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An analysis of wood availability under six policy scenarios of commercial forest plantations in Colombia = Un análisis de la disponibilidad de madera bajo seis escenarios de política de plantaciones forestales comerciales en Colombia

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Año de publicación 2022
Idioma Inglés
Publicado por Forest Policy and Economics

Descripción: Forest Policy and Economics 138 (2022) 102722 1389-9341/© 2022 Elsevier B.V. All rights reserved. An analysis of wood availability under six policy scenarios of commercial forest plantations in Colombia ´Oscar Geovani Martínez-Cort´es a, *, Shashi Kant b, Henrieta Isufllari c a Graduate Department of Forestry, John H. Daniels Faculty of Architecture, Landscape and Design, University of Toronto, 33 Willcocks Street, Toronto, ON M5S 3B3, Canada b Institute for Management & Innovation, and, Graduate Department of Forestry, John H. Daniels Faculty of Architecture, Landscape and Design, University of Toronto, 33 Willcocks Street, Toronto, ON M5S 3B3, Canada c Comisi´on Nacional de Evaluaci´on y Productividad, Amun´ategui 232, oficina 401, Santiago, Chile A R T I C L E I N F O Keywords: Forest policy Wood supply: Growth and yield models Colombia Commercial plantations Policy analysis A B S T R A C T An empirical analysis which compares Colombia’s 2019 Forest Plantation for Wood Production Value Chain policy (PFCm policy), aimed at reaching 1.5 Mha of commercial plantations by 2025, with five other policy scenarios, for the period 2015–2047, is presented. We consider two cases with no expansion, and two alternative goals for expansion reaching 0.765 Mha and 2 Mha, and compare the projected volume available for supply of wood with current and projected market demand. The exercise was conducted by designing and using the Colombian Forest Plantation Growth and Yield Simulator for predicting volume available for the supply of the country’s unprocessed wood market, and as a consequence, the manufactured wood forest product market. No-expansion scenarios are non-viable options for the current state of the market, while among the expansion paths considered, both the PCFm policy goal and the 2 Mha scenario produce desirable results. This empirical exercise could be useful in quantifying the magnitude of the wood shortage concerns already identified by the PCFm policy, and provide policy-makers and other stakeholders with a more precise framework for adequate action. 1. Introduction Colombia is a tropical country endowed with rich forest resources, including an estimated 25 million ha (Mha) of available area for the development of commercial forest plantations. However, in the past few decades, the Colombian forest sector has been underperforming, characterized, among other things, by high rates of deforestation and natural forest degradation, and difficulties in supplying from its national sources the forest products demanded. Currently, the country is redesigning its forest policy and implementing, with help from the international community, several forest initiatives to boost the forest sector, but no analytical tools for the forest sector, such as growth and yield simulation models, are available to the stakeholders involved in these processes for analyzing the impact of these policies. Initiatives to restructure the Colombian forest sector have been in the works, more intensively, since the start of the current millennium. As part of the Government initiatives, the Ministry of Agriculture, the Ministry of Environment and Sustainable Development, the Ministry of Industry, Trade, and Tourism, and the Department of National Planning of Colombia released the National Forest Development Plan (PNDF for its acronym in Spanish), in the year 2000 (MMA et al., 2000). One of the main objectives of this plan was positioning the country as a key player in the international arena, with a strong presence and negotiating power over the most pressing topics in forestry: the use, conservation, and sustainability of its forest ecosystems, as well as international competitiveness of its wood forest products (MMA et al., 2000). An important motivator, at the time the PNDF was announced, was Colombia’s heavily underused capacity for commercial forest plantations. By 1996, of the roughly 25 Mha estimated available area for commercial forest plantations, the country had utilized less than 2% for wood production; this, together with the degradation of national natural forest resources, resulted in a substantial negative trade balance of US$ 325 million for the Colombian forest sector, with exports at around US$ 66 million (Martínez-Cort´es, 1998). In addition, country wide data on reforestation in the years preceding 2000, consolidated by Martínez-Cort´es (2022), indicated low and stagnated rates, contrary to the upward trend observed worldwide for the same period. The decades that followed the introduction of the PNDF did not * Corresponding author. E-mail addresses: [email protected] (´O.G. Martínez-Cort´es), [email protected] (S. Kant), [email protected] (H. Isufllari). Contents lists available at ScienceDirect Forest Policy and Economics journal homepage: www.elsevier.com/locate/forpol https://doi.org/10.1016/j.forpol.2022.102722 Received 12 December 2021; Received in revised form 6 March 2022; Accepted 9 March 2022 Forest Policy and Economics 138 (2022) 102722 2 present much change to the state of the forest sector and particularly the wood forest products industry, due, in part, to the delay with which some of the objectives and goals of this plan were being executed. Two examples of this were the slow implementation of the tasks to reach the goals of 1.5 Mha of commercial forest plantations under sustainable management, and the modernization and expansion of the wood forest products industry. As marginal results for these goals were obtained under the PNDF, and the negative trade balance for the Colombian forest sector continued to widen for all manufactured wood forest products (Martínez-Cort´es, 2022), stakeholders called for action