Influence of sampling intensity on performance of two-phase forest inventory using airborne laser scanning

Background: Forest inventories have always been a primary information source concerning the forest ecosystem state. Various applied survey approaches arise from the numerous important factors during sampling scheme planning. Paramount aspects include the survey goal and scale, target population inherent variation and patterns,and available resources. The last factor commonly inhibits the goal, and compromises have to be made. Airborne laser scanning(ALS) has been intensively tested as a cost-effective option for forest inventories. Despite existing foundations, research has provided disparate results. Environmental conditions are one of the factors greatly influencing inventory performance. Therefore, a need for site-related sampling optimization is well founded.Moreover, as stands are the basic operational unit of managed forest holdings, few related studies have presented stand-level results. As such, herein, we tested the sampling intensity influence on the performance of the ALSenhanced stand-level inventory.Results: Distributions of possible errors were plotted by comparing ALS model estimates, with reference values derived from field surveys of 3300 sample plots and more than 300 control stands located in 5 forest districts. No improvement in results was observed due to the scanning density. The variance in obtained errors stabilized in the interval of 200–300 sample plots, maintaining the bias within +/-5% and the precision above 80%. The sample plot area affected scores mostly when transitioning from 100 to 200 m2. Only a slight gain was observed when bigger plots were used.Conclusions: ALS-enhanced inventories effectively address the demand for comprehensive and detailed information on the structure of single stands over vast areas. Knowledge of the relation between the sampling intensity and accuracy of ALS estimates allows the determination of certain sampling intensity thresholds. This should be useful when matching the required sample size and accuracy with available resources. Site optimization may be necessary, as certain errors may occur due to the sampling scheme, estimator type or forest site, making these factors worth further consideration.

Stand structure and species diversity regulate biomass carbon stock under major Central Himalayan forest types of India

Background:Data on the impact of species diversity on biomass in the Central Himalayas,along with stand structural attributes is sparse and inconsistent.Moreover,few studies in the region have related population structure and the influence of large trees on biomass.Such data is crucial for maintaining Himalayan biodiversity and carbon stock.Therefore,we investigated these relationships in major Central Himalayan forest types using nondestructive methodologies to determine key factors and underlying mechanisms.Results:Tropical Shorea robusta dominant forest has the highest total biomass density(1280.79 Mg ha^(−1))and total carbon density(577.77 Mg C ha^(−1))along with the highest total species richness(21 species).The stem density ranged between 153 and 457 trees ha^(−1) with large trees(>70 cm diameter)contributing 0–22%.Conifer dominant forest types had higher median diameter and Cedrus deodara forest had the highest growing stock(718.87 m^(3) ha^(−1));furthermore,C.deodara contributed maximally toward total carbon density(14.6%)among all the 53 species combined.Quercus semecarpifolia–Rhododendron arboreum association forest had the highest total basal area(94.75 m^(2) ha^(−1)).We found large trees to contribute up to 65%of the growing stock.Nine percent of the species contributed more than 50%of the carbon stock.Species dominance regulated the growing stock significantly(R^(2)=0.707,p<0.001).Temperate forest types had heterogeneous biomass distribution within the forest stands.We found total basal area,large tree density,maximum diameter,species richness,and species diversity as the predominant variables with a significant positive influence on biomass carbon stock.Both structural attributes and diversity influenced the ordination of study sites under PCA analysis.Elevation showed no significant correlation with either biomass or species diversity components.Conclusions:The results suggest biomass hyperdominance with both selection effects and niche complementarity to play a complex mechanism in enhancing Central Himalayan biomass carbon stock.Major climax forests are in an alarming state regarding future carbon security.Large trees and selective species act as key regulators of biomass stocks;however,species diversity also has a positive influence and should also reflect under management implications.