 ± 0.15, n = 22 taxonomic groups). Light, nutrients, water temperature, and seasonality for phytoplankton and food resources for zooplankton were the main drivers of both taxonomic and functional groups, giving confidence that our models captured the expected major environmental drivers. Our quantitative analyses highlight the multidimensionality of lake planktonic responses to environmental drivers and have implications for our capacity to select appropriate metrics for forecasting the future of lake ecosystems under global change scenarios.European Union's Horizon 2020 Research and Innovation ProgrammeBelmont ForumBiodivERsALimnoSCenE

Climate change impacts on ecologically relevant hydrological indicators in three catchments in three European ecoregions

Freshwater species are adapted to and depend on various discharge conditions, such as 32 indicators of hydrologic alteration (IHA). Knowing how these indicators will be altered under climate change is essential for predicting species response and to develop mitigation concepts. The simulation of IHA under climate change is subject to considerable uncertainties which should be considered to obtain credible and robust predictions. Therefore, we investigated the major uncertainties inherent in climate change data and processing: general circulation model (GCM) and regional climate model (RCM) choice, representative concentration pathway (RCP) scenario, bias correction (BC) method, all within three mesoscale catchments in the European ecoregions: Central Plains, Central Highlands, and Alpine. Highest uncertainties were caused by the GCM and RCM choice, followed by the type of BC and the RCP. For the prediction, we reduced these uncertainties tailored to the ideal depiction of the IHA in each ecoregion. Together with a significance test, this enabled a robust depiction of the change in IHA for two future time periods. We found diverging changes within the ecoregions, caused by the complex interaction between precipitation, temperature and the governing catchment hydrological processes. The results provide an important basis for further impact research, especially for ecological freshwater studies

Projected effects of Climate-change-induced flow alterations on stream macroinvertebrate abundances

Global change has the potential to affect river flow conditions which are fundamental determinants of physical habitats. Predictions of the effects of flow alterations on aquatic biota have mostly been assessed based on species ecological traits (e.g., current preferences), which are difficult to link to quantitative discharge data. Alternatively, we used empirically derived predictive relationships for species’ response to flow to assess the effect of flow alterations due to climate change in two contrasting central European river catchments. Predictive relationships were set up for 294 individual species based on (1) abundance data from 223 sampling sites in the Kinzig lower‐mountainous catchment and 67 sites in the Treene lowland catchment, and (2) flow conditions at these sites described by five flow metrics quantifying the duration, frequency, magnitude, timing and rate of flow events using present‐day gauging data. Species’ abundances were predicted for three periods: (1) baseline (1998–2017), (2) horizon 2050 (2046–2065) and (3) horizon 2090 (2080–2099) based on these empirical relationships and using high‐resolution modeled discharge data for the present and future climate conditions. We compared the differences in predicted abundances among periods for individual species at each site, where the percent change served as a proxy to assess the potential species responses to flow alterations. Climate change was predicted to most strongly affect the low‐flow conditions, leading to decreased abundances of species up to −42%. Finally combining the response of all species over all metrics indicated increasing overall species assemblage responses in 98% of the studied river reaches in both projected horizons and were significantly larger in the lower‐mountainous Kinzig compared to the lowland Treene catchment. Such quantitative analyses of freshwater taxa responses to flow alterations provide valuable tools for predicting potential climate‐change impacts on species abundances and can be applied to any stressor, species, or region

Social equity shapes zone-selection: Balancing aquatic biodiversity conservation and ecosystem services delivery in the transboundary Danube River Basin

Freshwater biodiversity is declining, despite national and international efforts to manage and protect freshwater ecosystems. Ecosystem-based management (EBM) has been proposed as an approach that could more efficiently and adaptively balance ecological and societal needs. However, this raises the question of how social and ecological objectives can be included in an integrated management plan. Here, we present a generic model-coupling framework tailored to address this question for freshwater ecosystems, using three components: biodiversity, ecosystem services (ESS), and a spatial prioritisation that aims to balance the spatial representation of biodiversity and ESS supply and demand. We illustrate this model-coupling approach within the Danube River Basin using the spatially explicit, potential distribution of (i) 85 fish species as a surrogate for biodiversity as modelled using hierarchical Bayesian models, and (ii) four estimated ESS layers produced by the Artificial Intelligence for Ecosystem Services (ARIES) platform (with ESS supply defined as carbon storage and flood regulation, and demand specified as recreation and water use). These are then used for (iii) a joint spatial prioritisation of biodiversity and ESS employing Marxan with Zones, laying out the spatial representation of multiple management zones. Given the transboundary setting of the Danube River Basin, we also run comparative analyses including the country-level purchasing power parity (PPP)-adjusted gross domestic product (GDP) and each country's percent cover of the total basin area as potential cost factors, illustrating a scheme for balancing the share of establishing specific zones among countries. We demonstrate how emphasizing various biodiversity or ESS targets in an EBM model-coupling framework can be used to cost-effectively test various spatially explicit management options across a multi-national case study. We further discuss possible limitations, future developments, and requirements for effectively managing a balance between biodiversity and ESS supply and demand in freshwater ecosystems