Toward understanding the dynamics of land change in Latin America: potential utility of a resilience approach for building archetypes of land-systems change

Abstract

Climate change, financial shocks, and fluctuations in international trade are some of the reasons why resilience is increasingly invoked in discussions about land-use policy. However, resilience assessments come with the challenge of operationalization, upscaling their conclusions while considering the context-specific nature of land-use dynamics and the common lack of long-term data. We revisit the approach of system archetypes for identifying resilience surrogates and apply it to land-use systems using seven case studies spread across Latin America. The approach relies on expert knowledge and literature-based characterizations of key processes and patterns of land-use change synthesized in a data template. These narrative accounts are then used to guide development of causal networks, from which potential surrogates for resilience are identified. This initial test of the method shows that deforestation, international trade, technological improvements, and conservation initiatives are key drivers of land-use change, and that rural migration, leasing and land pricing, conflicts in property rights, and international spillovers are common causal pathways that underlie land-use transitions. Our study demonstrates how archetypes can help to differentiate what is generic from context dependant. They help identify common causal pathways and leverage points across cases to further elucidate how policies work and where, as well as what policy lessons might transfer across heterogeneous settings.

Seeking sustainable pathways for land use in Latin America

“…By means of causal networks codeveloped with case experts, they found that deforestation, international trade, food demand, commodity prices, and technological change are key drivers of land use change; while rural migration, land pricing and property rights, as well as telecoupling are common causal pathways underlying land use transitions. Similar to Calaboni et al (2018), Rocha et al (2019) shows that successful policies are context dependent and in many cases competing political interests can lock land use in particular regimes.…”

“…The forest dynamics were not only driven by the economic incentives behind agriculture development, but also by competing policies to modernize agriculture on one hand, and protect natural resources on the other. Rocha et al (2019) studied system archetypes of land use change across seven case studies. By means of causal networks codeveloped with case experts, they found that deforestation, international trade, food demand, commodity prices, and technological change are key drivers of land use change; while rural migration, land pricing and property rights, as well as telecoupling are common causal pathways underlying land use transitions.…”

Mapping social-ecological systems archetypes

“…Typically depicted as causal diagrams, archetypes represent recurrent feedback structures reduced to 4 problem archetypes and their solutions [48][49][50]. These building blocks have inspired the identification of resilience surrogates in SES [51], shared causes [52] and potential interactions of regime shifts in SES [53], as well as archetypical configurations of land systems' change [54].…”

“…Our coarser resolution enabled us to include a larger variety of social-ecological variables at a scale where management strategies are usually decided. Our data-driven approach would benefit, however, of the integration of a building blocks perspective by including relevant processes such as large-scale land acquisitions, public policies, trade, or certification schemes, as shown in other structure oriented studies [54,56].…”

How can social–ecological system models simulate the emergence of social–ecological crises?

“…Research that highlights observed similarities among social-ecological contexts such as land system archetypes (Václavík et al, 2013) or decision-making types (Malek et al, 2019), can also aid identification of shared major processes (Rocha et al, 2019) or drivers of change (Harrison et al, 2018). A separate benefit of adopting a 'high-level' process approach is that the resulting models are likely to be widely understandable because the processes accord with those experienced by actors and stakeholders in any given system.…”