Sergio de-Miguel

A growth and yield model for even-aged Pinus brutia Ten. stands in Syria

AbstractPinus brutia Ten. subspecies brutia, which occurs in the Eastern Mediterranean region, is the main forest species in Syria and important for multi-purpose forestry. In this study, 6,631 10-year past growth diameter increment measurements were taken in 83 temporary sample plots. The current breast height diameter of all trees was measured and a sample of trees was measured for height and age. The plots were placed so as to capture the whole range of variation in site quality, stand age and stand density. The data were used to develop the following models: Dominant height model: the guide curve method was used to fit an anamorphic site index model between stand age and dominant height.Individual-tree diameter increment model: future 10-year diameter increment was modelled as a function of site index, stand basal area, basal area of trees larger than the subject tree, slope, aspect and diameter at breast height (dbh).Tree height model: tree height was modelled as a function of dbh, dominant height and dominant diameter.Self-thinning: the plots which have reached the self-thinning limit were selected and the (maximum) number of trees per hectare was modelled as a function of mean diameter and site index.The set of models enables the simulation of forest stand dynamics on an individual-tree basis.

Integrating pine honeydew honey production into forest management optimization

Pine honeydew honey is an economically important non-wood forest product from eastern Mediterranean Pinus brutia forests, which are also important for timber production. Pine honey is produced by bees that feed on the honeydew secretions of Marchalina hellenica, a scale insect that infests pine stands and feeds on pine sap. The aim of this study was to optimize the joint production of pine honeydew honey and timber by maximizing the soil expectation value of pine stands. The simulation of P. brutia stand dynamics and timber production in healthy and infested stands is based on individual-tree growth and yield models that account for the effect of M. hellenica on tree- and stand-level growth and mortality. The optimization procedure uses a direct search method based on nonlinear programming. The results suggest that pine stands growing on good sites should be managed using rather short rotations and mainly aiming at timber production. In contrast, forest management in medium- and poor-quality sites should aim at longer rotations by taking advantage of the joint production of pine honey and timber assortments. Honey-oriented forest management can be much more profitable than timber production in stands growing on medium and poor sites. Pine honey represents an opportunity to increase the value and economic profitability of P. brutia forests.

Even-aged or uneven-aged modelling approach? A case for Pinus brutia

ContextThe past management of Pinus brutia forests in Lebanon has led to diverse stand structures that cannot be easily classified as even-aged (EA) or uneven-aged (UA). Most stands are between these stand types, and they may be called as “semi-even-aged”. This is a very common characteristic throughout the Mediterranean conifer forests and makes the choice between the EA and UA approaches problematic, in both management and modelling. However, previous research has devoted little attention to the performance of growth and yield models when applied to transitional stand structures.AimsThe aim of this study was to find the best modelling approach and to recommend equations for simulating the dynamics of the semi-even-aged P. brutia stands of Lebanon on an individual-tree basis.MethodsFifty sample plots were measured in Lebanon. Individual-tree growth models were fitted to the whole dataset using either UA or EA modelling approach. Models were also fitted using two sub-samples containing the most EA and the most UA plots. The performance and accuracy of the two modelling approaches were evaluated in all three datasets.ResultsThe article provides the first complete growth model for uneven-aged P. brutia stands. The EA sub-models presented better statistical fitting. However, the UA sub-models enabled more accurate predictions of wood production and were almost as good as the EA sub-models when predicting stand dynamics of the EA plots. The EA approach provided poor predictions, and the errors were high when it was applied to UA stands.ConclusionsIn structurally complex stands, the UA modelling approach is to be preferred since it predicts the whole stand dynamics more accurately and enables simulations of a broader range of silvicultural treatments.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

A Mixed-Effects Model with Different Strategies for Modeling Volume in Cunninghamia lanceolata Plantations

A systematic evaluation of nonlinear mixed-effect taper models for volume prediction was performed. Of 21 taper equations with fewer than 5 parameters each, the best 4-parameter fixed-effect model according to fitting statistics was then modified by comparing its values for the parameters total height (H), diameter at breast height (DBH), and aboveground height (h) to modeling data. Seven alternative prediction strategies were compared using the best new equation in the absence of calibration data, which is often unavailable in forestry practice. The results of this study suggest that because calibration may sometimes be a realistic option, though it is rarely used in practical applications, one of the best strategies for improving the accuracy of volume prediction is the strategy with 7 calculated total heights of 3, 6 and 9 trees in the largest, smallest and medium-size categories, respectively. We cannot use the average trees or dominant trees for calculating the random parameter for further predictions. The method described here will allow the user to make the best choices of taper type and the best random-effect calculated strategy for each practical application and situation at tree level.

The spatial level of analysis affects the patterns of forest ecosystem services supply and their relationships

The implementation of the Ecosystem Services (ES) framework (including supply and demand) should be based on accurate spatial assessments to make it useful for land planning or environmental management. Despite the inherent dependence of ES assessments on the spatial resolution at which they are conducted, the studies analyzing these effects on ES supply and their relationships are still scarce. To study the influence of the spatial level of analysis on ES patterns and on the relationships among different ES, we selected seven indicators representing ES supply and three variables that describe forest cover and biodiversity for Catalonia (NE Iberian Peninsula). These indicators were estimated at three different scales: local, municipality and county. Our results showed differences in the ES patterns among the levels of analysis. The higher levels (municipality/county) removed part of the local heterogeneity of the patterns observed at the local scale, particularly for ES indicators characterized by a finely grained, scattered distribution. The relationships between ES indicators were generally similar at the three levels. However, some negative relationships (potential trade-offs) that were detected at the local level changed to positive (and significant) relationships at municipality and county. Spatial autocorrelation showed similarities between patterns at local and municipality levels, but differences with county level. We conclude that the use of high-resolution spatial data is preferable whenever available, in particular when identifying hotspots or trade-offs/synergies is of primary interest. When the main objective is describing broad patterns of ES, intermediate levels (e.g., municipality) are also adequate, as they conserve many of the properties of assessments conducted at finer scales, allowing the integration of data sources and, usually, being more directly relevant for policy-making. In conclusion, our results warn against the uncritical use of coarse (aggregated) spatial ES data and indicators in strategies for land use planning and forest conservation.

Mapping Human Impact Using Crowdsourcing

This chapter outlines how crowdsourcing and Google Earth have been used to create the first global crowdsourced map of human impact. Human impact in this context refers to the degree to which the landscape has been modified by humans as visible from satellite imagery on Google Earth. As human impact is measured on a continuum, it could be used to indicate the wildest areas on the Earth. This bottom-up approach to mapping using the crowd is in contrast to more traditional GIS-based wilderness mapping methods, which integrate proximity-based layers of remoteness and indicators of biophysical naturalness in a top-down manner. Data on human impact were collected via a number of different data collection campaigns using Geo-Wiki, a tool for visualization, crowdsourcing and validation of global land cover. An overview of the crowdsourced data is provided, along with the resulting map of human impact and a visual comparison with the map of human footprint (Sanderson EW, Jaiteh M, Levy MA, et al. BioSci 52:891–904. doi: 10.1641/0006-3568(2002)052[0891:THFATL]2.0.CO;2, 2002).