Jingfeng Xiao

Ecosystem carbon dioxide fluxes after disturbance in forests of North America

Disturbances are important for renewal of North American forests. Here we summarize more than 180 site years of eddy covariance measurements of carbon dioxide flux made at forest chronosequences in North America. The disturbances included stand-replacing fire (Alaska, Arizona, Manitoba, and Saskatchewan) and harvest (British Columbia, Florida, New Brunswick, Oregon, Quebec, Saskatchewan, and Wisconsin) events, insect infestations (gypsy moth, forest tent caterpillar, and mountain pine beetle), Hurricane Wilma, and silvicultural thinning (Arizona, California, and New Brunswick). Net ecosystem production (NEP) showed a carbon loss from all ecosystems following a stand-replacing disturbance, becoming a carbon sink by 20 years for all ecosystems and by 10 years for most. Maximum carbon losses following disturbance (g C m−2y−1) ranged from 1270 in Florida to 200 in boreal ecosystems. Similarly, for forests less than 100 years old, maximum uptake (g C m−2y−1) was 1180 in Florida mangroves and 210 in boreal ecosystems. More temperate forests had intermediate fluxes. Boreal ecosystems were relatively time invariant after 20 years, whereas western ecosystems tended to increase in carbon gain over time. This was driven mostly by gross photosynthetic production (GPP) because total ecosystem respiration (ER) and heterotrophic respiration were relatively invariant with age. GPP/ER was as low as 0.2 immediately following stand-replacing disturbance reaching a constant value of 1.2 after 20 years. NEP following insect defoliations and silvicultural thinning showed lesser changes than stand-replacing events, with decreases in the year of disturbance followed by rapid recovery. NEP decreased in a mangrove ecosystem following Hurricane Wilma because of a decrease in GPP and an increase in ER.

Simulating the Impacts of Disturbances on Forest Carbon Cycling in North America: Processes, Data, Models, and Challenges

[1] Forest disturbances greatly alter the carbon cycle at various spatial and temporal scales. It is critical to understand disturbance regimes and their impacts to better quantify regional and global carbon dynamics. This review of the status and major challenges in representing the impacts of disturbances in modeling the carbon dynamics across North America revealed some major advances and challenges. First, significant advances have been made in representation, scaling, and characterization of disturbances that should be included in regional modeling efforts. Second, there is a need to develop effective and comprehensive process‐based procedures and algorithms to quantify the immediate and long‐term impacts of disturbances on ecosystem succession, soils, microclimate, and cycles of carbon, water, and nutrients. Third, our capability to simulate the occurrences and severity of disturbances is very limited. Fourth, scaling issues have rarely been addressed in continental scale model applications. It is not fully understood which finer scale processes and properties need to be scaled to coarser spatial and temporal scales. Fifth, there are inadequate databases on disturbances at the continental scale to support the quantification of their effects on the carbon balance in North America. Finally, procedures are needed to quantify the uncertainty of model inputs, model parameters, and model structures, and thus to estimate their impacts on overall model uncertainty. Working together, the scientific community interested in disturbance and its impacts can identify the most uncertain issues surrounding the role of disturbance in the North American carbon budget and develop working hypotheses to reduce the uncertainty.

Macrosystems ecology: understanding ecological patterns and processes at continental scales

Macrosystems ecology is the study of diverse ecological phenomena at the scale of regions to continents and their interactions with phenomena at other scales. This emerging subdiscipline addresses ecological questions and environmental problems at these broad scales. Here, we describe this new field, show how it relates to modern ecological study, and highlight opportunities that stem from taking a macrosystems perspective. We present a hierarchical framework for investigating macrosystems at any level of ecological organization and in relation to broader and finer scales. Building on well-established theory and concepts from other subdisci- plines of ecology, we identify feedbacks, linkages among distant regions, and interactions that cross scales of space and time as the most likely sources of unexpected and novel behaviors in macrosystems. We present three examples that highlight the importance of this multiscaled systems perspective for understanding the ecology of regions to continents.

