Most leaf functional trait studies in the Amazon basin do not consider ontogenetic variations (leaf age), which may influence ecosystem productivity throughout the year. When leaf age is taken into account, it is generally considered discontinuous, and leaves are classified into age categories based on qualitative observations. Here, we quantified age-dependent changes in leaf functional traits such as the maximum carboxylation rate of ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) (Vcmax), stomatal control (Cgs%), leaf dry mass per area and leaf macronutrient concentrations for nine naturally growing Amazon tropical trees with variable phenological strategies. Leaf ages were assessed by monthly censuses of branch-level leaf demography; we also performed leaf trait measurements accounting for leaf chronological age based on days elapsed since the first inclusion in the leaf demography, not predetermined age classes. At the tree community scale, a nonlinear relationship between Vcmax and leaf age existed: young, developing leaves showed the lowest mean photosynthetic capacity, increasing to a maximum at 45 days and then decreasing gradually with age in both continuous and categorical age group analyses. Maturation times among species and phenological habits differed substantially, from 8 ± 30 to 238 ± 30 days, and the rate of decline of Vcmax varied from −0.003 to −0.065 μmol CO2 m−2 s−1 day−1. Stomatal control increased significantly in young leaves but remained constant after peaking. Mass-based phosphorus and potassium concentrations displayed negative relationships with leaf age, whereas nitrogen did not vary temporally. Differences in life strategies, leaf nutrient concentrations and phenological types, not the leaf age effect alone, may thus be important factors for understanding observed photosynthesis seasonality in Amazonian forests. Furthermore, assigning leaf age categories in diverse tree communities may not be the recommended method for studying carbon uptake seasonality in the Amazon, since the relationship between Vcmax and leaf age could not be confirmed for all trees.

Biogeochemistry, Ecology, Tropical ecology

Approximately 2.5 × 106 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year−1), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year−1). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.

Worldwide cities are at the forefront of tackling climate change; however, it is not clear to what extent they are prepared for the challenge, particularly in the context of lower income countries, where the need for action is urgent. In this context, many of cities struggle to develop evidence-based approaches to assess their current and future capacity to deal with climate impacts and inform the design of policies to respond in the short/long term. Based both on extensive field research carried out in Brazilian cities and on urban adaptation literature, we develop and test the Urban Adaptation Index (UAI) that cities can use to assess their current adaptive capacity in a realistic/achievable way. The index includes 26 indicators and focuses on a set of public policies to support interventions connected to adaptation: housing, urban mobility, sustainable agriculture, environmental management, and climate impact response. To make the UAI more usable/accessible, we use empirical data that is publicly available, and develop an approach that can be implemented with resources already available in many Brazilian cities. We illustrate the UAI usability by applying the index to the 645 municipalities of the state of São Paulo. Results show that more than half of the municipalities present low UAI ratings; however, municipalities located in metropolitan regions, where the majority of the population live, tend to have higher ratings. Practitioners agreed on the value of the UAI as a tool to monitor the current situation and changes regarding local potential capacity to adapt to climate change