Central and South America tropical dry forest (TDF) is a water-limited biome with a high number of endemic species and numerous ecosystem services which has experienced a boom in research in the last decade. Although the number of case studies across these seasonal, water-limited, tropical forests has increased, there has not been a comprehensive review to assess the physiological variability of this biome across the continent and assess how these forests respond to climatic variables. Additionally, understanding forest change and resilience under climatic variability, currently and in the future, is essential for assessing the future extent and health of forests in the future. Therefore, the objective of this paper is to provide a literature review on the variability of TDF diversity and structure across a latitudinal gradient and to assess how these components respond to differences in climatic variables across this geographic area. We first assess the current state of understanding of the structure, biomass, phenological cycles, and successional stages across the latitudinal gradient. We subsequently review the response of these five areas to differences in precipitation, temperature, and extreme weather events, such as droughts and hurricanes. We find that there is a range of adaptability to precipitation, with many areas exhibiting drought tolerance except under the most extreme circumstances, while being susceptible to damage from increased extreme precipitation events. Finally, we use this climatic response to provide a commentary on the projected resilience of TDFs under climatic changes, finding a likelihood of resilience under drying scenarios, although model projections do not agree on the magnitude or direction of precipitation change. This review of quantitative studies will provide more concrete details on the current diversity that encompasses the TDF, the natural climatic ranges under which this ecosystem can survive and thrive, and can help inform future forest management practices under climate change scenarios.

Agricultural expansion is causing deforestation in Minas Gerais, Brazil, converting savanna and tropical dry forest to farmland, and in 2012, Brazil’s Forest Code was revised with the government reducing deforestation restrictions. Understanding the effects of policy change on rates and locations of natural ecosystem loss is imperative. In this paper, deforestation in Minas Gerais was simulated annually until 2020 using Dinamica Environment for Geoprocessing Objects (Dinamica EGO). This system is a state-of-the-art land use and cover change (LUCC) model which incorporates government policy, landscape maps, and other biophysical and anthropogenic datasets. Three studied scenarios: (i) business as usual, (ii) increased deforestation, and (iii) decreased deforestation showed more transition to agriculture from shrubland compared to forests, and consistent locations for most deforestation. The probability of conversion to agriculture is strongly tied to areas with the smallest patches of original biome remaining. Increases in agricultural revenue are projected to continue with a loss of 25% of the remaining Cerrado land in the next decade if profit is maximized. The addition of biodiversity value as a tax on land sale prices, estimated at over $750,000,000 USD using the cost of extracting and maintaining current species ex-situ, can save more than 1 million hectares of shrubland with minimal effects on the economy of the State of Minas Gerais. With environmental policy determining rates of deforestation and economics driving the location of land clearing, site-specific protection or market accounting of externalities is needed to balance economic development and conservation.

Tropical dry forests (TDFs) worldwide have an environment-sensitive phenological signal, which easily marks their response to the changing climatic conditions, especially precipitation and temperature. Using TDF phenological characteristics as a proxy, this study aims to evaluate their current continental response to climate change across the Americas. Here, we show that TDFs are resilient to water stress and droughts by increasing their rain use efficiency (RUE) in drier years and recovering to average RUE in the year following the drought. Additionally, we find that TDF productivity trends over the past 18 years are spatially clustered, with sites in the northern hemisphere experiencing increased productivity, while equatorial regions have no change, and the southern hemisphere exhibiting decreased productivity. The results indicate that the TDF will be resilient under future climatic conditions, particularly if there are increasing drought conditions.

Climate change will have considerable impact on the global economy. Estimates of the economic damages due to climate change have focused on the effect of average temperature, but not the effect of other important climate variables. Related research has not explored the sub-annual economic cycles which may be impacted by climate volatility. To address these deficits, we propose a flexible, non-linear framework which includes a wide range of climate variables to estimate changes in GDP and project sub-annual economic cycle adjustments (period, amplitude, trough depth). We find that the inclusion of a more robust set of climate variables improves model performance by over 20%. Importantly, the improved model predicts an increase in GDP rather than a decrease when only temperature is considered. We also find that climate influences the sub-annual economics of all but one province in Canada. Highest stressed were the Prairie and Atlantic regions. Least stressed was the Southeastern region. Our study advances understanding of the nuances in the relationship between climate change and economic output in Canada. It also provides a method that can be applied to related economies globally to target adaptation and resilience management.