Hongcheng Zeng

Hurricane Katrina's Carbon Footprint on U.S. Gulf Coast Forests

Hurricane Katrinas impact on U.S. Gulf Coast forests was quantified by linking ecological field studies, Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) image analyses, and empirically based models. Within areas affected by relatively constant wind speed, tree mortality and damage exhibited strong species-controlled gradients. Spatially explicit forest disturbance maps coupled with extrapolation models predicted mortality and severe structural damage to ~320 million large trees totaling 105 teragrams of carbon, representing 50 to 140% of the net annual U.S. forest tree carbon sink. Changes in disturbance regimes from increased storm activity expected under a warming climate will reduce forest biomass stocks, increase ecosystem respiration, and may represent an important positive feedback mechanism to elevated atmospheric carbon dioxide.

Impacts of tropical cyclones on U.S. forest tree mortality and carbon flux from 1851 to 2000

Tropical cyclones cause extensive tree mortality and damage to forested ecosystems. A number of patterns in tropical cyclone frequency and intensity have been identified. There exist, however, few studies on the dynamic impacts of historical tropical cyclones at a continental scale. Here, we synthesized field measurements, satellite image analyses, and empirical models to evaluate forest and carbon cycle impacts for historical tropical cyclones from 1851 to 2000 over the continental U.S. Results demonstrated an average of 97 million trees affected each year over the entire United States, with a 53-Tg annual biomass loss, and an average carbon release of 25 Tg y−1. Over the period 1980–1990, released CO2 potentially offset the carbon sink in forest trees by 9–18% over the entire United States. U.S. forests also experienced twice the impact before 1900 than after 1900 because of more active tropical cyclones and a larger extent of forested areas. Forest impacts were primarily located in Gulf Coast areas, particularly southern Texas and Louisiana and south Florida, while significant impacts also occurred in eastern North Carolina. Results serve as an important baseline for evaluating how potential future changes in hurricane frequency and intensity will impact forest tree mortality and carbon balance.

A GIS-based decision support system for risk assessment of wind damage in forest management

In this study a GIS-based decision support system (DSS) was built for assessing the short- and long-term risk of wind damage in boreal forests. This was done by integrating a forest growth model SIMA and a mechanistic wind damage model HWIND into geographical information system software (ArcGIS 8.2) as a toolbar (DLL) using ArcObjects in ArcGIS and Visual Basic 6. In this DSS complex problems are solved within program so that forest gaps, edge stands and edges are automatically tracked when the forest structure changes over time as a result of forest growth dynamics and management. This DSS can be used to assess the risk of wind damage to Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and birch (Betula spp.) stands, regarding the number of stands and area at risk and length of vulnerable edges of these risk stands at certain critical wind speed classes (i.e. corresponding the maximum wind speed a tree/stand can resist). This DSS can helps forest managers to analyse and visualise (charts, maps) the possible effects of forest management, such as clear-cuts, on both the immediate and long-term risks of wind damage at both stand and regional level.

The effects of forest structure on the risk of wind damage at a landscape level in a boreal forest ecosystem

