Climate change will likely threaten areas of suitable habitats for the most relevant medicinal plants native to the Caatinga dry forest

Abstract

Disruption of ecosystem services associated with climate change may affect human well-being in different ways. Medicinal plants provide extremely relevant ecosystem services. Here, we tested the hypothesis that highly suitable habitats (i.e., suitability ≥ 0.8) for medicinal plants in Caatinga dry forest may be potentially contracted under scenarios of climate change, which are represented by different levels of increases in greenhouse gas emissions. We performed species distribution modelling to simulate the effects of climate change on the range of suitable habitats for medicinal plants native to the Caatinga dry forest. We selected the 10 most important plant species based on their high local importance as medicinal resources. We documented that climate change may distinctly affect areas of suitable habitats for medicinal plants in the Caatinga dry forest. Independent of the future climatic scenario projected to 2090, 70% of the studied species will likely experience reductions in their areas of highly suitable habitats and 30% will likely experience increases. Specifically, suitable habitats will likely be reduced for (1) Amburana cearensis, (2) Anadenanthera colubrina, (3) Bauhinia cheilantha, (4) Myracrodruon urundeuva, (5) Neocalyptrocalyx longifolium, (6) Operculina hamiltonii, (7) O. macrocarpa; and will likely be increased for (1) Cereus jamacaru, (2) Erythrina velutina, (3) Maytenus rigida. We also documented a reduction in medicinal plant species richness and composition in all three future climatic scenarios analyzed. We alert that potential future contractions of highly suitable habitats for the most important medicinal plants may compromise ecosystem functions and the provisioning of relevant natural medicines, mainly to low-income communities, which are abundant in the Caatinga dry forest.

Tree height, leaf thickness and seed size drive Caatinga plants' sensitivity to climate change

“…On the other hand, plants with larger SS are expected to expand their distribution area, with an estimated 19% increase in distribution area for every 1 cm increase in seed size (Table 1; Figure 5a). flora: Silva et al, 2019Silva et al, , 2022. Our results differ from these studies, as they show that most Caatinga species (58.4%) are likely to increase their distribution, which supports our first hypothesis.…”

“…Numerous studies indicate that Caatinga species may reduce their distribution area in the future (e.g., Cactaceae : Centeno‐Alvarado et al, 2022; Holoregmia viscida : Rabelo‐Costa et al, 2022; endemic flora: Silva et al, 2019, 2022). Our results differ from these studies, as they show that most Caatinga species (58.4%) are likely to increase their distribution, which supports our first hypothesis.…”

Vegetation diversity and habitat suitability modeling of the invasive plant Bellucia pentamera in conservation forests of West Sumatra, Indonesia

“…The evaluation criteria for model prediction accuracy were categorized into four groups: poor (AUC<0.80), fair (0.80≤AUC<0.90), good (0.90≤AUC<0.95), and excellent (0.95≤AUC≤1.00). TSS evaluates a model's overall accuracy relative to random accuracy, with a TSS score exceeding 0.5 indicating optimal performance (Silva et al 2022).…”

Potential Geographic Distribution of <i>Durio oxleyanus</i> (Malvaceae): a Threatened Wild Fruit Plant Species in Sumatra, Indonesia

“…TSS recognizes a model's overall accuracy based on its random accuracy, assigning a score between -1 and 1, with values close to 1 indicating optimal performance [25]. TSS values greater than 0.5 are considered adequate for informing model performance [26].…”