PDF hosted at the Radboud Repository of the Radboud University Nijmegen The following full text is a publisher's version. For additional information about this publication click this link. https://hdl.handle.net/2066/228804 Please be advised that this information was generated on 2021-10-02 and may be subject to change. Ecological Modelling 438 (2020) 109331 Contents lists available at ScienceDirect Ecological Modelling journal homepage: www.elsevier.com/locate/ecolmodel Integration of local knowledge and data for spatially quantifying ecosystem services in the Hoeksche Waard, the Netherlands M.J. Paulin a,b,*, M. Rutgers a, T. de Nijs a, A.J. Hendriks b, K.R. Koopman a, T. Van Buul c, M. Frambach d, G. Sardano e, A.M. Breure a,b a National Institute for Public Health and the Environment (RIVM), Bilthoven, Netherlands b Radboud University, Nijmegen, Netherlands c Utrecht University, Utrecht, Netherlands d Tauw, Utrecht, Netherlands e University of Amsterdam (UvA), Amsterdam, Netherlands ARTICLE INFO ABSTRACT Keywords: Enhancing consideration of the ecosystem services concept within decision-making calls for integration of local Field margins knowledge and data within assessments to capture context-specific spatial and thematic detail. This paper Ecosystem services modelling demonstrates how local knowledge and (biophysical, sociocultural, economic) data can be integrated within Local information ecosystem service assessments by use of well-established spatial quantification methods. We hypothesise that Biophysical ecosystem services can be spatially quantified at high spatial and thematic detail by integration of local Sociocultural Monetary knowledge and data within models, contributing to identificationof key factors that influencetheir delivery. We demonstrate this by making use of local knowledge and data to assess ecosystem services in the Hoeksche Waard, a Dutch municipality characterised by historically-rich cultural landscapes and predominant agriculture. Ecosystem services assessed include crop production, air quality regulation, human health, pest control, soil biodiversity, sociocultural values, property value. Quantificationmethods were selected based on their suitability for modelling ecosystem services given particular resource endowments (i.e., time, data, knowledge). Methods implemented include look-up tables, causal relationships, expert elicitation, primary data extrapolation, and regression models. Maps displaying the distribution of ecosystem services at high spatial resolution (10 × 10 m) enabled identification of factors that influence their delivery, including the distribution and typology of natural elements, ecological pressures that require mitigation, and the distribution of inhabitants that act as ecosystem service beneficiaries. For instance, the distribution and typology of field margins plays a key role in the sup­ pression of pests (aphids) by natural enemies (hoverflies, carabids, coccinellids). Air quality regulation (i.e. particulate matter retention) is highest in the northeast sector of the municipality given higher concentrations of particulate matter that require mitigation due to the area’s proximity to the cities of Rotterdam and Dordrecht. Contributions by natural elements to human health and property value are prominent in villages, where most inhabitants and thus built-up property are concentrated. 1. Introduction humans with, such as crop and groundwater production for human consumption and animal feed (MEA, 2005). Regulating services are Ecosystem services are the direct and indirect benefits that ecosys­ ecological processes that directly or indirectly contribute to human tems provide humans with (Costanza et al., 2017; MEA, 2005). Ac­ well-being (MEA, 2005). Examples include the retention of atmospheric cording to the Common International Classification of Ecosystem concentrations of harmful pollutants by vegetation and water (Remme Services (CICES; Haines-Young and Potschin, 2018), ecosystem services et al., 2018; Janhall,¨ 2015), the potential contribution of biological pest can be classified as provisioning, regulation and maintenance (also control to final crop yield and ecosystem resilience (Tschumi et al., regulating; MEA, 2005; TEEB, 2010), and cultural services. Provisioning 2016), and climate regulation through carbon sequestration by vegeta­ services are the material contributions that natural capital endows tion and soils (Díaz et al., 2009; Breure et al., 2018). Cultural services * Corresponding author. E-mail address: [email protected] (M.J. Paulin). https://doi.org/10.1016/j.ecolmodel.2020.109331 Received 25 March 2020; Received in revised form 6 October 2020; Accepted 11 October 2020 Available online 17 