[1] Most global temperature analyses are based on station air temperatures. This study presents a global analysis of the relationship between remotely sensed annual maximum LST (LST max ) from the Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and the corresponding site-based maximum air temperature (T amax ) for every World Meteorological Organization station on Earth. The relationship is analyzed for different land cover types. We observed a strong positive correlation between LST max and T amax . As temperature increases, LST max increases faster than T amax and captures additional information on the concentration of thermal energy at the Earth's surface, and biophysical controls on surface temperature, such as surface roughness and transpirational cooling. For hot conditions and in nonforested cover types, LST is more closely coupled to the radiative and thermodynamic characteristics of the Earth than the air temperature (T air ). Barren areas, shrublands, grasslands, savannas, and croplands have LST max values between 10°C and 20°C hotter than the corresponding T amax at higher temperatures. Forest cover types are the exception with a near 1:1 relationship between LST max and T amax across the temperature range and 38°C as the approximate upper limit of LST max with the exception of subtropical deciduous forest types where LST max occurs after canopy senescence. The study shows a complex interaction between land cover and surface energy balances. This global, semiautomated annual analysis could provide a new, unique, monitoring metric for integrating land cover change and energy balance changes.

No abstract

Forests are undergoing significant changes throughout the globe. These changes can modify water, energy, and carbon balance of the land surface, which can ultimately affect climate. We utilize satellite data to quantify the potential and actual impacts of forest change on land surface temperature (LST) from 2003 to 2013. The potential effect of forest change on temperature is calculated by the LST difference between forest and nearby nonforest land, whereas the actual impact on temperature is quantified by the LST trend difference between deforested (afforested) and nearby unchanged forest (nonforest land) over several years. The good agreement found between potential and actual impacts both at annual and seasonal levels indicates that forest change can have detectable impacts on surface temperature trends. That impact, however, is different for maximum and minimum temperatures. Overall, deforestation caused a significant warming up to 0.28 K/decade on average temperature trends in tropical regions, a cooling up to −0.55 K/decade in boreal regions, a weak impact in the northern temperate regions, and strong warming (up to 0.32 K/decade) in the southern temperate regions. Afforestation induced an opposite impact on temperature trends. The magnitude of the estimated temperature impacts depends on both the threshold and the data set (Moderate Resolution Imaging Spectroradiometer and Landsat) by which forest cover change is defined. Such a latitudinal pattern in temperature impact is mainly caused by the competing effects of albedo and evapotranspiration on temperature. The methodology developed here can be used to evaluate the temperature change induced by forest cover change around the globe.

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 limited. Here we capitalize on a recent North American Carbon Program disturbance synthesis to discuss techniques and future work needed to better understand carbon dynamics after forest disturbance. Specifically, this paper addresses three topics: (1) the history, spatial distribution, and characteristics of different types of disturbance (in particular fire, insects, and harvest) in North America; (2) the integrated measurements and experimental designs required to quantify forest carbon dynamics in the years and decades after disturbance, as presented in a series of case studies; and (3) a synthesis of the greatest uncertainties spanning these studies, as well as the utility of multiple types of observations (independent but mutually constraining data) in understanding their dynamics. The case studies—in the southeast U.S., central boreal Canada, U.S. Rocky Mountains, and Pacific Northwest—explore how different measurements can be used to constrain and understand carbon dynamics in regrowing forests, with the most important measurements summarized for each disturbance type. We identify disturbance severity and history as key but highly uncertain factors driving post‐disturbance carbon source‐sink dynamics across all disturbance types. We suggest that imaginative, integrative analyses using multiple lines of evidence, increased measurement capabilities, shared models and online data sets, and innovative numerical algorithms hold promise for improved understanding and prediction of carbon dynamics in disturbance‐prone forests.

