Key message
By combining inventory data and spatially-continuous environmental information, we were able to develop models for Atlantic populations of maritime pine (
Pinus pinaster
Aiton) in Spain ...in order to predict suitable habitat and site index at a spatial resolution of 250 × 250 m.
Context
Currently available, spatially continuous environmental information was used to make reliable predictions about suitable habitat and forest productivity.
Aims
To develop raster-based distribution and productivity models for Atlantic populations of maritime pine in Spain to predict current and future suitable habitat and productivity.
Methods
Occurrence data and site index values were obtained from the Third Spanish National Forest Inventory and research plots, respectively. After testing different algorithms, random forest were selected for modelling the relationships between maritime pine occurrence, site index and spatially continuous environmental variables.
Results
The overall accuracy of the suitable habitat model was 73%, and climate (mainly thermal properties) and soil physical properties were the most important variables. The site index model explained 60% of the observed variability, and lithological properties were the most important variables. A slight increase in site index (0.46–0.51%) and a large increase in suitable habitat (50–66%) are expected for 2070 under the most pessimistic climate change scenario.
Conclusion
The currently available spatial continuous information enables the development of accurate raster data models for predicting suitable habitat and site productivity without the need for fieldwork. Climate change is expected to increase the potentially suitable habitat of Atlantic maritime pine populations in Spain in the coming decades.
•The first site index curves have been developed for Cantabrian beech forests.•Beech presence is affected by climate, soil and terrain variables.•Beech productivity is related to silt content, ...temperature and terrain curvature.•Climate change may lead to a reduction in suitable habitat for beech in NW Spain.•Productivity projections indicate an increase in the average site index.
The beech forests in the Cantabrian Range occur at the southwestern limit of the distribution of the species and are very important for wildlife and biodiversity in the region. Climate change is expected to increase the frequency and severity of drought events over the next few decades in southwestern Europe, and establishing how this will alter the distribution, abundance and productivity of beech is fundamental for biodiversity conservation and management. In this study, we used spatially continuous environmental variables to develop spatial distribution and site-productivity models for beech forests in the Cantabrian Range and to project these models to different climate change scenarios. Two raster-based models of resolution 250 m were constructed to identify suitable habitat (species distribution model) and to estimate site index (productivity model) for beech in the Cantabrian Range. Of the 23 variables retained in the spatial distribution model, climate, soil and terrain were the most important (explaining respectively 51.2%, 34.2% and 10.1% of the variation). The productivity model retained only three variables (percentage of silt in soil, mean diurnal range of temperature and plan curvature of the terrain) but was able to explain 54% of the total variation. Future projections based on two emission scenarios suggest that suitable habitat will be drastically reduced by 2070 (loss of 40–90% of the area for the moderate and pessimistic scenarios, respectively). However, the projections do not imply current population removal rather it can be probably interpreted in less favorable conditions for seedling establishment, higher mortality rates and a reduction in local density of populations. Productivity projections for suitable habitat suggest a large increase in the average site index (from current 15.19 to 18.18 m) in the moderate scenario and an increase of only 34 cm in the pessimistic scenario. The study findings provide basic information for conservation biology and could be used by decision-makers to develop and implement actions for mitigating the impact of climate change on beech forests.
Aim of study: Although beech (Fagus sylvatica L.) forests in north-western Spain constitute c.a. 40% of the total area occupied by the species in the whole country, no growth or yield studies have ...been carried out regarding these forests. The specific objective of this study was to elaborate yield tables and stand density management diagrams for the beech forests.
Area of study: Asturias and León provinces (NW Spain).
Material and methods: Sample plots (n=112) were established in natural beech forests, and 60 dominant trees were felled for sampling. The Asturias Government Forest Service provided data on another 351 felled trees. Yield tables and stand density management diagrams (SDMDs) were elaborated to estimate tree volume and biomass in the study area for the first time.
Main results: These forests are more productive than expected. Although they are currently not managed for forestry purposes, they could be managed again in the future and the tools are now available for this purpose.
Research highlights: The study generates new user-friendly tools to manage beech forests in northwestern Spain. These tools will also enable simulations to be conducted to determine the potential carbon storage or the capacity of the stands to sequester atmospheric carbon.
