Biodiversity conservation is a priority because it is the cornerstone of ecosystem services and natural cycles, providing essential resources for the development of humans and other species. Several ...indices have been proposed to prioritize areas needing protection. However, some require specific information while others are based on subjective categorical variables, are limited to a particular plant community or cannot be represented at a spatial scale. We developed an Index of Importance for Biological Conservation (InICoB), which was applied to a temperate forest in central Mexico but can be used for any plant community by adjusting some of its parameters. The proposed index is objective, based on quantitative indicators of vegetation composition and structure, and can be spatially projected. InICoB was tested and validated on a temperate cloud forest (CF) and its associated communities: advanced secondary vegetation (ASV) / coffee plantations (CP), agriculture, and induced grasslands. Life forms, presence of endemic, climax, native and protected species, diversity, structural complexity, and complementarity were used as indicators in its construction. InICoB was calculated for 63 sampling units (SUs), and a geostatistical model was incorporated for its interpolation with environmental and social variables as predictors. The results show that InICoB adequately evaluated the different environmental units that cover the locality. Significant differences were observed between the forest and the secondary/induced vegetation. The highest value of InICoB (0.91) was found in the CF, and the lowest in induced vegetation (0.3). The geostatistical model showed that occupation of the land, distance to town, and slope have an important influence on InICoB. The advantages of InICoB include the use of quantitative indicators that can be applied to any plant community. Additionally, it is flexible with respect to the data collected, it can be calculated only with the presence/absence of species or it can include forest measurement data. Furthermore, it is easy to interpret and can be spatially represented in a raster layer that can be added to a geographic information system. Therefore, it can be a very helpful tool in decision-making for land use planning and evaluation of the effects of human activities on plant communities.
Sustainable forest management requires accurate biometric tools to estimate forest site quality. This is particularly relevant for prescribing adequate silvicultural treatments of forest management ...planning. The aim of this research was to incorporate topographic and climatic variables into dominant height growth models of patula pine stands to improve the estimation of forest stand productivity. Three generalized algebraic difference approach (GADA) models were fit to a dataset from 66 permanent sampling plots, with six re-measurements and 77 temporary inventory sampling plots established on forest stands of patula pine. The nested iterative approach was used to fit the GADA models, and goodness-of-fit statistics such as the root mean square error, Akaike’s Information Criterion, and Bias were used to assess their performance. A Hossfeld IV GADA equation type that includes altitude, slope percentage, mean annual precipitation, and mean annual minimum temperature produced the best fit and estimation. Forest site productivity was negatively affected by altitude, while increasing the mean annual minimum temperature suggested the fastest-growing rates for dominant tree height.
•A statistical framework is provided to predict the yield of patula pine stands.•The Weibull and Johnson's SB functions modeled stand diameter distributions.•The Bayesian approach produced robust ...parameter estimates for probability density functions.•The Weibull function fits best empirical diameter distributions; its implementation is simple.•The diameter distribution model could improve southern Mexico's forest management strategies.
Characterization of the diameter distribution of forest stands managed for timber production provides accurate estimates of existing wood volume by diameter class and area unit. It provides the basis for determining the stand's ecological and economic value, its structure, the potential for ecosystem services, and appropriate management practices. Patula pine is one of the most important conifers in southern Mexico and requires biometric tools to improve management strategies. This study aimed to use the Bayesian approach to estimate the parameters of Johnson's SB (JSB) and Weibull (W) probability density functions (pdf) and to model the diameter distribution of patula pine stands in southern Mexico. We used data from 462 diameter distributions derived from 66 permanent 400 m2 sampling plots. The results indicated that the Bayesian approach was appropriate for estimating the JSB and W pdf parameters. Due to the similarity between the nonparametric tests and the goodness-of-fit statistics of the functions, the graphical analysis helped to select the W function as the better option to adequately model the diameter distribution of the analyzed stands. The equations developed for parameter prediction of the W function with stand variables allowed us to characterize and project the theoretical distribution of diameter classes in a simple accurate way with variables easily obtained from forest inventories. The Bayesian approach proved to be an effective method for estimating the pdf parameters used. This allowed for the correct characterization of the observed diameter distribution, and its implementation was easy for executing the procedure. Diameter distribution models are a powerful tool for forest inventory and management of patula pine stands analyzed in southern Mexico.
The search for mechanisms to mitigate global warming has generated a series of proposals to reduce deforestation and promote conservation of forests as carbon stocks through financial or in-kind ...support. However, the economic implications of including carbon sequestration in forest for timber production have not been dealt with in depth, and the conditions in which combined production might be a profitable option to forest owners, particularly in Mexico, are unknown. The aim of this study was to quantify carbon sequestration in a central region of Mexico and evaluate the profitability of selling carbon credits as well as timber products. Data and information used comes from three inventories (2013, 2014 and 2016) taken in 160 permanent sampling plots of 400 m2 each; forest management costs per hectare were obtained through interviews to the landowners, and the profitability was assessed using the economic indicators Net Present Value (NPV), Internal Return Rate (IRR), Benefit-Cost Ratio (BCR), and Land Expected Value (LEV). The results indicate that, in areas of low productivity, carbon sequestration is profitable only at a low discount rate (3.5%) and a high price of the ton CO2e (USD 100 ha-1 year-1). However, under combined production, the optimal rotation periods are longer, depending on the discount rate and price of sequestered carbon. Therefore, timber production will continue to be the main economic activity, until the rules of operation of the different mechanisms created for carbon sequestration become more flexible and the carbon markets offer more attractive incentives.
