Integrating approaches and methodologies into phenological research in Neotropical dry forests: a systematic review

• Published in: Environmental research letters Vol. 20; no. 8; pp. 83002 - 83014
• Main Authors: Pereira Dos Santos, Maria Maraíza, Morellato, Leonor Patrícia Cerdeira, Freire da Silva, Thieres George, Jardim, Alexandre Maniçoba da Rosa Ferraz, de Souza, Carlos André Alves, Dos Santos, Wilma Roberta, Bastos de Souza, Luciana Sandra
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.08.2025
• Subjects: Biodiversity; Caatinga; Climate adaptation; Climate change; Climate models; Climate prediction; Climate variability; Climatic data; Conservation; Data collection; Drought; Dry forests; environmental triggers; Forests; leaf phenology; Leaves; Literature reviews; phenocams; Phenology; Plants (botany); Prediction models; Tropical forests
• DOI: 10.1088/1748-9326/ade9e2
• ISSN: 1748-9326

Phenological shifts are increasingly recognized as tangible indicators of plant responses to climate change. Tropical dry forests (TDFs), in particular, are key ecosystems for unraveling the mechanisms driving phenological dynamics, given their crucial role in biodiversity conservation and carbon balance. Although phenological research has advanced rapidly in recent decades in tandem with new methodological innovations, TDFs remain underrepresented. Consequently, the extent to which recent approaches have improved our understanding of leaf changes is still poorly understood. Here, we conducted a comprehensive literature review of phenology in seasonally dry tropical forests (SDTFs) in the Neotropics using Web of Science and Scopus databases up to December 2024. We aimed to synthesize methodological advances, environmental drivers, and functional traits related to phenology, providing insights about mechanisms underlying phenological shifts in Neotropical SDTFs. We documented a significant expansion in phenology research in Neotropical SDTFs over the last decade, with a concentration of studies in South America, particularly Brazil, followed by Central America. Despite these advances, long-term studies remain scarce, limiting our ability to detect interannual variability and long-term trends. The integration of high-resolution monitoring tools, such as phenocameras, has enhanced data collection across spatial and temporal scales, improving our ability to track phenological changes. Furthermore, plant functional traits such as wood density and leaf characteristics associated with deciduousness are key for understanding drought adaptation strategies in dry forests. Given the strong dependence of SDTFs phenological patterns on climate variability, predictive models that incorporate phenological observations, plant functional traits, and climate data will be further crucial for refining our understanding of adaptive mechanisms and improving forecasts of vegetation responses in dry forests. By highlighting research gaps and future directions, this synthesis provides a foundation to improve conservation efforts and climate resilience assessments in seasonally dry tropical ecosystems.