A generalized height–diameter (
h–
d) model based on Schnute's function was developed for radiata pine (
Pinus radiata D. Don) plantations in Galicia (northwestern Spain). The study involved the ...estimation of fixed and random parameters by mixed-model techniques. The hierarchical structure of the data set, trees within plots, justifies the application of mixed-effects modelling. Techniques for calibrating the generalized height–diameter model for a particular plot of interest were also applied. For the experimental data analyzed, calibration can be used to obtain
h–
d relationships tailored to individual plots after measuring the height of only the three smallest trees in a plot. The main reason for the high predictive ability using this subsample of trees is that the dominant height of each plot was already considered as a fixed-effect in the height–diameter model formulation; therefore, heights corresponding to the largest trees did not provide much more additional information for calibrations. The model also included an unstructured random component to mimic the observed natural variability in heights within diameter classes for the same plot. This is an important aspect because the model will be applied to fill in the missing height measurements, subsequently used for assessing variables (e.g., volume, biomass, etc.) that depend on the estimated heights.
Aim of study: Agroforestry systems of Castanea sativa have specific forest structures, which are different from other ecosystems of sweet chestnut. They have provided several ecosystems services (ES) ...to local inhabitants for centuries including relevant pastoral use. However on present times, have isolated distribution ranges and declining trends. The chestnut trees are their main components but occur at low densities. They are cultivated by using different treatments to improve specific features and maximize different types of production.Area of study: North-western of Iberian Peninsula.Material and methods: We used a large database (>750 field plots) to classify C. sativa dominated-stands into different ecosystems typology (including traditional agroforestry systems), and to assess their most relevant ES. We used field data to define their spatial distribution and discriminant analysis to determine the classification accuracy. Finally we also defined a set of qualitative and quantitative ES indicators for different groups to compare different trends.Main results: We successfully classified these ecosystems and found that the traditional agroforestry systems are of major importance in providing ES, as food provision or cultural services, but showed isolated distribution patterns. Moreover, other types of chestnut-dominated ecosystems, supply important ES such as biomass provision and climate regulation.Research highlights: The relevance of the C. sativa agroforestry systems from ES point of view was pointed out in this work, but also their declining dynamic. Further analysis, based on temporal trends, could help to a better understanding of their status and to define conservation and management strategies.
The prediction of growing stock volume is one of the commonest applications of remote sensing to support the sustainable management of forest ecosystems. In this study, we used data from the 4th ...Spanish National Forest Inventory (SNFI-4) and from the 1st nationwide Airborne Laser Scanning (ALS) survey to develop predictive yield models for the three major commercial tree forest species (Eucalyptus globulus, Pinus pinaster and Pinus radiata) grown in north-western Spain. Integration of both types of data required prior harmonization because of differences in timing of data acquisition and difficulties in accurately geolocating the SNFI plots. The harmonised data from 477 E. globulus, 760 P. pinaster and 191 P. radiata plots were used to develop predictive models for total over bark volume, mean volume increment and total aboveground biomass by relating SNFI stand variables to metrics derived from the ALS data. The multiple linear regression methods and several machine learning techniques (k-nearest neighbour, random trees, random forest and the ensemble method) were compared. The study findings confirmed that multiple linear regression is outperformed by machine learning techniques. More specifically, the findings suggest that the random forest and the ensemble method slightly outperform the other techniques. The resulting stand level relative RMSEs for predicting total over bark volume, annual increase in total volume and total aboveground biomass ranged from 30.8–38.3%, 34.2–41.9% and 31.7–38.3% respectively. Although the predictions can be considered accurate, more precise geolocation of the SNFI plots and coincide temporarily with the ALS data would have enabled use of a much larger and robust field database to improve the overall accuracy of estimation.
A basal area growth system for single-species, even-aged maritime pine (Pinus pinaster Ait.) stands in Galicia (northwestern Spain) was developed from data of 212 plots measured between one and four ...times. Six dynamic equations were considered for analysis, and both numerical and graphical methods were used to compare alternative models. The double cross-validation approach was used to assess the predictive ability of the models. The data were best described by a dynamic equation derived from the Korf growth function using the generalized algebraic difference approach (GADA) by considering two parameters to be site specific. The equation was fitted in one stage using the base-age-invariant dummy variables method. In addition, the system incorporates a function for predicting initial stand basal area, in which the site-related variable was expressed as a power function of site index. This function can be used to establish the starting point for the projection equation when no inventory data are available. The two equations are compatible. The effect of thinning on basal area growth was examined; the results showed that there was no need to use a different equation to reliably predict postthinning basal area development. The nonlinear extra sum of squares method indicated differences in the model parameters for the two ecoregions (coastal and interior) defined for this species in the area of study.
