Divergent spatio-temporal tree growth trends in Pinus pinaster Ait. in South-Western European forests.

Climate change influences forest ecosystems in several ways, such as modifying forest growth or ecosystem functionality. To fully understand the impact of changing climatic conditions on forest growth it is necessary to undertake long-term spatiotemporal analyses. The main purpose of this work is to describe the major trends in tree growth of Pinus pinaster in Spain over the last 70 years, differentiating homogeneous ecological units using an unsupervised classification algorithm and additive modelling techniques. We also aim to relate these growth trends with temporal series for precipitation and temperature, as well as forest variables. We leverage information from a large data set of tree cores (around 2200) extracted during the field campaign of the Fourth Spanish National Forest Inventory. An unsupervised algorithm classified the plots into five classes, which were consistent in ecological terms. We also found a general decline in growth in three of the five ecoregions since the 1970s, concomitant with an increase in temperature and a reduction in precipitation. However, this tree growth decline has not been observed in the Atlantic influenced ecoregion, where the cooler, more humid climatic conditions are more stable. Certain stand features, such as low basal area through forest management practices, may have alleviated the impact of harsh climatic conditions on some areas of inner Spain, while denser stands display a more pronounced decline in tree growth. We concluded that Southern populations show some degrees of growth decline and low growth trends while Northern populations did not exhibit growth decline and have the largest growth rates. Under a forecasted increment of temperatures, the growth decline can be expanded.

Using spectral indices as early warning signals of forest dieback: The case of drought-prone Pinus pinaster forests.

Forest dieback processes linked to drought are expected to increase due to climate warming. Remotely sensed data offer several advantages over common field monitoring methods such as the ability to observe large areas on a systematic basis and monitoring their changes, making them increasingly used to assess changes in forest health. Here we aim to use a combined approximation of fieldwork and remote sensing to explore possible links between forest dieback and land surface phenological and trend variables derived from long Landsat time series. Forest dieback was evaluated in the field over 31 plots in a Mediterranean, xeric Pinus pinaster forest. Landsat 31-year time series of three greenness (EVI, NDVI, SAVI) and two wetness spectral indices (NMDI and TCW) were derived covering the period 1990-2020. Spectral indices from time series were decomposed into trend and seasonality using a Bayesian estimator while the relationships of the phenological and trend variables among levels of damage were assessed using linear and additive mixed models. We have not found any statistical pieces of evidence of extension or shortening patterns for the length of the phenological season over the examined 31-year period. Our results indicate that the dieback process was mainly related to the trend component of the spectral indices series whereas the phenological metrics were not related to forest dieback. We also found that plots with more dying or damaged trees displayed lower spectral indices trends after a severe drought event in the middle of the 1990s, which confirms the Landsat-derived spectral indices as indicators of early-warning signals. Drops in trends occurred earlier for wetness indices rather than for greenness indices which suggests that the former could be more appropriate for dieback detection, i.e. they could be used as early warning signals of impending loss of tree vigor.

Deadwood stocks in south-western European forests: Ecological patterns and large scale assessments.

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.

Towards complete and harmonized assessment of soil carbon stocks and balance in forests: The ability of the Yasso07 model across a wide gradient of climatic and forest conditions in Europe.

Accurate carbon-balance accounting in forest soils is necessary for the development of climate change policy. However, changes in soil organic carbon (SOC) occur slowly and these changes may not be captured through repeated soil inventories. Simulation models may be used as alternatives to SOC measurement. The Yasso07 model presents a suitable alternative because most of the data required for the application are readily available in countries with common forest surveys. In this study, we test the suitability of Yasso07 for simulating SOC stocks and stock changes in a variety of European forests affected by different climatic, land use and forest management conditions and we address country-specific cases with differing resources and data availability. The simulated SOC stocks differed only slightly from measured data, providing realistic, reasonable mean SOC estimations per region or forest type. The change in the soil carbon pool over time, which is the target parameter for SOC reporting, was generally found to be plausible although not in the case of Mediterranean forest soils. As expected under stable forest management conditions, both land cover and climate play major roles in determining the SOC stock in forest soils. Greater mean SOC stocks were observed in northern latitudes (or at higher altitude) than in southern latitudes (or plains) and conifer forests were found to store a notably higher amount of SOC than broadleaf forests. Furthermore, as regards change in SOC, an inter-annual sink effect was identified for most of the European forest types studied. Our findings corroborate the suitability of Yasso07 to assess the impact of forest management and land use change on the SOC balance of forests soils, as well as to accurately simulate SOC in dead organic matter (DOM) and mineral soil pools separately. The obstacles encountered when applying the Yasso07 model reflect a lack of available input data. Future research should focus on improving our knowledge of C inputs from compartments such as shrubs, herbs, coarse woody debris and fine roots. This should include turnover rates and quality of the litter in all forest compartments from a wider variety of tree species and sites. Despite the limitations identified, the SOC balance estimations provided by the Yasso07 model are sufficiently complete, accurate and transparent to make it suitable for reporting purposes such as those required under the UNFCCC (United Nations Framework Convention on Climate Change) and KP (Kyoto Protocol) for a wide range of forest conditions in Europe.