How much do we know about trade-offs in ecosystem services? A systematic review of empirical research observations

As an important domain of sustainability science, trade-offs in ecosystem services (ES) is crucial for spatial planning to sustainably manage natural resources while satisfying the needs of local and non-local beneficiaries. However, there is still a growing debate in understanding, characterization, and visualization of the trade-off relationships. This paper systematically reviews a total of 473 articles, published in the last 16 years (2005-2020) through 135 academic journals, based on empirical studies conducted in over 80 countries, and led by the researcher from over 50 countries. Trade-off relationships are often visualized as spatial associations of ES, but very few articles have characterized trade-offs as the causal interaction among ES. More than two-thirds of the studies were carried out in temperate and sub-tropical regions, but we depicted an under-representation of the critical ecosystems in tropics. About 90% of the articles were based on funded research but the involvement of government institutions was very low (<10%). Trade-off analysis was based only on biophysical constraints of the ecosystem, as observed in more than 80% of the selected articles, without due regards of the divergence in utility functions of different stakeholders and ecosystem beneficiaries. This study identifies a total of 198 pairs of conflicting ES, of which the trade-off between crop production and carbon/climate services has the highest records of observation (i.e., as identified by 20% of the total studies). Further, this study identifies the major drivers (i.e., ecological and social) and stakeholders (i.e., land users and government agencies) of trade-off in ES, and major gaps in the analytical approach to understand the trade-off relationships. Based on our findings, we have discussed and recommended a number of research trajectories, including trans-disciplinary research considering both biophysical constraints and utility functions, in order to guide the future direction of sustainability science through the creation of win-win scenarios.