In this study, we used Spanish National Forest Inventory (SNFI) data, Sentinel-2 imagery and ancillary data to develop models that estimate forest variables for major commercial timber plantations in ...northern Spain. We carried out the analysis in two stages. In the first stage, we considered plots with and without sub-meter geolocation, three pre-processing levels for the Sentinel-2 images and two machine learning algorithms. In most cases, geometrically, radiometrically, atmospherically and topographically (L2A-ATC) corrected images and the random forest algorithm provided the best results, with topographic correction producing a greater gain in model accuracy as the average slope of the plots increased. Our results did not show any clear impact of the geolocation accuracy of SNFI plots on results, suggesting that the usual geolocation accuracy of SNFI plots is adequate for developing forest models with data obtained from passive sensors. In the second stage, we used all plots together with L2A-ATC-corrected images to select five different groups of predictor variables in a cumulative process to determine the influence of each group of variables in the final RF model predictions. Yield variables produced the best fits, with R2 ranging from 0.39 to 0.46 (RMSE% ranged from 44.6% to 61.9%). Although the Sentinel-2-based estimates obtained in this research are less precise than those previously obtained with Airborne Laser Scanning (ALS) data for the same species and region, they are unbiased (Bias% was always below 1%). Therefore, accurate estimates for one hectare are expected, as they are obtained by averaging the values of 100 pixels (model resolution of 10 m pixel−1) with an expected error compensation. Moreover, the use of these models will overcome the temporal resolution problem associated with the previous ALS-based models and will enable annual updates of forest timber resource estimates to be obtained.
âKEY MESSAGE : A dynamic growth model was developed for maritime pine in Asturias. During the evaluation process, a stand volume ratio function proved the best of two alternative methods for ...estimating merchantable volume. Comparison of the developed model with existing models for nearby regions showed that a single model may suffice for the whole of the NW Iberian Peninsula. âCONTEXT : Maritime pine is one of the most important tree species in NW Spain. There was no existing dynamic growth model for this species in Asturias. âAIMS : To develop a dynamic growth model for maritime pine in Asturias, by evaluating two different methods of estimating volume (a disaggregation system and a stand volume ratio function), and to compare the developed model with existing models for Galicia and northern Portugal are the goals of this study. âMETHODS : The dynamic model is based on the state-space approach, in which three state variables characterize the stand at any point in time: dominant height, number of stems per hectare and stand basal area. The transition function for the first variable was developed on the basis of stem analysis data in a previous study, while the corresponding functions for the last two variables were simultaneously fitted with data obtained from successive measurements of permanent plots. An appendix outlining the implementation of a stand growth simulator in the R environment is included to facilitate model use and evaluation. âRESULTS : When the whole model was used to project the stand conditions, the stand volume ratio function performed best, yielding a root mean square error of 22.4 m³ haâ»Â¹ and a critical error of 18.4 %. Comparison with models developed for other regions revealed both similarities and differences, some of which may be attributed to an unequal distribution of the available data in age and site quality classes. âCONCLUSION : The proposed dynamic growth model provided accurate results, and comparison with other region-specific models showed that a single dynamic model may suffice for the whole of the NW Iberian Peninsula.
A willow short rotation coppice (SRC) trial was conducted on former mining land in northern Spain over a period of five years, with the purpose of evaluating the effects on yield of two planting ...densities (9876 and 14,815 cuttings ha−1), three treatments (control, two levels of nitrogen, phosphorus and potassium compound fertilizer (NPK) plus weed control) and three willow clones (Björn, Inger, Olof). The area was subsoiled, ploughed, harrowed and fertilized with NPK before trial establishment. A randomized block design was applied, with three replications of each treatment in a total of 54 plots, each of an area of 400 m2. The effects of the interactions between the various factors on yield and other growth parameters were also studied. The clone factor significantly affected the number of shoots per stool (greatest for the Inger clone) and the Olof clone, which showed the lowest mortality rate and produced the largest trees and largest quantity of biomass. The combined application of fertilizer and herbicide also significantly increased the values of all response variables considered, except the mortality rate. The planting density did not significantly affect the response variables. Clone × treatment interactions were significant for the shoots per stool, height, diameter and biomass variables, and the Olof clone displayed the highest height and diameter growth and yield. The results obtained in the first rotation indicate that the Olof clone adapted well to the trial conditions and therefore would be appropriate for producing biomass in abandoned mine land in Asturias. These findings will help in the development of strategies for the establishment and management of SRC on marginal land.
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