Abstract• The aim of this work was to analyze how the forest structure affects the risk of wind damage at the landscape level in a boreal forest.• This was done by employing: (i) Monte Carlo simulation technique for generating landscapes with different age class distributions, proportions of open areas (gaps), and tree species composition; and (ii) a mechanistic wind damage model, HWIND, for predicting the critical wind speeds at downwind stand edges of open areas (gaps) for risk consideration. The level of risk of wind damage observed at the landscape level was significantly affected by the presence of gaps and old stands. Even a slight increase in the proportion of gap areas or older stands had a significant impact on the total length of edges at risk. As a comparison, variation in species composition (Scots pine and/or Norway spruce) had much smaller impact on the risk of damage.• In conclusion, the effects of forest structure on the risk of wind damage should especially be considered by forest managers in day-to-day forest planning in order to reduce the risk of wind damage both at the stand and landscape level.Résumé• L’objectif de ce travail était d’analyser comment la structure forestière affecte le risque de dommages causés par le vent à l’échelle du paysage dans une forêt boréale.• C’est objectif a été atteint par l’emploi : (i) de la technique de simulation de Monte Carlo pour générer des paysages de différentes distributions de classe d’âge, de proportions des zones ouvertes (trouées), et de composition des espèces d’arbres ; et (ii) d’un modèle mécaniste de dommages causés par le vent, HWIND, pour la prédiction des vitesses de vent critiques au niveau des lisières sous le vent des zones ouvertes (trouées) en relation avec les risques. Le niveau de risque de dommages causés par le vent observé à l’échelle du paysage a été significativement affecté par la présence de trouées et de vieux peuplements. Une augmentation même légère dans la proportion de trouées ou de vieux peuplements a eu un impact significatif sur la longueur totale des lisières à risque. À titre de comparaison, la variation dans la composition des espèces (pin sylvestre et/ou épicéa) a eu beaucoup moins d’impact sur le risque de dommages.• En conclusion, les effets de la structure de la forêt sur le risque de dommages causés par le vent devraient être examinées en particulier par les gestionnaires forestiers pour une planification des opérations forestière au jour le jour, afin de réduire le risque de dommages causés par le vent à la fois au niveau du peuplement et au niveau du paysage.

Using GIS to quantify mountains in China

Studying the natural resources, environment, and socioeconomic development of Chinas mountain areas is difficult without a clear quantification of those mountains. Quantification is also essential for developing digital mountains. Using GIS and the digital elevation model, this research effort quantified and classified Chinas mountains according to domestic and international criteria.

Assessing earthquake-induced tree mortality in temperate forest ecosystems: A case study from wenchuan, china

Earthquakes can produce significant tree mortality, and consequently affect regional carbon dynamics. Unfortunately, detailed studies quantifying the influence of earthquake on forest mortality are currently rare. The committed forest biomass carbon loss associated with the 2008 Wenchuan earthquake in China is assessed by a synthetic approach in this study that integrated field investigation, remote sensing analysis, empirical models and Monte Carlo simulation. The newly developed approach significantly improved the forest disturbance evaluation by quantitatively defining the earthquake impact boundary and detailed field survey to validate the mortality models. Based on our approach, a total biomass carbon of 10.9 Tg∙C was lost in Wenchuan earthquake, which offset 0.23% of the living biomass carbon stock in Chinese forests. Tree mortality was highly clustered at epicenter, and declined rapidly with distance away from the fault zone. It is suggested that earthquakes represent a significant driver to forest carbon dynamics, and the earthquake-induced biomass carbon loss should be included in estimating forest carbon budgets.

The quantification of mountains in China Based on Geographic Information System

Two criteria are chosen to determine the boundaries of mountains in China. One is the domestic criterion (DC) in China; the other is an international criterion (IC). According to the DC, there are 4 000 265 km2 mountain areas; while according to the IC, there are 4 426 130 km2 mountain areas. The mountains are classified into six categories: C1.300～1 000 m;C2.1 000～1 500 m;C3.1 500～2 500 m;C4.2 500～3 500 m;C5.3 500～4 500 m;C6.≥4 500 m. The areas of mountains in the two criteria over 3 500 m are equal (C5 & C6). Except the area of C1 in DC is larger than international criterion (the value is 324 508 km2), the areas of C2, C3 and C4 in IC are larger than DC (the values are 2 273 km2, 336 186 km2 and 133 432 km2, separately).

E-mountains and progress of digital mountains

Human being has experienced five stages on the mountainous study, in which the form of mountain information presented like a cycle, i.e. starts from data, and changed to information, knowledge, finally returned back to data. Similarly, attribute of mountain information also experienced a cycle of objective information-subjective information-objective information. There is no essential difference between e-mountains and digital mountains. Based on the analyzing of the progression of e-mountains studies in China and abroad, this work proposed three key points to build digital mountains (China): 1) integration and sharing mountain information; 2) methods and models of mountain data mining; 3) visualization and 3-D simulation of mountain surface processes.