Forest management planning requires a permanent collection of data on the distribution, composition, and structure of the stands that conform a woodland. These data serve as the basis for suggesting ...the most appropriate management scheme according to the natural resource conditions and management objectives. It is common for the collected databases’ structure and dimension to hinder their analysis using traditional descriptive techniques. Therefore, alternative methodologies are required to facilitate both the exploration of data properties and their collective behavior. We used complex networks analysis to identify distribution patterns of topographic, biological, and productive conditions of a managed forest, suggesting its functional zoning. The forest was considered a graph consisting of nodes and edges; the stands served as nodes and interactions between them as edges. Degree, clustering coefficient, triangles, and modularity were used as segregation and connectivity metrics to evaluate forest properties and allocate stands to five predefined potential forest uses (zones). The clustering coefficient metric provided the better graph partition, allowing to obtain the best alternatives for zoning the forest in conservation areas, areas with potential for timber production, and carbon storage. Proposing forest functional zoning through complex network theory is a powerful methodological option to represent the spatial and nonspatial interactions among the relevant attributes defining a forest ecosystem condition.
The different models that predict the distribution of species are a useful tool for the evaluation and monitoring of forest resources as they facilitate the planning of their management in a changing ...climate environment. Recently, a significant number of algorithms have been proposed for this purpose, making it difficult to select the most appropriate to use. The evaluation of performance and predictive stability of these models can elucidate this problem. Distribution data of 17 pine species with high economic importance for Mexico were collected and distribution models were carried out. We carried out a pre-modeling design to select the prediction variables (climatic, edaphic and topographic), after which nine algorithms and an ensemble model were contrasted against one another. The true skill statistic (TSS) and the area under the curve (AUC) were used to evaluate the predictive performance of the models, and the coefficient of variation of the predictions was used to evaluate their stability. The number of predictive variables in the final models fluctuated from 6 to 12; the mean diurnal range and the maximum temperature of warmest month were included in the models for most species. Random forests, the ensemble model, generalized additive models and MaxEnt were the ones that best described the distribution of the species (AUC >0.92 and TSS >0.72); the opposite was found in Bioclim and Domain (AUC<0.75 and <0.82; and TSS<0.5 and <0.55). Support vector machine, Mahalanobis distance, generalized linear models and boosted regression trees obtained intermediate settings. The coefficient of variation indicated that Bioclim, Domain and Support vector machine have low predictive stability (CV>0.055); on the contrary, Maxent and the ensemble model attained high predictive stability (CV<0.015). The ensemble model obtained greater performance and predictive stability in the predictions of the distribution of the 17 species of pines. The differences found in performance and predictive stability of the algorithms suggest that the ensemble model has the potential to model the distribution of tree species.
Correctly estimating stem diameter at any height is an essential task in determining the profitability of a commercial forest plantation, since the integration of the cross-sectional area along the ...stem of the trees allows estimating the timber volume. In this study the ability of four artificial intelligence (AI) models to estimate the stem diameter of Tectona grandis was assessed. Genetic Programming (PG), Gaussian Regression Process (PGR), Category Boosting (CatBoost) and Artificial Neural Networks (ANN) models’ ability was evaluated and compared with those of Fang 2000 and Kozak 2004 conventional models. Coefficient of determination (R2), Root Mean Square of Error (RMSE), Mean Error of Bias (MBE) and Mean Absolute Error (MAE) statistical indices were used to evaluate the models’ performance. Goodness of fit criterion of all the models suggests that Kozak’s model shows the best results, closely followed by the ANN model. However, PG, PGR and CatBoost outperformed the Fang model. Artificial intelligence methods can be an effective alternative to describe the shape of the stem in Tectona grandis trees with an excellent accuracy, particularly the ANN and CatBoost models.
Current approaches to forest management must be capable of specifying where, when, and how much can be harvested from the forest to procure wood production while dealing with multiple operational and ...conservation considerations. To accomplish such a task, in this work, we present a multi-objective optimization model based on the “triad zoning” approach, which proposes dividing a forest under management into three zones: a) conservation, b) wood extensive production, and c) wood intensive production. An instance of functional zoning for the communal forest of San Pedro El Alto, Oaxaca, Mexico was built, which was validated by a panel of experts. This instance was solved through six heuristic techniques which are: local search, local beam search, multi-start, and three hybrids composed by simulated annealing with each one of the heuristic techniques mentioned above. The results obtained by each metaheuristic were compared among themselves and with the current forest management plan carried out by the community of San Pedro. The simulated annealing with simple local search technique (SLS) generated the best results, maximizing economic gains in the planning horizon while respecting the zoning criteria. In general, the results showed that techniques that use guided search respond efficiently to the defined problem.
•Optimization models have been successfully used in forest management and planning.•TRIAD is a forest planning approach that delivers sustainable benefits.•Heuristics facilitates visualizing scenarios in forest management.
Studies on functional relationships between relative stem diameter and height to estimate timber yield are useful in the management of commercial forest plantations. With taper analysis data of 42 ...Pinus pseudostrobus Lindl. trees in the indigenous community of Nuevo San Juan Parangaricutiro , Michoacan, Mexico, six compatible systems for predicting taper (d), merchantable volume (Vm), stem volume (Vs), total tree volume (Vt) and branch volume (Vb) were fitted and evaluated. The compatible taper and merchantable volume equations were based on volume ratio equations. Three Vs equations were tested in each system. In general, the compatible systems presented statistical accuracy in the d, Vm, Vs and Vt components but were less accurate in Vb. Three compatible systems were selected, according to their more efficient goodness-of-fit statistics, and a different total volume equation was incorporated into each system. The compatible systems based on volume ratio equations are simple, reliable tools for estimation of stand timber stocks and product classification of P. pseudostrobus in commercial forest plantations in Mexico.
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