in the first half of the 2010s. This call ended up in the Agricultural Rural Planning Unit (UPRA – its acronym in Spanish) leading a two-year (2016–2017) consultation process, which involved more than 50 stakeholders partially to redesign the Colombian forest policy, resulting into what was called the Commercial Forest Plantation for the Wood Production (PFCm) Value Chain policy (PFCm policy - its acronym in Spanish). The PFCm policy was only signed and officially released by the Ministry of Agriculture and Rural Development of Colombia (MADR) in June 2019. This policy is set to be implemented in three time-periods during the next 20 years: 2018–2022, 2023–2030, and 2031–2038, each period to be evaluated against the original objectives (MADR, 2019). Comprising a set of policy guidelines and an action plan, the policy aims to continue to develop and consolidate the PFCm value chain, an initiative which originated in the middle of the 1950s (Martínez- Cort´es et al., 2018a) and, by 2016, was the main source of raw wood for the Colombian forest industry, and within the same year, it generated about 40,000 direct jobs in forest plantations activities alone (MADR, 2017a). At that stage, the total available commercial forest plantation area comprised 0.3 million hectares, translating into a yearly production volume of around 3.0 million cubic meters of underbark unprocessed roundwood (Profor, 2017). One important commitment of this policy, agreed upon through collaboration with the private sector stakeholders, was to continue with the expansion of commercial forest plantations until it reached 1.5 Mha by 2025, the same goal of the PNDF. By focusing on increasing the supply of wood forest products, this policy plans to address two issues related to growing the country’s GDP through the forest sector: increase the international market share of Colombian exports and meet the projected increase in national demand. Estimates for the country’s per capita consumption of wood forest products put the increase in demand for these products at 30% by 2030, and at 50% by 2038, both compared to 2013 levels (Martínez-Cort´es et al., 2018b). The same study also estimated an increase of 20% in the productivity upon successful implementation of the PFCm policy, compared to 2016 levels, as well as an increase in the quality of its wood forest products, on par with international levels. Another important area of the Colombian economy expected to benefit from the PFCm policy is the labour market, which is projected to experience an increase of up to 500,000 new formal jobs by 2030. Of these, around 127,000 will be from the commercial forest plantation expansion and its sustainable management, and the rest will be indirect jobs, related to the transportation, the traditional wood forest products industry, and the commercialization of wood and manufactured wood forest products. Additional jobs are expected to be generated from the expansion of innovative wood forest product industries, such as bio composites, and those belonging to the cosmetics, and the food industry, to name a few. The environmental sustainability aspect of the PFCm policy promises to increase sustainable forest management through a full certification of its practices related to the establishment, management and harvesting, and of the chain-of-custody standards of the wood produced in these plantations. By the end of 2016, the Forest Stewardship Council (FSC) database reported that only around 143,000 ha of the total commercially forest planted area was FSC certified. By that year, there were no other certification programmes for forest plantations in Colombia. In addition to increasing the commercially planted area to 1.5 Mha, the PFCm policy plans to reach a certification level of 80% of this area by 2030, and an 80% certification of the chain-of-custody standards for its forest products by the same year (Martínez-Cort´es et al., 2018b). The contribution of this level of certification is expected to span from protecting Colombia from deforestation and illegal logging of its vast natural forests to improvements in water quality, biodiversity protection, as well as much needed reductions in the carbon footprint. The PFCm policy comprises 12 different programs and 30 projects necessary for its successful execution. The total cost of its implementation, without considering industry modernization and expansion, was budgeted at US$ 1.73 billion, 35% of which will come from the public sector, 64% from the private sector, and the rest from international aid. The majority of these costs are allocated to the expansion of the current (2016) commercial forest plantations to 1.5 Mha and their management. Out of the total cost of US$1.73 billion, the cost of commercial plantations is estimated US$ 1.7 billion, 65% of which will come from the private sector stakeholders invested in the initiative, and 35% from the government budget (Martínez-Cort´es et al., 2018a). Aside from the importance of such policy to both the private sector and the economy as a whole, a more detailed look at the implementation of the 1.5 Mha of the PFCm goal suggests that it was defined without a clear, transparent, and analytical analysis of the impacts that the development of forest plantations of such magnitude would have on the wood forest products markets, and the manufactured wood forest products industry as a whole.1 A good first step towards better insight on the potential impacts of such policy would be a rigorous estimation of the additional volumes of wood added to the market. The heterogenous and multidimensional composition of the source of wood, and the industry that utilizes it make the calculation of volume production from the commercial forest plantations fairly complex. As of 2015, the commercially planted area comprises uneven aged plantations of more than 20 distinct species, planted by large, medium, and small landholders (Profor 2017).2 These species are planted in different geographical areas, and as such, their productivity levels are subject to variations in soil composition, as well climate and other