Spatial pattern information of forest biomass carbon (FBC) density in forest ecosystems plays an important role in evaluating carbon sequestration potentials and forest management. The spatial variation of FBC density in a subtropical region of southeastern China was studied using geostatistics combined with Moran’s I and geographical information systems (GIS). Forest biomass carbon density values were variable, ranging from 0.12 Mg ha⁻¹ to 182.12 Mg ha⁻¹, with an average of 27.33 Mg ha⁻¹. The FBC density had the strongest positive correlation with forest age, followed by forest litter and elevation. The FBC density had significant positive spatial autocorrelation revealed by global Moran’s I. Clear spatial patterns were observed based on local Moran’s I. High FBC density values were mainly distributed in the northwestern and southwestern parts of Zhejiang province, which were related to adopting long-term policy of forest conservation in these areas, while low FBC density values located in the middle part and southeastern coastal area of the study area due to low forest coverage and intensive management of economic forests. The Moran’s I combined with geostatistical interpolation proved to be a useful tool for studying spatial variation of FBC density.

Hickory plantations play an important role in improving local farmers’ economic conditions, but extreme drought in July–August 2013 seriously influenced hickory nut production. It is necessary to understand the extent and magnitude of this drought-induced hickory disturbance through mapping its spatial distribution using remote sensing data. This paper proposes a new approach to examine hickory disturbance based on multitemporal Landsat imagery. Ratios of green vegetation to soil fractions were calculated, in which the green vegetation and soil fractions were extracted from Landsat multispectral imagery using the linear spectral mixture analysis approach. We used the differences between before-drought and after-drought ratios to detect hickory disturbances. Four disturbance levels—non-disturbance, light, medium, and severe—were grouped according to the field survey data. The spatial distribution of these four levels was developed using the ratio-based approach. The result indicates that this approach is effective to detect drought-induced hickory disturbance and may be transferred to detect other kinds of disturbances, such as forest disease and selective logging. Cautions should be taken to properly select image acquisition dates and the change detection period, in addition to the approach itself.

Both leaf area (LA) and leaf angle distribution are the most important eco-physiological measures of tree crowns. However, there are limited published investigations on the two parameters of Moso bamboo (Phyllostachys edulis (Carrière) J. Houz., abbreviated as MB). The aim of this study was to develop allometric equations for predicting crown LA of MB by taking the diameter at breast height (DBH) and tree height (H) as predictors and to investigate the leaf angle distribution of a MB crown based on direct leaf angle measurements. Data were destructively sampled from 29 MB crowns including DBH, H, biomass and the area of sampled leaves, biomass of total crown leaves, and leaf angles. The results indicate that (1) the specific leaf area (SLA) of a MB crown decreases from the bottom to the top; (2) the vertical LA distribution of MB crowns follow a “Muffin top” shape; (3) the LA of MB crowns show large variations, from 7.42 to 74.38 m²; (4) both DBH and H are good predictors in allometry-based LA estimations for a MB crown; (5) linear, exponential, and logarithmic regressions show similar capabilities for the LA estimations; (6) leaf angle distributions from the top to the bottom of a MB crown can be considered as invariant; and (7) the leaf angle distribution of a MB crown is close to the planophile case. The results provide an important tool to estimate the LA of MB on the standing scale based on DBH or H measurements, provide useful prior knowledge for extracting leaf area indexes of MB canopies from remote sensing-based observations, and, therefore, will potentially serve as a crucial reference for calculating carbon balances and other ecological studies of MB forests.