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Reliable assessment of forest structural types (FSTs) aids sustainable forest management. We developed a methodology for the identification of FSTs using airborne laser scanning (ALS), and demonstrate its generality by applying it to forests from Boreal, Mediterranean and Atlantic biogeographical regions. First, hierarchal clustering analysis (HCA) was applied and clusters (FSTs) were determined in coniferous and deciduous forests using four forest structural variables obtained from forest inventory data – quadratic mean diameter (QMD), Gini coefficient (GC), basal area larger than mean (BALM) and density of stems (N) –. Then, classification and regression tree analysis (CART) were used to extract the empirical threshold values for discriminating those clusters. Based on the classification trees, GC and BALM were the most important variables in the identification of FSTs. Lower, medium and high values of GC and BALM characterize single storey FSTs, multi-layered FSTs and exponentially decreasing size distributions (reversed J), respectively. Within each of these main FST groups, we also identified young/mature and sparse/dense subtypes using QMD and N. Then we used similar structural predictors derived from ALS – maximum height (Max), L-coefficient of variation (Lcv), L-skewness (Lskew), and percentage of penetration (cover), – and a nearest neighbour method to predict the FSTs. We obtained a greater overall accuracy in deciduous forest (0.87) as compared to the coniferous forest (0.72). Our methodology proves the usefulness of ALS data for structural heterogeneity assessment of forests across biogeographical regions. Our simple two-tier approach to FST classification paves the way toward transnational assessments of forest structure across bioregions.

Accurate estimations of carbon stocks across large tracts of tropical forests are key for participation in programs promoting avoided deforestation and carbon sequestration, such as the UN REDD+ framework. Trained local technicians can provide such data, and this, combined with satellite imagery, allows robust carbon stock estimation across vegetation classes and large areas. In the first comprehensive survey in Guyana conducted by indigenous people, ground data from 21 study sites in the Rupununi region were used to estimate above ground tree carbon density across a diversity of ecosystems and land use types. Carbon stocks varied between village sites from 1Tg to 22.7Tg, and these amounts were related to stem density and diameter. This variation was correlated with vegetation type across the region, with savannas holding on average 14MgCha-1 and forests 153MgCha-1. The results indicated that previous estimates based on remotely sensed data for this area may be inaccurate (under estimations). There were also differences in carbon densities between village sites and uninhabited control areas, which are presumably driven by community use. Recruiting local technicians for field work allowed (a) large amounts of ground data to be collected for a wide region otherwise hard to access, and (b) ensured that local people were directly involved in Guyana's Low Carbon Development Strategy as part of REDD+. This is the first such comprehensive survey of carbon stocks, carbon density and vegetation types over a large area in Guyana, one of the first countries to develop such a program. The potential inclusion of forests held by indigenous peoples in REDD+ programs is a global issue: we clearly show that indigenous people are capable of assessing and monitoring carbon on their lands.

The structure of forest canopies correlates with stand maturity and biomass, and develops consistently over time. Remote-sensing technologies such as Light Detection and Ranging (LiDAR) have become prominent tools for measuring structural characteristics of forests.We walked a portable canopy LiDAR (PCL), an up-facing rangefinder that detects vegetation through the canopy at two kilohertz, along multiple transects at ten different forest stands in the area of Wytham Woods, Oxfordshire, UK. The stands had different species composition, were situated at forest edges and in forest core, were in fragments of different sizes and had different land-use histories. With these data we tested structural differences in vegetation across these stand types.Although none of the stands have been managed in the last 70. years, they have not converged structurally. Vertical canopy structure differed between stands that regrew naturally from open field and those with a history of coppice management. Forest stands that have developed following major fellings or through spread on to former grazing land showed some structural similarities to classic natural succession from large disturbances. Stands that were actively managed as coppice over preceding centuries, showed a similar structural pattern to mature forest, but without the tall overstorey that can develop into old growth communities.This structural divergence indicates two distinct pathways for secondary forests: with implications for the future biomass, stand structure, and species composition. The legacy of management practices can determine canopy structure decades after the forest is removed from active management, but can also be difficult to discern with remote sensing data. We recommend that "ground-truthing" remote sensing data go beyond traditional checks of height and topography, as the history and composition of secondary forests can have an important influence on the pace and compositional structure of recovery from management.

Three years of monthly growth increment data identified large interannual differences in growth rate across six contrasting species in a broadleaved, temperate forest with minimum management intervention (Wytham Woods, UK). Growth rates varied by species and canopy position, and were higher in canopy species. Growth rate in 2010 was up to 40% lower than in 2011 and 2012. This can best be explained as an effect of low temperature, which delayed the start of spring and the growing season. This had a greater impact on the growth of sub-canopy trees than that of canopy species. In temperate systems, late spring and summer is an important component of the whole growing season carbon balance because of long day length. In 2010 there were also periods of lower-than-average rainfall, which may additionally have constrained growth during the growing season. Fluctuations and seasonal changes in both temperature and rainfall are projected to continue, so we may expect to see increasing differences in growth and growth rates. A small effect of location relative to the nearest edge was also detected, with higher growth rates only found >50 m from the forest edge. The findings have implications for forest structure and productivity under climate change, and may thus inform current and future forest management.