The 2010 spring drought reduced primary productivity in southwestern China

Many parts of the world experience frequent and severe droughts. Summer drought can significantly reduce primary productivity and carbon sequestration capacity. The impacts of spring droughts, however, have received much less attention. A severe and sustained spring drought occurred in southwestern China in 2010. Here we examine the influence of this spring drought on the primary productivity of terrestrial ecosystems using data on climate, vegetation greenness and productivity. We first assess the spatial extent, duration and severity of the drought using precipitation data and the Palmer drought severity index. We then examine the impacts of the drought on terrestrial ecosystems using satellite data for the period 2000?2010. Our results show that the spring drought substantially reduced the enhanced vegetation index (EVI) and gross primary productivity (GPP) during spring 2010 (March?May). Both EVI and GPP also substantially declined in the summer and did not fully recover from the drought stress until August. The drought reduced regional annual GPP and net primary productivity (NPP) in 2010 by 65 and 46?Tg?C?yr?1, respectively. Both annual GPP and NPP in 2010 were the lowest over the period 2000?2010. The negative effects of the drought on annual primary productivity were partly offset by the remarkably high productivity in August and September caused by the exceptionally wet conditions in late summer and early fall and the farming practices adopted to mitigate drought effects. Our results show that, like summer droughts, spring droughts can also have significant impacts on vegetation productivity and terrestrial carbon cycling.

Twentieth-Century Droughts and Their Impacts on Terrestrial Carbon Cycling in China

Abstract Midlatitude regions experienced frequent droughts during the twentieth century, but their impacts on terrestrial carbon balance are unclear. This paper presents a century-scale study of drought effects on the carbon balance of terrestrial ecosystems in China. The authors first characterized the severe extended droughts over the period 1901–2002 using the Palmer drought severity index and then examined how these droughts affected the terrestrial carbon dynamics using tree-ring width chronologies and a process-based biogeochemistry model, the Terrestrial Ecosystem Model (TEM). It is found that China suffered from a series of severe extended droughts during the twentieth century. The major drought periods included 1920–30, 1939–47, 1956–58, 1960–63, 1965–68, 1978–80, and 1999–2002. Most droughts generally reduced net primary productivity (NPP) and net ecosystem productivity (NEP) in large parts of drought-affected areas. Moreover, some of the droughts substantially reduced the countrywide annual NPP...

Geographical distribution of global greening trends and their climatic correlates: 1982-1998

We examined trends in vegetation activity at the global scale from 1982 to 1998 using a recently developed satellite‐based vegetation index in conjunction with a gridded global climate dataset. Vegetation greening trends were observed in the northern high latitudes, the northern middle latitudes, and parts of the tropics and subtropics. Temperature, and in particular spring warming, was the primary climatic factor associated with greening in the northern high latitudes and western Europe. Temperature trends also explained greening in the US Pacific Northwest, tropical and subtropical Africa, and eastern China. Precipitation was a strong correlate of greening in fragmented regions only. Decreases in greenness in southern South America, southern Africa, and central Australia were strongly correlated to both increases in temperature and decreases in precipitation. Over vast areas globally, strong positive trends in greenness exhibited no correlation with trends in either temperature or precipitation. These areas include the eastern United States, the African tropics and subtropics, most of the Indian subcontinent, and south‐east Asia. Thus, for large areas of land that are undergoing greening, there appears to be no climatic correlate. Globally, greening trends are a function of both climatic and non‐climatic factors, such as forest regrowth, CO2 enrichment, woody plant proliferation, and trends in agricultural practices.

Trends in vegetation activity and their climatic correlates: China 1982 to 1998

We combined a satellite-derived Leaf Area Index (LAI) dataset and a gridded climate dataset to analyse trends in vegetation activity and their correlation with climate variability in China between 1982 and 1998. Vegetation activity over the growing season increased 11.03% in China during the 17-year period, which is broadly consistent with the greening trend in the northern high latitudes in Eurasia and North America shown in previous studies. Approximately 99×106 ha of croplands and 35×106 ha of forest exhibited significant upward trends in growing season LAI, and accounted for 53% and 19% of the total vegetated area with greening trends, respectively. Temperature was the leading climatic factor controlling greening patterns. However, trends in agricultural practices, such as increased use of high-yield crops and application of chemical fertilizers, along with land-use changes such as afforestation and reforestation probably made a greater contribution to the greening trend than temperature. Increased vegetation activity in forests suggests an increasing carbon stock in forest biomass in China, which supports previous studies based on satellite sensor data and forest inventory data.

