학술논문

Observed variation in soil properties can drive large variation in modelled forest functioning and composition during tropical forest secondary succession
Document Type
article
Source
New Phytologist. 223(4)
Subject
Environmental Sciences
Biological Sciences
Ecology
Biomass
Computer Simulation
Entropy
Forests
Models
Theoretical
Soil
Tropical Climate
ecosystem composition
ED2-MEND-N-COM
forest biomass
soil nutrients
soil texture
spatial variation
terrestrial ecosystem modelling
tropical forests
ED2−MEND−N-COM
Agricultural and Veterinary Sciences
Plant Biology & Botany
Plant biology
Climate change impacts and adaptation
Ecological applications
Language
Abstract
Censuses of tropical forest plots reveal large variation in biomass and plant composition. This paper evaluates whether such variation can emerge solely from realistic variation in a set of commonly measured soil chemical and physical properties. Controlled simulations were performed using a mechanistic model that includes forest dynamics, microbe-mediated biogeochemistry, and competition for nitrogen and phosphorus. Observations from 18 forest inventory plots in Guanacaste, Costa Rica were used to determine realistic variation in soil properties. In simulations of secondary succession, the across-plot range in plant biomass reached 30% of the mean and was attributable primarily to nutrient limitation and secondarily to soil texture differences that affected water availability. The contributions of different plant functional types to total biomass varied widely across plots and depended on soil nutrient status. In Central America, soil-induced variation in plant biomass increased with mean annual precipitation because of changes in nutrient limitation. In Central America, large variation in plant biomass and ecosystem composition arises mechanistically from realistic variation in soil properties. The degree of biomass and compositional variation is climate sensitive. In general, model predictions can be improved through better representation of soil nutrient processes, including their spatial variation.