water Article An Extended Ecosystem Model for Understanding EE2 Indirect Effects on a Freshwater Food Web and Its Ecosystem Function Resilience Ludiwine Clouzot, Charlotte Haguenauer and Peter A. Vanrolleghem * modelEAU, Université Laval, Québec, QC G1V 0A6, Canada; [email protected] (L.C.); [email protected] (C.H.) * Correspondence: [email protected] Received: 8 May 2020; Accepted: 15 June 2020; Published: 17 June 2020 Abstract: Freshwater species are highly impacted by human activities and the consequences on ecosystem functioning are still not well understood. In the literature, a multitrophic perspective appears to be key to advance future biodiversity and ecosystem functioning (BEF) research. This paper aims at studying indirect effects of the synthetic hormone 17α-ethinylestradiol (EE2) on a freshwater food web by creating BEF links, through the interpretation of seasonal cycles and multitrophic interactions. An ecosystem model previously developed using experimental data from a unique whole-ecosystem study on EE2 was extended with the addition of Chaoborus, an omnivorous insect. During the experimental study, a collapse of fathead minnow was measured after one year of exposure. The simulation results showed that EE2 indirect effects on other fishes (horizontal diversity) and lower trophic levels (vertical diversity) were connected to multitrophic interactions with a top-down cascade effect. The results also demonstrated that adding an omnivorous, mid-trophic level group such as Chaoborus enhances resilience. Conversely, missing such a species means that the actual resilience of an ecosystem and its functioning cannot be properly simulated. Thus, the extended ecosystem model offers a tool that can help better understand what is happening after environmental perturbations, such as with EE2. Keywords: 17(alpha)-ethinylestradiol; biodiversity; Chaoborus; ecological function; experimental lake area; freshwater ecosystem; multitrophic interactions 1. Introduction Pharmaceuticals and hormones are continuously entering the environment through release from wastewater treatment plants (WWTPs). In the last few decades, the occurrence of those emerging compounds has increasingly received attention due to their harm to the ecosystem. A review on worldwide environmental monitoring of water organic pollutants identified by European guidelines [1,2]demonstrated that pharmaceuticals represent the most studied class of Watch List compounds (42.9%), the natural estrogens E1 and E2 and the synthetic 17α-ethinylestradiol (EE2) being the second most studied (35.3%). Both the natural and synthetic hormones were previously identified as the main substances responsible for estrogenic activities in WWTPs, with concentrations as low as ng/L, sometimes exceeding their predicted no-effect concentrations (PNECs) for ecological toxicity [3]. Species responses to these environmental estrogens vary considerably, with fishes having much higher sensitivities than invertebrates [4,5]. Indirect effects on tolerant species, mediated by ecological mechanisms, may also appear in the environment but cannot be measured by single species laboratory-based toxicity tests; this is why population, community or ecosystem level studies are required [6]. EE2, one of the most potent synthetic estrogens, interferes in multiple ways with the activity of different physiological endpoints of aquatic organisms, including the endocrine system [7–10]. In a Water 2020, 12, 1736; doi:10.3390/w12061736 www.mdpi.com/journal/water Water 2020, 12, 1736 2 of 22 multi-year whole-ecosystem study performed at an experimental lake, [11] exposed well-defined fish and lower-trophic level populations to environmentally relevant concentrations of EE2. During this experimental study, a collapse of fathead minnow was measured after one year of exposure to EE2. A mix of reduced gamete production, increased gamete mortality and an increase of both adults and juvenile mortality was hypothesized to explain the collapse of both adult and juvenile fathead minnow due to EE2 addition in reference [12]. Since several small fishes declined in the experimental lake after EE2 additions, the authors sought evidence for a trophic cascade resulting from the associated reductions in planktivory and benthivory fish [13]. Trophic cascades (indirect effects mediated through consumer–resource interactions) are a well-studied type of indirect effect, and are generally considered in terms of ‘top–down’ (predator influence on lower trophic levels) or ‘bottom–up’ (nutrient/food/prey influence on higher trophic levels) mechanism [6]. Unlike the many studies that have shown direct effects of estrogens and their mimics on aquatic species, especially fishes, Kidd et al. [13] advance the understanding of how estrogen-induced changes in fish abundance can lead to indirect effects on freshwater food webs. This paper aims at taking further their interpretation of the direct and indirect effects of EE2 by modeling links between aquatic biodiversity and ecological functioning. In terms of extinction risk, freshwater species are among the world’s most threatened [14]. Thus, one important question to be answered is: “To what extent does species loss from freshwaters affect ecosystem functioning and their ability to provide ecosystem goods and services for people?”