Search

• Deadwood harmonization efforts by forest type. • We used National Forest Inventory deadwood data encompassing more than 55,000 plots. • We create bridge functions to convert deadwood measurements to 7.5 and 10.0 cm. • Bridge equations validation statistics indicate that the models performed adequately. • The standing deadwood trees proportion is not a good indicator of the total deadwood. National as well as international requirements have led to an increased need to quantify deadwood stocks in forest ecosystems given their important role not only in terms of carbon storage and regulation of the carbon cycle but also as biodiversity refugia. However, differences in definitions and field monitoring as well as gaps in existing data on deadwood mean that comparisons among countries and retrospective analyses are difficult. In this research, we propose two potential approaches to solve the most common gaps in forest deadwood monitoring. First, we develop bridging functions capable of converting deadwood measurements with a specific reference diameter to 7.5 cm (minimum diameter value in Spain) and 10.0 cm (the most common minimum value for international statistics) diameters for the main forest types while also addressing the effect of raising the minimum measurable size on the quantification of deadwood. Furthermore, we aim to calculate the ratios between the amount of standing deadwood, the most common indicator monitored in National Forest Inventories, and the entire deadwood pool as a proxy for estimating complete deadwood stocks when data are not available. For this objective, we use information obtained from the Spanish National Forest Inventory, linear models and 10-fold cross-validation. We estimate the percentage of deadwood omitted when the minimum deadwood size is increased for the main eight forest types in Spain as well as for the entire country, using two different approaches. The ratio between the amount of standing deadwood and the entire deadwood pool ranged between 0.14 and 0.45 depending on the forest type. The lowest values of this ratio were found in Open woodlands and the largest in Mediterranean conifers. The validation statistics (R2 ranging from 0.82 in Evergreen broadleaves to 0.97 in Macaronesian broadleaves) indicate that the bridging functions we propose are robust and accurate. However, the ratios between the amount of standing deadwood and the entire deadwood pool performed poorer (R2 ranging from 0.26 in Macaronesian conifers to 0.65 in Macaronesian broadleaves) and led to an overestimation of the total stocks. Our results are of value not only for the purposes of comparison and harmonization but also for the implementation of new forest monitoring systems. [ABSTRACT FROM AUTHOR]

Forest transitions (FT) occur when socioeconomic development leads to a shift from net deforestation to reforestation; these dynamics have been observed in multiple countries across the globe, including the island of Puerto Rico in the Caribbean. Starting in the 1950s, Puerto Rico transitioned from an agrarian to a manufacturing and service economy reliant on food imports, leading to extensive reforestation. In recent years, however, net reforestation has leveled off. Here we examine the drivers of forest transition in Puerto Rico from 1977 to 2000 at two subnational, nested spatial scales (municipality and barrio) and over two time periods (1977-1991 and 1991-2000). This study builds on previous work by considering the social and biophysical factors that influence both reforestation and deforestation at multiple spatial and temporal scales. By doing so within one analysis, this study offers a comprehensive understanding of the relative importance of various social and biophysical factors for forest transitions and the scales at which they are manifest. Biophysical factors considered in these analyses included slope, soil quality, and land-cover in the surrounding landscape. We also considered per capita income, population density, and the extent of protected areas as potential factors associated with forest change. Our results show that, in the 1977-1991 period, biophysical factors that exhibit variation at municipality scales (~100 km²) were more important predictors of forest change than socioeconomic factors. In this period, forest dynamics were driven primarily by abandonment of less productive, steep agricultural land in the western, central part of the island. These factors had less predictive power at the smaller barrio scale (~10 km²) relative to the larger municipality scale during this time period. The relative importance of socioeconomic variables for deforestation, however, increased over time as development pressures on available land increased. From 1991-2000, changes in forest cover reflected influences from multiple factors, including increasing population densities, land development pressure from suburbanization, and the presence of protected areas. In contrast to the 1977-1991 period, drivers of deforestation and reforestation over this second interval were similar for the two spatial scales of analyses. Generally, our results suggest that although broader socioeconomic changes in a given region may drive the demand for land, biophysical factors ultimately mediate where development occurs. Although economic development may initially result in reforestation due to rural to urban migration and the abandonment of agricultural lands, increased economic development may lead to deforestation through increased suburbanization pressures. [ABSTRACT FROM AUTHOR]

Forest deadwood is a relevant factor in the provision of ecosystem services (forest biodiversity, carbon sequestration, recreational and aesthetic values), but it also influences the risk and impact of forest perturbations. Hence, reliable estimations are urgently need in the lack of detailed information in Mediterranean forests at large scales. In this study we provide, for the first time, national-level estimations for Spain based on the information from the Spanish National Forest Inventory (38,945 plots). In addition, we compare and validate two approaches for estimating deadwood stocks where data is lacking; the first of these being a modelling approach based on stand, climatic and physiographical variables, and the other considers the ratio between deadwood and living biomass. We also examine the different patterns stock across forest types in four biogeographical regions according to a broad-spectrum of species groups and forests with different degrees of anthropogenic influence. The degrees are based on levels of protection and naturalness categories. The modelling approach provides more robust deadwood estimates and better predictive capacity than the ratio approach. Alpine (6.09 Mg.ha−1) and Atlantic (3.53 Mg.ha−1) bioregion forests store significantly higher mean deadwood biomass stocks than Macaronesian and Mediterranean forests. However, the share of deadwood in relation to the total biomass stock is greater in Mediterranean biogeographical region. As regards species groups, the mean deadwood stock of mixed forests doubled the stocks found in conifer and broadleaved dominated forests. We also found significant differences in deadwood biomass stocks between forests with different levels of anthropogenic protection. However, forest types with intensive forest management had contrasting figures for deadwood stock. The mean values obtained at national level according to forest type, bioregion and degree of anthropogenic influence, provide baseline information for carbon accounting as well as for other forest policy planning and management strategies. Unlabelled Image • Alpine and Atlantic forests stored higher DW biomass (6.09 and 3.53 Mg ha-1) than Macaronesian and Mediterranean forests • DW biomass in mixed forests (2.92 Mg ha-1) is double the stock found in conifer and broadleaved forests • Lying and standing adult-tree DW stocks account for 72% of the total DW volume • Deadwood stocks (DW) and the percentage of DW to total stocks exhibit opposite trends • GAM displays more robust and accurate estimates than the DW-living biomass ratio approach [ABSTRACT FROM AUTHOR]