Fog immersion is a key factor linking patterns in vegetation structure and composition in tropical montane cloud forests: preliminary results of CloudNet meta-analysis

Thursday, 9 June 2016
Han Tseng1, Katherine Heineman2, Z. Carter Berry3, Rebecca Ostertag4, Patrick Martin5, Thomas W Giambelluca1 and CloudNet Database Contributors, (1)University of Hawaii at Manoa, Department of Geography, Honolulu, HI, United States, (2)University of Illinois at Urbana Champaign, Urbana, IL, United States, (3)University of New Hampshire Main Campus, Durham, NH, United States, (4)University of Hawaii at Hilo, Department of Biology, Hilo, HI, United States, (5)Colorado State University, Horticulture & Landscape Architecture, Fort Collins, CO, United States
Abstract:
Tropical montane cloud forests (TMCFs) are among the most unusual yet least studied ecosystems in the tropics, renowned for their high biodiversity and endemism, and the ecosystem services they provide. TMCFs often have reduced tree stature and high epiphytic biomass, and their climate tends to be wetter and cooler than other tropical forests. Frequent fog immersion is likely the key factor shaping TMCF systems; interactions between fog and vegetation are proposed to have significant effects on ecology and hydrology. However, while studies have discovered linkages, the climatic influences on TMCF structure and function remain largely unclear. This is partly due to difficulties in quantifying fog inputs and influence, and impediments to making comparisons among TMCF sites.

CloudNet is a research coordination network whose goal is to unify and advance study of TMCFs’ hydrological and ecological processes, including development of a global repository of TMCF field sites and datasets. Currently, the CloudNet database has data from 792 plots across 18 countries. Using these data and a global hydrological model (WaterWorld), we analyzed the relationship between fog input, cloud forest structure and species distribution. Multiple regression models show significant correlation between fog inputs and stem density, basal area, and woody plant diversity. Multivariate analysis found that fog inputs explained variation in tree species distributions that could not be explained by elevation and temperature alone. Based on this finding, we identified tree genera that are potentially sensitive to fog dynamics, and thus vulnerable to changes in cloud climatology. The limitations in the dataset due to model spatial resolution and low precision of some site coordinates highlight the need for more field-based climate data at finer scales. Additionally, CloudNet is still actively seeking collaborators particularly in Asia and Africa which are currently underrepresented in the database.

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