ARBOLES: a trait-based understanding of LATAM forest biodiversity and resilience

Abstract

Latin American (LATAM) forests from Brazil, Peru, Argentina and Chile are global epicentres of biological and environmental diversity. LATAM forests are home of Earth's poorest and most vulnerable people and are highly threatened by local anthropogenic disturbance and global environmental change. ARBOLES aims to improve our understanding of LATAM forest response to anthropogenic disturbance and environmental change, by integrating established forest inventory surveys with cutting-edge functional trait, genomics, experimental, computational and remote sensing approaches. Anthropogenic disturbances include deforestation, within-forest disturbance such as logging or wildfires, and defaunation. There are considerable opportunities for active restoration and enrichment of degraded land, evidenced by the Brazilian government's pledge to re-forest 12 million hectares by 2030, with a substantial reforestation commitment also made by Chile. LATAM forests are also affected by rapid global environmental change, including temperature rise (0.5 °C/decade) in some regions and droughts, causing widespread increases in forest fires. Therefore, ARBOLES will test the overarching hypothesis that plant traits determine (i) biodiversity patterns, (ii) temporal responses to global environmental change, (iii) regeneration success along gradients of anthropogenic influence, and (iv) performance of species in restoration projects. These hypotheses will be tested following five objectives. Objective 1 (O1) quantifies functional trait patterns across LATAM forests. Objective 2 (O2) assesses the trait basis of temporal changes in old-growth LATAM forests, linking these to global environmental change. Objective 3 (O3) examines whether there are predictable changes in the mean trait values of regenerating trees along gradients of forest loss, edge effects, and defaunation. Objective 4 (O4) evaluates the capacity of functional traits to inform management decisions in an applied context (forest restoration practice and planting/harvesting of commercially important taxa). Objective 5 (O5) provides scaled-up knowledge of trait variation in space and time by combining high and moderate spatial resolution remote sensing (RS) derived information with emergent computational processing methods and field-based trait data (O1-3). The outputs of this project will provide insights into the four main themes of the call, helping LATAM countries to manage natural capital in terms of biodiversity, carbon and other ecosystems services as well as to achieve critical Sustainable Development Goals. (AU)