Incorporating ecological disturbance into biogeochemical models is critical for estimating current and future carbon stocks and fluxes. In particular, anthropogenic disturbances, such as forest conversion and wood harvest, strongly affect forest carbon dynamics within North America. This paper summarizes recent (2000–2008) rates of extraction, including both conversion and harvest, derived from national forest inventories for North America (the United States, Canada, and Mexico). During the 2000s, 6.1 million ha/yr were affected by harvest, another 1.0 million ha/yr were converted to other land uses through gross deforestation, and 0.4 million ha/yr were degraded. Thus about 1.0% of North America's forests experienced some form of anthropogenic disturbance each year. However, due to harvest recovery, afforestation, and reforestation, the total forest area on the continent has been roughly stable during the decade. On average, about 110 m3 of roundwood volume was extracted per hectare harvested across the continent. Patterns of extraction vary among the three countries, with U.S. and Canadian activity dominated by partial and clear‐cut harvest, respectively, and activity in Mexico dominated by conversion (deforestation) for agriculture. Temporal trends in harvest and clearing may be affected by economic variables, technology, and forest policy decisions. While overall rates of extraction appear fairly stable in all three countries since the 1980s, harvest within the United States has shifted toward the southern United States and away from the Pacific Northwest.

The timing, location, and magnitude of major disturbance events are currently major uncertainties in the global carbon cycle. Accurate information on the location, spatial extent, and duration of disturbance at the continental scale is needed to evaluate the ecosystem impacts of land cover changes due to wildfire, insect epidemics, flooding, climate change, and human-triggered land use. This paper describes an algorithm developed to serve as an automated, economical, systematic disturbance detection index for global application using Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua Land Surface Temperature (LST) and Terra/MODIS Enhanced Vegetation Index (EVI) data from 2003 to 2004. The algorithm is based on the consistent radiometric relationship between LST and EVI computed on a pixel-by-pixel basis. We used annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Verification of potential disturbance events from our algorithm was carried out by demonstration of close association with independently confirmed, well-documented historical wildfire events throughout the study domain. We also examined the response of the disturbance index to irrigation by comparing a heavily irrigated poplar tree farm to the adjacent semiarid vegetation. Anomalous disturbance results were further examined by association with precipitation variability across areas of the study domain known for large interannual vegetation variability. The results illustrate that our algorithm is capable of detecting the location and spatial extent of wildfire with precision, is sensitive to the incremental process of recovery of disturbed landscapes, and shows strong sensitivity to irrigation. Disturbance detection in areas with high interannual variability of precipitation will benefit from a multiyear data set to better separate natural variability from true disturbance.

No Abstract available.

Large-diameter trees store disproportionally massive amounts of carbon and are a major driver of carbon cycle dynamics in forests worldwide. In the temperate forests of the western United States, proposed changes to Forest Plans would significantly weaken protections for a large portion of trees greater than 53 cm (21 inches) in diameter (herein referred to as "large-diameter trees") across 11.5 million acres (∼4.7 million ha) of National Forest lands. This study is among the first to report how carbon storage in large trees and forest ecosystems would be affected by a proposed policy. We examined the proportion of large-diameter trees on National Forest lands east of the Cascade Mountains crest in Oregon and Washington, their contribution to overall aboveground carbon (AGC) storage, and the potential reduction in carbon stocks resulting from widespread harvest. We analyzed forest inventory data collected on 3,335 plots and found that large trees play a major role in the accumulated carbon stock of these forests. Tree AGC (kg) increases sharply with tree diameter at breast height (DBH; cm) among five dominant tree species. Large trees accounted for 2.0 to 3.7% of all stems (DBH ≥ 1" or 2.54 cm) among five tree species; but held 33 to 46% of the total AGC stored by each species. Pooled across the five dominant species, large trees accounted for 3% of the 636,520 trees occurring on the inventory plots but stored 42% of the total AGC. A recently proposed large-scale vegetation management project that involved widespread harvest of large trees, mostly grand fir, would have removed ∼44% of the AGC stored in these large-diameter trees, and released a large amount of carbon dioxide to the atmosphere. Given the urgency of keeping additional carbon out of the atmosphere and continuing carbon accumulation from the atmosphere to protect the climate system, it would be prudent to continue protecting ecosystems with large trees for their carbon stores, and also for their co-benefits of habitat for biodiversity, resilience to drought and fire, and microclimate buffering under future climate extremes.