Delineation of the study and research objectives

1.2.1 Identification of the working field

Integrated constructed wetlands (ICWs) rely on a complex interplay of physical, chemical and biological processes that deserve attention during decision-making and prior to implementing on-site measures. More specifically, the success of ICWs (either after construction or restoration) ultimately depends heavily on (1) the integration in its surrounding, (2) the degree of pollutant removal and (3) the resulting augmented biodiversity. With the current freshwater biodiversity crisis in mind (Harrison et al., 2018; He et al., 2019), the majority of this work is dedicated to the biodiversity potential of ICWs, without completely ignoring the physical and chemical aspects.

The biological response to the prevailing abiotic conditions and dynamics can be inferred from experiments, models or a combination of both. More importantly, both data sources entail a continuum that ranges from a simplified to a highly complex approach. For instance, experiments can be performed under controlled laboratory conditions with a single treatment factor, though can be as complex as restoring hydraulic conditions and assessing the difference in species richness over time.

Similarly, models to infer species-specific habitat suitability and distribution patterns can be purely data-driven (empirical) or completely mechanistic (process-based), yet the design and application of all models is greatly determined by their intended usage.

This variety in experiment and model complexity requires a further delineation of the working field considered throughout this work. Given the increasing importance of environmental data science in decision-making and the growing amount of publicly-available occurrence data sets (Gibert et al., 2018a; Maldonado et al., 2015), it was decided to work with data-driven modelling techniques. These models allow for inferring species-specific habitat preferences, though tend to be challenged by a lack of data or by limited integration of species dynamics. This is especially the case for rare and alien species, which advocates the use of simplified experiments to infer and forecast species-specific behaviour. In short, both models and experiments are considered and applied to support the biotic restoration and construction of ICWs.

Aside from this conceptual delineation, several boundary conditions require specification prior to identifying the knowledge gaps and associated study objectives.

Firstly, the physical design is assumed to promote relatively high hydraulic retention times and to represent inclined banks that allow for a gradient in water depth (and associated microhabitats). Secondly, the chemical conditions mainly represent a wastewater polishing stage and are, therefore, assumed to reflect elevated nutrient levels. Thirdly, the geographic location is focused on Belgium and the Netherlands and assumes a similar climate (i.e. no important steering climatic variables).

INTRODUCTION

11 1.2.2 Research objectives

The conceptual delineation of the study area (see Section 1.2.1) creates a transparent foundation for outlining the practical research objectives of this work. These objectives help to link and streamline individual studies and can be easily divided into three major themes: (1) literature review, (2) data-driven modelling and (3) autecological experiments.

To start, literature provides an essential basis to narrow the practical working field further. More specifically, ICWs have already been introduced in Section 1.1.3, though deserve a more in-depth description of the various chemical processes and biotic interactions that take place within. Similarly, a variety of data-driven modelling techniques exists, which merits a detailed qualitative comparison prior to technique selection. Specific research objectives related to the literature review on ICWs and modelling techniques are provided in Section 1.2.2.1.

Secondly, data-driven modelling is not limited to technique selection, but also includes data cleaning and pre-processing in order to improve the quality of the data. This is especially the case when dealing with publicly available data, as these often contain noise and impure information (Maldonado et al., 2015). The geographical delineation of the study allows the use of the Limnodata Neerlandica (Knoben and van der Wal, 2015), which is characterised by a relatively high spatiotemporal coverage. The structure of this data set supports the development of models trained with presence-absence data, which narrows the number of techniques to be considered in the first theme. Specific research objectives related to data-driven modelling are introduced in Section 1.2.2.2.

Thirdly, experiments provide valuable information when insufficient data is available for model development. The conceptual framework entails open water systems with elevated nutrient levels and are, similar to other freshwater systems, exposed to the introduction of alien species. Only a fraction of the introduced alien species survives (see Box 1.1), though these survivors can drastically affect ecosystem structure and functioning. Therefore, alien species with a negative effect on native species are best known in advance to support proactive management. In contrast, when such a species is already present, reactive management is needed to reduce its impact. Data-driven models are generally incapable of providing appropriate answers to these questions, which highlights the importance of experiments. Specific research objectives related to these autecological experiments are summarised in Section 1.2.2.3.

Throughout this work, these three themes are dealt with in the presented order, and subdivided in a series of research questions and related objective. For each theme, a visual representation is provided, along with the identification of the chapter dealing with the objective(s).

