Accurate and reliable estimates of gross primary productivity (GPP) are required for monitoring the global carbon cycle at different spatial and temporal scales. Because GPP displays high spatial and temporal variation, remote sensing plays a major role in producing gridded estimates of GPP across spatiotemporal scales. In this context, understanding...
Severe droughts occurred in the western United States during recent decades, and continued human greenhouse gas emissions are expected to exacerbate warming and drying in this region. We investigated the role of water availability in shaping forest carbon cycling and morphological traits in the eastern Cascade Mountains, Oregon, focusing on...
Severe droughts occurred in the western United States during recent decades, and continued human greenhouse gas emissions are expected to exacerbate warming and drying in this region. We investigated the role of water availability in shaping forest carbon cycling and morphological traits in the eastern Cascade Mountains, Oregon, focusing on...
A semi-parametric PAR diffuse radiation model
was developed using commonly measured climatic variables
from 108 site-years of data from 17 AmeriFlux sites. The
model has a logistic form and improves upon previous efforts
using a larger data set and physically viable climate
variables as predictors, including relative humidity, clearness
index,...
Predicting the net effects on the carbon and water
balance of semi-arid forests under future conditions depends
on ecosystem processes responding to changes in
soil and atmospheric drought. Here we apply a combination
of field observations and soil–plant–atmosphere modeling
(SPA) to study carbon and water dynamics in a regenerating
ponderosa...
Gross primary productivity (GPP) is the largest
and most variable component of the global terrestrial carbon
cycle. Repeatable and accurate monitoring of terrestrial
GPP is therefore critical for quantifying dynamics in
regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is
widely used to monitor and...
The eddy-covariance method often underestimates fluxes under stable, low-wind conditions at night when turbulence is not well developed. The most common approach to resolve the problem of nighttime flux underestimation is to identify and remove the deficit periods using friction-velocity (u*) threshold filters (u*[superscript Th]). This study modifies an accepted...
Ecosystem process models are important tools for determining the interactive effects of global change and disturbance on forest carbon dynamics. Here we evaluated and improved terrestrial carbon cycling simulated by the Community Land Model (CLM4), the land model portion of the Community Earth System Model (CESM1.0.4). Our analysis was conducted...
Earth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model–data agreement, but usually do not...
Disturbance processes of various types substantially modify ecosystem carbon dynamics both temporally and spatially, and constitute a fundamental part of larger landscape-level dynamics. Forests typically lose carbon for several years to several decades following severe disturbance, but our understanding of the duration and dynamics of post-disturbance forest carbon fluxes remains...