Tropical ecosystems are among the most vulnerable to climate change. Understanding climate impacts on these ecosystems is a primary challenge for policy makers, ecologists, and conservationists today. We analyzed the vulnerability of ecosystems in a very heterogeneous tropical region in southern Ecuador, selected because of its exceptional biodiversity and its ecosystem services provided to people of southern Ecuador and northern Peru. The vulnerability assessment focused on three components: exposure, sensitivity, and adaptive capacity. For the first two components, we identified stressors or drivers of change that negatively influence ecosystems. For the third component, we identified existing and potential buffers that reduce impacts. This process was developed in workshops and by expert elicitation. Representative Concentration Pathway (RCP) scenarios were used, considering RCP 2.6 and RCP 8.5 for a time horizon to 2050. Under the RCP 2.6 scenario, the components of overall vulnerability in the southern region of Ecuador showed very low to moderate vulnerability for most areas, particularly in semi-deciduous forest ecosystems, Amazon semi-deciduous forest, Amazon rainforest, and mangrove forests. These areas had high vulnerability under the RCP 8.5 scenario. A variety of conservation strategies (e.g., protected areas) were shown to increase the adaptive capacity of ecosystems and reduce their vulnerability. We therefore recommend improving these conservation initiatives in ecosystems like dry forests, where the greatest vulnerability is evident.

The balance between the supply of multiple ecosystem services (ES) and the fulfillment of society demands is a challenge, especially in the tropics where different land use transition phases emerge. These phases are characterized by either a decline (from intact old-growth to logged forests) or a recovery of ES (successional forests, plantations, and agroforestry systems). This highlights the importance of ecosystem service multifunctionality (M) assessments across these land use transition phases as a basis for forest management and conservation. We analyzed synergies and trade-offs of ES to identify potential umbrella ES. We also evaluated the impact of logging activities in the decline of ES and M, and the influence of three recovery phases in the supply of ES and M. We installed 156 inventory plots (1600 m²) in the Ecuadorian Central Amazon and the Chocó. We estimated indicators for provisioning, regulating, supporting services and biodiversity. M indicator was estimated using the multifunctional average approach. Our results show that above-ground carbon stocks can be considered as an umbrella service as it presented high synergetic relations with M and various ES. We observed that logging activities caused a decline of 16–18% on M, with high impacts for timber volume and above-ground carbon stocks, calling for more sustainable practices with stricter post-harvesting control to avoid a higher depletion of ES and M. From the recovery phases it is evident that, successional forests offer the highest level of M, evidencing high potential to recover multiple ES after human disturbance.

Tropical dry forest is an important ecosystem that offers different good and services to communities. However, despite their importance, these ecosystems are the least studied and have been impacted by human activity in the last decades. Moreover, future projections show an additional impact caused by climate change. For this reason, the understanding of anthropogenic and climate change impacts will help to improve adaptation strategies for a better species conservation. Consequently, we analyzed the impact of climate change and stressors on species distribution from dry forest ecosystem in southern Ecuador. We identified the variables that could help to buffer the potential impacts. Indicator species of climate change impacts were chosen using a species selection index considering an importance index value, density, rarity and altitudinal range. The selected species were Cavanillesia platanifolia, Cordia macrantha (C. macrantha), Erythrina velutina, Handroanthus chrysanthus (H. chrysanthus) and Terminalia valverdeae (T. valverdeae). Species current and future distribution models were generated with information from Herbarium ‘Reinaldo Espinosa’ of the National University of Loja and permanent plots that were established between 2005 and 2009. We used climate data from WorldClim under two climate change scenarios based on two IPCC Representative Concentration Pathways; RCP 2.6 and RCP 8.5. To know if the species distribution will be placed in regions with high sensitivity or adaptive capacity, 13 stressor variables and 3 buffers were selected. The sensitivity and adaptive capacity maps were intersected with species future distribution models under RCP 2.6 and RCP 8.5. Four of five species in the analysis showed a reduction in their future distribution: C. macrantha, T. valverdeae and H. chrysanthus. These were reduced due to increasing niche restriction. Between 18 and 26% of species future distribution area were located in zones with high sensitivity. In addition, among 14% to 46% of species future distribution area could be in sites with high adaptive capacity. In these areas, conservation strategies can serve as buffers against climate change; however, nowadays there is a conservation gap that needs to be addressed through the implementation of different strategies oriented to reinforce the adaptive capacity of these species in dry forest ecosystems. Species distribution models showed no migration to higher altitudes, but we observed a reduction in areas with high probability of presence. Additionally, sites with high likelihood of species presence have been influenced by deforestation, fragmentation, land use and other stressors, that will likely diminish their ability to adapt to climate warming and increased rainfall variability.

Tropical forests, and more concretely, the Amazon Basin and the Chocó-Darién, are highly affected by deforestation activities. Households are the main land-use decision-makers and are key agents for forest conservation and deforestation. Understanding the determinants of deforestation at the household level is critical for conservation policies and sustainable development. We explore the drivers of household deforestation decisions, focusing on the quality of the forest resources (timber volume potential) and the institutional environment (conservation strategies, titling, and governmental grants). Both aspects are hypothesized to influence deforestation, but there is little empirical evidence. We address the following questions: (i) Does timber availability attract more deforestation? (ii) Do conservation strategies (incentive-based programs in the Central Amazon and protected areas in the Chocó-Darién) influence deforestation decisions in household located outside the areas under conservation? (iii) Does the absence of titling increase the odds of a household to deforest? (iv) Can governmental grants for poverty alleviation help in the fight against deforestation? We estimated a logit model, where the dependent variable reflects whether or not a household cleared forest within the farm. As predictors, we included the above variables and controlled by household-specific characteristics. This study was conducted in the Central Amazon and the Chocó-Darién of Ecuador, two major deforestation fronts in the country. We found that timber volume potential is associated with a higher odds of deforesting in the Central Amazon, but with a lower odds in the Chocó-Darién. Although conservation strategies can influence household decisions, the effects are context-dependent. Households near the incentive-based program (Central Amazon) have a lower odds of deforesting, whereas households near a protected area (Chocó-Darién) showed the opposite effect. Titling is also important for deforestation reduction; more attention is needed in the Chocó-Darién where numerous households are living in untitled lands. Finally, governmental grants for poverty alleviation showed the potential to generate positive environmental outcomes.