October 2020 0304-3800/© 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). M.J. Paulin et al. Ecological Modelling 438 (2020) 109331 are non-material benefits that ecosystems provide for humans, such as number of studies reviewed publications mapping ecosystem services in the spiritual, recreational, or intrinsic value people assign to natural order to identify and conceptualise commonly implemented spatial elements and landscapes (MEA, 2005). quantification methods (Martínez-Harms and Balvanera, 2012; The ecosystem services concept provides an opportunity for incor­ Gr^et-Regamey et al., 2017; Lavorel et al., 2017). We demonstrate how porating scientificknowledge within spatial management (Haase et al., well-established methods can be integrated to spatially quantify seven 2014; Walsh et al., 2015). It can serve as a language through which ecosystem services in the Hoeksche Waard, incorporating local knowl­ science communicates to society, shedding light on the various mecha­ edge and data (Section 3). The Hoeksche Waard is a Dutch municipality nisms by which ecosystems generate value for humans (Potschin and characterised by historically-rich cultural landscapes and predominant Haines-Young, 2016; Breure et al., 2012). Recognising the concept’s agriculture. Covering 40% of Earth’s terrestrial ecosystems, agricultural potential, recent years have seen an upsurge in the number of initiatives landscapes comprise a range of ecosystem services and stakeholders, calling for integration of ecosystem services within environmental making them some of the most interesting to analyse (Foley et al., 2011; decision-making (Díaz et al., 2015; EC, 2011; CBD, 2010). To meet their Montoya et al., 2020). The Hoeksche Waard is a particularly interesting common objectives, a number of standardised modelling approaches study site, given notable interest by local stakeholders to collaborate to have been developed (e.g., InVEST, ARIES, ESTIMAP; Tallis and Polaski, meet their common objectives. Spatial quantificationmethods that were 2011; Villa et al., 2014; Zulian et al., 2014; Maes et al., 2016). Their aim implemented in this study were conceptualised based on the seminal is to contribute to the standardisation and harmonisation of the work of Martínez-Harms & Balvanera (2012) and Schroter¨ et al. (2015), ecosystem service spatial quantificationprocess, thereby facilitating the who conducted extensive literature reviews to identify spatial quantifi­ comparability of results across space and time. Despite these initiatives, cation methods that are commonly implemented to map ecosystem consideration of the ecosystem services concept within decision-making services. Implemented methods include causal relationships, expert remains limited (Haase et al., 2014; Walsh et al., 2015). This partly elicitation, primary data extrapolation, regression models, and look-up results from a limited integration of spatial and thematic detail central to tables. We elaborate on these methods and how they can be integrated particular socioecological systems within assessments (Derkzen et al., to spatially quantify ecosystem services given different resource en­ 2015; Martínez-Lopez´ et al., 2019), as well as challenges in the dowments (i.e., knowledge, data, time; Section 2). A key feature of this communication of complex models and their outputs to non-scientist study’s methodology is that all models incorporate local knowledge and end users (Villa et al., 2014). This limits confidence in assessment data. We hypothesise that ecosystem services can be spatially quantified output and thereby its uptake to support spatial planning (Lilburne and at high spatial and thematic detail by integration of local knowledge and Tarantola, 2009; Schuwirth et al., 2019). data within models, contributing to identification of key factors that To address this challenge, enhanced integration of local knowledge influence their delivery. and data within ecosystem service models is needed (Martínez-Lopez´ et al., 2019; Orchard-Webb et al., 2016). Consideration of local knowl­ 2. Materials and methods edge and data (where available) is instrumental for capturing site-specificsociocultural and ecological factors that influencethe access 2.1. Study area to and use of ecosystem services by beneficiaries (Díaz et al., 2018; Paulin et al., 2020a). It also contributes to the democratisation and The Hoeksche Waard is a municipality with a surface area of legitimisation of the assessment process, supporting the integration of approximately 324 km2, distributed across croplands (49%), grasslands final results within decision-making (Orchard-Webb et al., 2016). (13%), nature areas (13%), small and large water bodies (17%), and Despite