Vegetation response to extreme climate events on the Mongolian Plateau from 2000 to 2010

Climate change has led to more frequent extreme winters (aka, dzud) and summer droughts on the Mongolian Plateau during the last decade. Among these events, the 2000?2002 combined summer drought?dzud and 2010 dzud were the most severe on vegetation. We examined the vegetation response to these extremes through the past decade across the Mongolian Plateau as compared to decadal means. We first assessed the severity and extent of drought using the Tropical Rainfall Measuring Mission (TRMM) precipitation data and the Palmer drought severity index (PDSI). We then examined the effects of drought by mapping anomalies in vegetation indices (EVI, EVI2) and land surface temperature derived from MODIS and AVHRR for the period of 2000?2010. We found that the standardized anomalies of vegetation indices exhibited positively skewed frequency distributions in dry years, which were more common for the desert biome than for grasslands. For the desert biome, the dry years (2000?2001, 2005 and 2009) were characterized by negative anomalies with peak values between ?1.5 and ?0.5 and were statistically different (P?<?0.001) from relatively wet years (2003, 2004 and 2007). Conversely, the frequency distributions of the dry years were not statistically different (p?<?0.001) from those of the relatively wet years for the grassland biome, showing that they were less responsive to drought and more resilient than the desert biome. We found that the desert biome is more vulnerable to drought than the grassland biome. Spatially averaged EVI was strongly correlated with the proportion of land area affected by drought (PDSI?<??1) in Inner Mongolia (IM) and Outer Mongolia (OM), showing that droughts substantially reduced vegetation activity. The correlation was stronger for the desert biome (R2?=?65 and 60, p?<?0.05) than for the IM grassland biome (R2?=?53, p?<?0.05). Our results showed significant differences in the responses to extreme climatic events (summer drought and dzud) between the desert and grassland biomes on the Plateau.

Satellite evidence for significant biophysical consequences of the “Grain for Green” Program on the Loess Plateau in China

Afforestation has been implemented worldwide as regional and national policies to address environmental problems and to improve ecosystem services. Chinas central government launched the “Grain for Green” Program (GGP) in 1999 to increase forest cover and to control soil erosion by converting agricultural lands on steep slopes to forests and grasslands. Here a variety of satellite data products from the Moderate Resolution Imaging Spectroradiometer were used to assess the biophysical consequences of the GGP for the Loess Plateau, the pilot region of the program. The average tree cover of the plateau substantially increased because of the GGP, with a relative increase of 41.0%. The GGP led to significant increases in enhanced vegetation index (EVI), leaf area index, and the fraction of photosynthetically active radiation absorbed by canopies. The increase in forest productivity as approximated by EVI was not driven by elevated air temperature, changing precipitation, or rising atmospheric carbon dioxide concentrations. Moreover, the afforestation significantly reduced surface albedo, leading to a positive radiative forcing and a warming effect on the climate. The GGP also led to a significant decline in daytime land surface temperature and exerted a cooling effect on the climate. The GGP therefore has significant biophysical consequences by altering carbon cycling, hydrologic processes, and surface energy exchange and has significant feedbacks to the regional climate. The net radiative forcing on the climate depends on the offsetting of the negative forcing from carbon sequestration and higher evapotranspiration and the positive forcing from lower albedo.

Evaluation of continental carbon cycle simulations with North American flux tower observations

Terrestrial biosphere models can help identify physical processes that control carbon dynamics, including land-atmosphere CO2 fluxes, and have great potential to predict the terrestrial ecosystem response to changing climate. The skill of models that provide continental-scale carbon flux estimates, however, remains largely untested. This paper evaluates the performance of continental-scale flux estimates from 17 models against observations from 36 North American flux towers. Fluxes extracted from regional model simulations were compared with co-located flux tower observations at monthly and annual time increments. Site-level model simulations were used to help interpret sources of the mismatch between the regional simulations and site-based observations. On average, the regional model runs overestimated the annual gross primary productivity (5%) and total respiration (15%), and they significantly underestimated the annual net carbon uptake (64%) during the time period 2000- 2005. Comparison with site-level simulations implicated choices specific to regional model simulations as contributors to the gross flux biases, but not the net carbon uptake bias. The models performed the best at simulating carbon exchange at deciduous broadleaf sites, likely because a number of models used prescribed phenology to simulate seasonal fluxes. The models did not perform as well for crop, grass, and evergreen sites. The regional models matched the observations most closely in terms of seasonal correlation and seasonal magnitude of variation, but they have very little skill at interannual correlation and minimal skill at interannual magnitude of variability. The comparison of site vs. regional-level model runs demonstrated that (1) the interannual correlation is higher for site-level model runs, but the skill remains low; and (2) the underestimation of year-to-year variability for all fluxes is an inherent weakness of the models. The best-performing regional models that did not use flux tower calibration were CLM-CN, CASA-GFEDv2, and SIB3.1. Two flux tower calibrated, empirical models, EC-MOD and MOD17þ, performed as well as the best process-based models. This suggests that (1) empirical, calibrated models can perform as well as complex, process-based models and (2) combining process- based model structure with relevant constraining data could significantly improve model performance.