Tree Density Index Research Articles

Paleobiogeoclimatic reconstruction of the Monte Cristo cave, Minas Gerais, Brazil, through phytolith analysis

This study aims to contribute to the understanding of possible paleoclimatic variations during the Quaternary in the Serra do Espinhaço Mountain Range, Minas Gerais, Brazil, based on phytolith analysis. Two soil profiles were collected from the Monte Cristo cave, which is formed in quartzite, the first being an Organosol outside the cave and the second consisting of mostly sandy material from inside the cave, in layers varying between light and dark tones. The results showed that both profiles present a high stock of phytoliths. The phytoliths are well preserved, with a predominance of Spheroid echinate and Spheroid ornate morphotypes, in addition to the presence of Bulliform flabellate, Cross, Bilobate, Rondel, and Trapezoid. The tree density index (D/P) is between 0.19 and 0.36, indicating open vegetation. The values of the Bi% index (32.8–53%) indicate moderate water stress, which is similar to previous studies in nearby regions. The Ic (climatic) index showed variations in plant adaptation at lower temperatures, with a predominance of C3 grasses, while the Pa/P index (palm tree density) indicated the presence of palm trees along both profiles. The ages obtained using 14C-AMS in the Organosol were from 4440/4230 to 2740/2430 years cal BP, and the ages of the sandy material inside the cave were from 1000/920 to 660/550 years cal BP. The phytoliths found inside the cave may be an indication that this material has an allochthonous origin, probably transported by flooding in periods under different hydrogeomorphological conditions, which is one of the hypotheses that will continue to be investigated. The vegetation type remained stable during the analyzed period, being characteristic of rupestrian fields with the presence of trees in more humid environments.

Relative contributions of competition, stand structure, age, and climate factors to tree mortality of Chinese fir plantations: Long-term spacing trials in southern China

Tree mortality is an important process during forest succession, influencing forest structure, composition, and ecosystem services. Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.), a native and fast growing species with high quality timber, is widely planted in southern China. Yet the mechanisms leading to tree mortality of Chinese fir plantations under climate change conditions is still not clearly understood. A long-term spacing trial including 60 permanent plots located in Fujian, Jiangxi, Guangxi, and Sichuan provinces in southern China were used to explore tree mortality in relation to competition, age, structural diversity, and climatic variables using a logistic mixed effects model. Results showed that tree mortality increased with increasing LnN (natural logarithm of number of trees per ha), tree density index (TN), Gini coefficient, age (A), LnAP (natural logarithm of annual precipitation), and mean warmest month temperature, and decreased with increasing relative density (RD), inverse of diameter (1/D), and mean annual temperature. The relative contributions of competition, age and structure variables to mortality were 88.82%, much larger than climate variables 11.18%. In addition, in view of the contributions of stand factors, competition indices including RD, LnN, TN were 50.57%, much larger than age (A, 1/D) contribution of 37.45%, and structural diversity contribution of 0.80%, which indicated that competition was the main driver of tree mortality. Our findings highlight the mechanisms of tree mortality of Chinese fir in southern China under climate change.

Effects of competition, age and climate on tree slenderness of Chinese fir plantations in southern China

Tree slenderness coefficient (TSC) is an important measure of tree stability. Generally, trees with higher TSC values are prone to snow, icing, and wind damage than trees with smaller TSC values. Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) a native and fast growing species, is widely distributed in southern China. Yet our understanding of how TSC of Chinese fir plantations is affected by biotic (including size, competition, and age) and climatic variables in different sites is limited. A data set of 60 remeasured plots consisted of five spacing trials and distributed in in Fujian, Jiangxi, Guangxi, and Sichuan provinces in southern China were used to explore TSC of Chinese fir relating to biotic and climatic variables using nonlinear mixed effects model (NLME). Results showed that TSC values increased with increasing stand age (Age), stand basal area (BA), and mean annual temperature (MAT). In contrast, it decreased with increasing tree density index (TN), relative diameter (RD = DBH/quadratic mean diameter), mean warmest month temperature (MWMT), and annual heat-moisture index (AHM). The relative importance of RD influencing TSC was the most followed by Age, Spacing A, TN, Spacing D, MAT, BA, Spacing C, Spacing B, AHM, and MWMT through hierarchical partitioning analysis. MAT was the most important climate factor that contributed to TSC variations, followed by AHM, and MWMT, which indicated that temperature was a critical climate variable modulating TSC of Chinese fir in southern China. Additionally, trees grown in less dense stands of 1667, 3333, and 5000 trees ha−1 were more stable (lower TSC) than those grown in dense stands of 6667 and 10 000 trees ha−1. In a word, TSC variance explained by biotic variables was 59% much larger than climate variables 2.8%. Our results will help with further assessments of tree/stand stability of Chinese fir plantations under climate change.

Designing a field sampling plan for landscape-pest ecological studies using VHR optical imagery

The objective of this study was to develop an easily replicable sampling methodology using very high spatial resolution (VHSR) optical imagery to study the effect of landscape composition on crop pest incidence and biological control. The methodology was developed for the millet head miner (MHM), Heliocheilus albipunctella (de Joannis) (Lepidoptera: Noctuidae), a key pest of millet in Senegal (West Africa). The sampling plan was developed according to two main hypotheses: (i) pest incidence increases with millet abundance in the landscape, and (ii) biological control increases with the abundance of semi-natural habitats in the landscape. VHSR satellite imagery (<1 m) provided from a Pléiades sensor was used to map and to quantify the landscape elements. Covering a square region of 20 × 20 km, a hierarchical, broad-scale land cover map focusing on crop (millet and peanut crops) and tree (tree vegetation) categories was produced and validated with ground truth data. Then, the landscape variables (tree density index and millet crop density index) were calculated based on a regular grid of 100 ha for each cell size covering the study area; the variables were then split into three density classes (low-medium-high) representative of the full landscape heterogeneity and combined into nine landscape patterns. Finally, according to sampling capacity, track accessibility, and statistical constraints, 45 field sites, including five replicates for each landscape pattern, were validated and selected for pest monitoring.