title: Environmental controls on canopy foliar nitrogen distributions in a Neotropical lowland forest.
abstract: Distributions of foliar nutrients across forest canopies can give insight into their plant functional diversity and improve our understanding of biogeochemical cycling. We used airborne remote sensing and partial least squares regression to quantify canopy foliar nitrogen (foliar N) across ~164 km2of wet lowland tropical forest in the Osa Peninsula, Costa Rica. We determined the relative influence of climate and topography on the observed patterns of foliar N using a gradient boosting model technique. At a local scale, where climate and substrate were constant, we explored the influence of slope position on foliar N by quantifying foliar N on remnant terraces, their adjacent slopes, and knife-edged ridges. In addition, we climbed and sampled 540 trees and analyzed foliar N in order to quantify the role of species identity (phylogeny) and environmental factors in predicting foliar N. Observed foliar N heterogeneity reflected environmental factors working at multiple spatial scales. Across the larger landscape, elevation and precipitation had the highest relative influence on predicting foliar N (30% and 24%), followed by soils (15%), site exposure (9%), compound topographic index (8%), substrate (6%), and landscape dissection (6%). Phylogeny explained ~75% of the variation in the field collected foliar N data, suggesting that phylogeny largely underpins the response to the environmental factors. Taken together, these data suggest that a large fraction of the variance in foliar N across the landscape is proximately driven by species composition, though ultimately this is likely a response to abiotic factors such as climate and topography. Future work should focus on the mechanisms and feedbacks involved, and how shifts in climate may translate to changes in forest function.
authors.affiliation: Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA.
authors.forename: Christopher S
authors.initials: CS
authors.lastname: Balzotti
authors.affiliation: Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA.
authors.forename: Gregory P
authors.initials: GP
authors.lastname: Asner
authors.affiliation: Nicholas School of the Environment, Duke University, Durham, North Carolina, 27708, USA.
authors.forename: Philip G
authors.initials: PG
authors.lastname: Taylor
authors.affiliation: Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana, 59812, USA.
authors.forename: Cory C
authors.initials: CC
authors.lastname: Cleveland
authors.affiliation: Department of Natural Resources and Environmental Management, University of Hawaii at Manoa, Honolulu, Hawaii, 96822, USA.
authors.forename: Rebecca
authors.initials: R
authors.lastname: Cole
authors.affiliation: Department of Global Ecology, Carnegie Institution for Science, Stanford, California, 94305, USA.
authors.forename: Roberta E
authors.initials: RE
authors.lastname: Martin
authors.affiliation: Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, Montana, 59812, USA.
authors.forename: Megan
authors.initials: M
authors.lastname: Nasto
authors.affiliation: Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, 02912, USA.
authors.forename: Brooke B
authors.initials: BB
authors.lastname: Osborne
authors.affiliation: Department of Ecology and Evolutionary Biology, Brown University, Providence, Rhode Island, 02912, USA.
authors.forename: Stephen
authors.initials: S
authors.lastname: Porder
authors.affiliation: Nicholas School of the Environment, Duke University, Durham, North Carolina, 27708, USA.
authors.forename: Alan R
authors.initials: AR
authors.lastname: Townsend
mesh_terms: D003364:Costa Rica; D065928:Forests; D009584:Nitrogen; D018515:Plant Leaves; D014197:Trees; D014329:Tropical Climate
chemical_list: D009584:Nitrogen
keywords: Carnegie Airborne Observatory; Osa Peninsula, Costa Rica; gradient boosting; hyperspectral; light detection and ranging; partial least squares regression; topography