. “Ecosystem function” (EF) is a general term that includes stocks of materials (e.g., carbon, water and mineral nutrients) and rates of processes involving fluxes of energy and matter between trophic levels and the environment. EFs are linked to biodiversity, and can thus be broadly defined as the biological, geochemical and physical processes that take place or occur within an ecosystem. Due to such complexity, the underlying role of biodiversity in ecosystem functioning, its relevance for ecosystem service provision in general, as well as the consequences of its decline, remain poorly understood [15]. A multitrophic perspective is key to advancing future biodiversity and ecosystem functioning (BEF) research and to address some of its most important remaining challenges [16]. Research on biodiversity and ecosystem functioning is one of the most prominent topics investigated by ecologists in the last three decades, with two new domains (Aquatic Food Webs and Agricultural Landscapes) arising in the last decade [17]. Besides, the “ecosystem service” has become the most prominent science policy term used in the last 8 years (2011–2018). Ecosystem-based management (EBM) is a collaborative management approach used with the intention to restore, enhance and protect the resilience of an ecosystem so as to sustain or improve ecosystem services (ES) and protect biodiversity, while considering nature and society [18]. In their review, Eisenhauer et al. [16] concluded that understanding why and how the strength of biodiversity effects varies with environmental conditions and at which spatial scales different mechanisms operate, will be key to operationalize BEF insights for ecosystem management, society and decision making. Duffy et al. [19] pointed out that understanding how biodiversity affects functioning of complex ecosystems will benefit from integrating theory and experiments with simulations and network-based approaches. Indeed, integrated models could highlight priorities for the collection of new empirical data, identify gaps in our existing theories of how ecosystems work, help develop new concepts for how biodiversity composition and ecosystem function interact, and allow predicting BEF relations and its drivers at larger scales [20]. Besides, Queirós et al. [21] identified a need to translate observed mechanisms (short-term and single species) into conceptual models that include combinations of species and environmental gradients not yet observed (multiple stressors, long-term and interacting species). According to Barnes et al. [22], integrating trophic complexity is key to understanding how biodiversity affects whole-ecosystem functioning. Therefore, this study takes up the challenge to improve an ecosystem model that was previously developed and successfully calibrated [12], with the addition of Chaoborus, an omnivorous insect that is an important food source for higher trophic levels and preys on lower trophic levels. This extended ecosystem model will be used to confirm and take Water 2020, 12, 1736 3 of 22 further the hypotheses on EE2 indirect effects on a freshwater food web [13]. Besides, indirect EE2 effects will be compared with and without the presence of Chaoborus in the food web. Finally, how the presence of Chaoborus enhances the resilience of ecosystem functioning will be discussed. Consultation with the ecologists observing the ecosystem was made to verify that major ecosystem mechanisms were correctly represented in the model. This was necessary as a first-order assessment of model reliability when extrapolated to conditions beyond the observed state [21]. The results presented in this paper will support the transition of BEF from a description of patterns to a predictive science [16], which can help better understand the link between biodiversity and ecosystem functioning in the context of EBM. 2. Materials and Methods 2.1. Step 1: Collecting Experimental Data The experimental data used for the model were collected during a multi-year whole-lake study on Lake 260 in the Experimental Lakes Area (ELA) in northwestern Ontario, Canada (all sampling details can be found in [13]). This experimental lake is oligotrophic (high oxygen