Assessing the impact of grassland management on landscape multifunctionality

Highlights

• An online tool identifies optimal landscape compositions for desired ecosystem services.

• When the desired services are synergic, the optimum is their common best landscape composition.

• When the desired services trade-off, a mix of grassland intensity is most multifunctional.

• Such tools could support decision-making processes and aid conflict resolution.

Abstract

Land-use intensification has contrasting effects on different ecosystem services, often leading to land-use conflicts. While multiple studies have demonstrated how landscape-scale strategies can minimise the trade-off between agricultural production and biodiversity conservation, little is known about which land-use strategies maximise the landscape-level supply of multiple ecosystem services (landscape multifunctionality), a common goal of stakeholder communities.

We combine comprehensive data collected from 150 German grassland sites with a simulation approach to identify landscape compositions, with differing proportions of low-, medium-, and high-intensity grasslands, that minimise trade-offs between the six main grassland ecosystem services prioritised by local stakeholders: biodiversity conservation, aesthetic value, productivity, carbon storage, foraging, and regional identity. Results are made accessible through an online tool that provides information on which compositions best meet any combination of user-defined priorities (https://neyret.shinyapps.io/landscape_composition_for_multifunctionality/).

Results show that an optimal landscape composition can be identified for any pattern of ecosystem service priorities. However, multifunctionality was similar and low for all landscape compositions in cases where there are strong trade-offs between services (e.g. aesthetic value and fodder production), where many services were prioritised, and where drivers other than land use played an important role. We also found that if moderate service levels are deemed acceptable, then strategies in which both high and low intensity grasslands are present can deliver landscape multifunctionality. The tool presented can aid informed decision-making by predicting the impact of future changes in landscape composition, and by allowing for the relative roles of stakeholder priorities and biophysical trade-offs to be understood by scientists and practitioners alike.

Introduction

Habitat conversion and land-use intensification are driving biodiversity loss and changes to ecosystem service supply across the world (IPBES, 2019). While high land-use intensification promotes a small number of ecosystem services related to food production, it is often detrimental to biodiversity conservation (Bennett et al., 2009, Lavorel et al., 2011, Raudsepp-Hearne et al., 2010) and other regulating or cultural ecosystem services that depend on biodiversity for their delivery (Allan et al., 2015, Le Clec'h et al., 2019). Such contrasting responses of different ecosystem services to ecosystem drivers often make it impossible to achieve high levels of all desired services at a local or lanscape scale (van der Plas et al., 2019). This has led to land-use conflicts, which are becoming increasingly common across the globe (Goldstein et al., 2012).

To date, much of the work on minimising trade-offs between ecosystem services within landscapes has compared a ‘land sparing’ strategy, in which semi-natural high-biodiversity areas and intensive farmland are spatially segregated, and a ‘land sharing’ strategy in which biodiversity conservation and commodity production are co-delivered in a landscape of intermediate intensity, and where these different land uses form a mosaic (Green, 2005). Within this field, most studies have found that land sparing is the best way to achieve high levels of both biodiversity conservation and commodity production (Phalan et al., 2011, Simons and Weisser, 2017). However, multiple studies have also stressed the limitations of the land sharing versus land sparing concept. The framework focuses on just two extreme strategies, and on only two services - commodity production and biodiversity conservation (Bennett, 2017, Fischer et al., 2014), while in reality, most landscapes are expected to provide multiple services, even within a single ecosystem type. This is the case for semi-natural grasslands (sensu Bullock et al. (2011)), which supply a wide range of highly prioritised ecosystem services including water provision, climate regulation (carbon storage) and recreation services, in addition to food production and biodiversity conservation (Bengtsson et al., 2019). Accounting for these additional ecosystem services could significantly affect which land-use strategy is considered optimal, meaning the best strategy for achieving high levels of multiple services within grassland landscapes remains unknown.

One way of measuring how land use affects the overall supply of multiple services is the ecosystem service multifunctionality approach (Manning et al., 2018). Ecosystem service multifunctionality is defined as the simultaneous supply of multiple prioritised ecosystem services, relative to their human demand (Linders et al. 2021). It builds upon the metrics used in biodiversity-ecosystem functioning research (Allan et al., 2015, Barnes et al., 2017, Byrnes et al., 2014) by combining ecological and biophysical data describing the supply of multiple ecosystem services with social data that quantifies the relative priority given by stakeholder groups to each service. The approach also advances on existing methods such as the identification of ecosystem service bundles (Frei et al., 2018, Raymond et al., 2009) by measuring the overall supply of ecosystem services relative to their demand. The resulting multifunctionality metrics can therefore be seen as summarising the overall benefit provided by a system to stakeholders.

Here, we combine the multifunctionality approach with data simulation methods to identify the optimal landscape composition for multiple ecosystem services. This approach involves varying the proportion of land under different intensities in data simulations and measuring the outcome on ecosystem service multifunctionality. We also investigate how the relative priority of services to land users affects the optimal strategy. The analysis was achieved by using ecosystem service data collected at 150 grassland sites that vary in their intensity, found in the three regions of the large-scale and long-term Biodiversity Exploratories project, in Germany. This was utilised in simulations in which artificial ‘landscapes’ of varying composition, in terms of land-use intensity, were assembled from site-level data (Fig. 1). We base our metrics of multifunctionality on six services which are directly linked to final benefits (sensu the cascade model, Mace et al., 2012, Fisher and Turner, 2008): fodder production, biodiversity conservation, climate change mitigation, aesthetic value, foraging opportunities and regional identity, covering all the services provided by grasslands that were demanded by the main stakeholder groups, as identified in a social survey (Supplementary Fig. A1). We hypothesised that heterogeneous landscapes composed of both high- and low-intensity sites would have the highest multifunctionality (van der Plas et al., 2019).