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1.2.2.1 Theme 1: Exploring experiences

When working with integrated constructed wetlands, identification of a biotic group that represents habitat modifiers is recommended as they shape and transform the local ecosystem. Hence, the first research question is summarised as: “Which biotic groups are relatively strong habitat modifiers?” (Figure 1.2). An answer to this question is obtained by creating an overview of how biotic groups interact in shallow eutrophic freshwater systems (Objective 1.1) and determining which group has a relatively large impact on both the abiotic conditions and biotic community (Objective 1.2).

Secondly, a detailed description of the system under study is essential to construct the overall framework. Therefore, the second research question within this theme entails:

“What hampers implementing Integrated Constructed Wetlands (ICWs)?” (Figure 1.2).

An answer to this question is obtained by summarising wastewater treatment performance of constructed wetlands (Objective 1.3) and elaborating on the desired functions to identify current knowledge gaps (Objective 1.4).

Lastly, species occurrence is highly dependent on the prevailing abiotic conditions and biotic interactions, which can be combined in a modelling framework. Yet, as the number of available techniques increases rapidly, the following research question remains: “What options exist for correlative habitat suitability modelling?” (Figure 1.2).

By comparing a selection of modelling techniques (Objective 1.5) and describing the overall modelling framework (Objective 1.6), an answer to this question is provided.

Figure 1.2: Content of the first theme, including research questions and underlying objectives. Research question 1.1 and 1.2 are discussed in Chapter 2, while research question 1.3 is discussed in Chapter 3 (see further).

INTRODUCTION

13 1.2.2.2 Theme 2: Model development

When developing ecological models, natural processes and interactions are simplified to ease interpretation by complexity reduction (Wilson et al., 2011). Therefore, model results should be interpreted with care, especially when publicly available data is used.

This real-world data is generally in need of cleaning to improve the overall information density prior to being used, thereby positively affecting model fit and related results (Maldonado et al., 2015; Zhang et al., 2003). Hence, the first research question of this theme can be summarised as: “How to prepare the available data to improve model performance?” (Figure 1.3). An answer to this question is obtained by identifying and applying a technique to deal with missing data (Objective 2.1), along with exploring data cleaning procedures and related threshold selection to increase the information content (Objective 2.2). With data and time being valuable aspects during modelling, related gains or losses will be juxtaposed with changes in accuracy.

Subsequently, the pre-processed data act as information source for the development of predictive models in order to identify those locations that will benefit from artificial introduction. Moreover, it also allows to identify locations that remain unsuitable for native species, yet suitable for invasive alien species. Therefore, the second research question of this theme entails: “How applicable is the selected modelling technique?”

(Figure 1.3). By developing specific models (Objective 2.3), derive species-specific habitat descriptors (Objective 2.4) and applying these models within a management framework (Objective 2.5), an answer to this research question is obtained.

Figure 1.3: Content of the second theme, including research questions and underlying objectives. Research question 2.1 is discussed in Chapters 5 and 6, while research question 2.2 is discussed in Chapter 7 (see further).

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1.2.2.3 Theme 3: Autecological experiments

Management of invasive alien species is significantly supported by the development of correlative habitat suitability and species distribution models (Boets et al., 2010;

Gallardo et al., 2012). Yet, the data-driven nature of most modelling techniques relies on the presence of these non-indigenous species within the non-native range, thereby hampering their application to support proper proactive management. Hence, the first research question within this theme is summarised as: “Can functional traits be used to infer invasive behaviour of alien species?” (Figure 1.4). An answer to this question is obtained by selecting traits according to the SMART guidelines (Specific – Measurable – Attainable – Relevant – Time-bound) (Objective 3.1), followed by the comparison of field observations with the achieved trait results (Objective 3.2).

Secondly, management of freshwater sites that have been invaded by an alien species can be based on developed habitat suitability or species distribution models. Yet, only a fraction of modelling techniques is able to substantially include temporal dynamics, which illustrates a major drawback of model-based management. Moreover, it represents the basis of the second research question within this experiment-based theme: “How does partial biomass removal affect species productivity?” (Figure 1.4). By experimentally determining biomass production and ratio under different pressures (Objective 3.3) and comparing the response of a native and alien population (Objective 3.4), an answer to this research question is obtained.

Figure 1.4: Content of the third theme, including research questions and underlying objectives. Research question 3.1 is discussed in Chapter 8, while research question 3.2 is discussed in Chapter 9 (see further).

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