Protected areas buffer the Brazilian semi-arid biome from climate change

Proline and antioxidant enzymes protect Tabebuia aurea (Bignoniaceae) from transitory water deficiency

Abstract Water deficiency is a major abiotic stress that limits biomass production and drives plant species distributions. We evaluate the effects of water deficiency on ecophysiological and biochemical parameters of seedlings of Tabebuia aurea. Plants were subjected to daily watering (control) and to stress by soil water deficiency for 29 days. Leaf area, plant biomass, gas exchange, SPAD index, maximum quantum yield (Fv / Fm), quantum yield of PSII (ΦPSII), superoxide dismutase (SOD) and L-ascorbate peroxidase (APX) activity, lipid peroxidation, and proline content were recorded. Plants responded to water deficit by reducing leaf area and accumulating proline. Stomatal conductance was reduced to limit the water loss by transpiration. However, limiting CO2 uptake caused reduction in photosynthesis and biomass. The excess of energy unutilized by photosynthesis reduced SPAD index and ΦPSII. As a result, we observed an increase in SOD and APX activity, protecting chloroplast membranes from further damages caused by lipid peroxidation. Our results indicate that T. aurea have capacity to survive under water deficiency reducing stomatal aperture, but affecting the rate of CO2 assimilation. Nevertheless, plants showed mechanisms to preventing damages to the photosynthetic apparatus. Such plasticity is an important adaptation for plants growing in dry environmental.

Energy Balance, CO2 Balance, and Meteorological Aspects of Desertification Hotspots in Northeast Brazil

The main objective of this study was to evaluate meteorological variables and the simulated components of energy and CO2 balances in desertification hotspots in Northeast Brazil. Meteorological data were obtained from the National Institute of Meteorology measurement network for the Cabrobó and Ibimirim sites. Initially, hourly linear trends were calculated for the meteorological variables using the non-parametric Mann–Kendall test. Then, the seasonal variability in the components of energy and CO2 balances was assessed through simulations of the simple tropical ecosystem (SITE) model. Results showed evidence of increasing air temperature trends in the Cabrobó site in the first months of the year, which was not observed in the Ibimirim site. Regarding relative humidity, increasing trends were observed in a few months over the Cabrobó site, while decreasing trends were observed in the Ibimirim site. Opposite behaviors were also identified for the trends in wind speed in both sites. Gross primary production (GPP) and net ecosystem exchange (NEE) simulated values were higher in the first half of the year in both sites. GPP varied from 0.8 to 1.2 g C m−² h−¹, and NEE fluctuated around approximately −5 g C m−² h−¹. These results indicate that rainfall seasonality is a crucial factor for the modulation of CO2 and energy balance fluxes in the Caatinga biome.

Soil predictors are crucial for modelling vegetation distribution and its responses to climate change

Bioclimatic envelope models have been extensively used to predict the vegetation dynamics in response to climate changes. However, they are prone to the uncertainties arising from General Circulation Models (GCMs), classification algorithms and predictors, with low-resolution results and little detail at the regional level. Novel research has focused on the improvement of these models through a combination of climate and soil predictors to enhance ecological consistency. In this framework, we aimed to apply a joint edaphoclimatic envelope to predict the current and future vegetation distribution in the semiarid region of Brazil, which encompasses several classes of vegetation in response to the significant environmental heterogeneity. We employed a variety of machine learning algorithms and GCMs under RCP 4.5 and 8.5 scenarios of Coupled Model Intercomparison Project Phase 5 (CMIP5), in 1 km resolution. The combination of climate and soil predictors resulted in higher detail at landscape-scale and better distinction of vegetations with overlapping climatic niches. In forecasts, soil predictors imposed a buffer effect on vegetation dynamics as they reduced shifts driven solely by climatic drift. Our results with the edaphoclimatic approach pointed to an expansion of the dry Caatinga vegetation, ranging from an average of 16% to 24% on RCP 4.5 and RCP8.5 scenarios, respectively. The shift in environmental suitability from forest to open and dry vegetation implies a major loss to biodiversity, as well as compromising the provision of ecosystem services important for maintaining the economy and livelihoods of the world's largest semiarid population. Predicting the most susceptible regions to future climate change is the first step in developing strategies to mitigate impacts in these areas.

Climate change will reduce suitable Caatinga dry forest habitat for endemic plants with disproportionate impacts on specialized reproductive strategies

Global climate change alters the dynamic of natural ecosystems and directly affects species distributions, persistence and diversity. The impacts of climate change may lead to dramatic changes in biotic interactions, such as pollination and seed dispersal. Life history traits are extremely important to consider the vulnerability of a species to climate change, producing more robust models than those based primarily on species distributions. Here, we hypothesized that rising temperatures and aridity will reduce suitable habitats for the endemic flora of the Caatinga, the most diverse dry tropical forest on Earth. Specifically, species with specialized reproductive traits (e.g. vertebrate pollination, biotic dispersal, obligatory cross-pollination) should be more affected by climate change than those with generalist traits. We performed two ecological niche models (current and future) to simulate the effects of climate change on the distribution area of endemic species in relation to life-history traits. We used the MIROC-ESM and CCSM4 models for both intermediate (RCP4.5) and highest predicted (RCP8.5) GHG emission scenarios, with a resolution of 30' (~1 km²). Habitat with high occurrence probability (>80%) of endemic species will be reduced (up to ~10% for trees, ~13% for non-arboreous, 10–28% for species with any pollination/reproductive system), with the greatest reductions for species with specialized reproductive traits. In addition, the likely concentration of endemic plants in the extreme northeastern portion of the Caatinga, in more mesic areas, coincides with the currently most human-modified areas of the ecosystem, which combined with climate change will further contract suitable habitats of endemic species. In conclusion, plant species endemic to the Caatinga are highly vulnerable to even conservative scenarios of future climate change and may lose much of their climatic envelopes. New protected areas should be located in the northeastern portion of the Caatinga, which hosts a more favorable climate, but is currently exposed to escalating agricultural intensification.