environmental conditions. At the management level, the plantations serve different production objectives, such as wood, fiber, bioenergy, and non-wood/wood forest products. Given that such variation is present in both within the same planted area or between two or more different areas, this, in turn, has generated multiple forestry management regimes. The PFCm policy plans to achieve the 1.5 Mha goal by expanding most of the country’s current commercial plantation areas. It will do so through the planting and management of 16 of more than 20 existing species, specifically the ones with the highest production efficiency.3 In doing so, the additional plantations inherit the same complexity as the current ones. 1 The Colombian wood forest product markets comprise two markets: the unprocessed wood market and the manufactured wood forest products market. The manufactured wood forest products industry includes the wood industry, the furniture industry and the pulp and paper industry. The Colombian wood industry comprises the sawnwood industry; the wood-based panel industry; roundwood industry for poles, piling, posts, etc. preserved or not; and the industry that elaborates a series of manufactured wood products such as moulding and pallets. In this paper, the traditional manufactured wood forest products industries of pulp, wood-based panel other than veneer and plywood, jointly with the innovative manufactured wood forest products industries (forest bioenergy, bio-composites, and derivates from wood for the chemical, cosmetic and food industries) are grouped under the acronym of CITPI. 2 For a 2021 up-to-date distribution on commercial forest plantation area in Colombia refer to MADR (2021). The breakdown of this area by species in 2015 and 2020 is almost the same. 3 Pinus caribaea, P. maximinoi, P. oocarpa, P. patula, P. tecunumanii, Eucalyptus camaldulensis, E. grandis, E. pellita, E. tereticornis, E. urophylla, Tectona grandis, Gmelina arborea, Acacia mangium, Cupressus lusitanica, Pachira quinata y Ochroma pyramidale (Martínez-Cort´es et al., 2018a). ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 3 As a result, there is an imminent need for a dynamic and comprehensive analysis that uses a systematic and robust way of predicting the volume increase upon the implementation of the expansionary policy, which can be utilized by policymakers when evaluating the policy implementation results. In this paper, we provide such analysis through an exercise that evaluates the results of the proposed 1.5 Mha expansion plan of the PFCm policy and five other commercial plantation expansionary paths, for comparison with the ability of said policy to satisfy projected quality-based demand from each wood product industry. In order to conduct our analysis, we developed the Colombian Forest Plantation Growth and Yield Simulator (SCRPFC, by its acronym in Spanish) using the site-quality and species-specific data from the existing commercial plantations. This simulator was designed as part of the Colombian Forest Sector Model (CFSM) which is the main focus of the Ph.D. thesis of the first author. The Simulator estimates volume available for wood supply, and uses it to calculate the expected volume of wood for different industrial use, that will be useful to policymakers during their evaluation stage of the policy. We compare the results of six policy scenarios of commercial forest plantations and discuss their implications for wood supply to forest industry. The rest of the paper is organized as follows: Section 2 presents the literature review. Section 3 introduces the methodology and the simulator. The theoretical details of the simulator are given in Appendix A. An empirical exercise comparing six expansion scenarios as well as the results of the exercise are presented in Sections 4 and 5. We discuss the findings and conclusions in Section 6 and include some final thoughts and future research in Section 7. 2. Literature review Projecting the future availability of wood supply on a national scale is the key to analyzing a country’s long-term forest industry development and the supply and demand of forest products markets. This is one of the reasons why, during the twentieth century, many countries in the world (especially in Europe and North America), implemented forest resource monitoring systems, started nation-wide assessments and later on developed wood availability projection systems that include mostly country-specific tools, models and simulators (Barreiro et al., 2017a). The important features of these projection systems are growth and yield models. These models, which are the representation of an average growth of trees (Salas et al., 2016), are used to predict stand of tree development through time (Twery, 2004). These models can be classified as follows: yield tables, aggregated level (also known as stands-level) models, and individual-tree models (Munro, 1974; Salas et al., 2016; Vargas et al., 2016). The yield tables represent the average value of a stand’s variables (Salas et al., 2016). These are the oldest approach to predict the growth of an even-aged forest, with the first yield table published in Germany in 1787 (Vanclay, 2014). With the continuous development of statistics, yield tables have improved, and by incorporating equations that describe variables through time, they have become a reliable method (Vanclay, 2014). On the other hand, stand-level models use the stand as a single model unit, projecting the number of trees, basal area, or volume per stand based on information on age, stand density and site index (Barreiro and Tom´e, 2017). Although these models omit variations within the stand, they are widely applied around the world (H¨ark¨onen et al., 2010). An example of the former are the growth and yield prediction models for various silviculture regimes, based on large databases of experimental data from large-scale industrial pine plantations in southern US, developed by the Plantation Management Research Cooperative at University of Georgia in collaboration with the forest industry. Aside from considering growth and yield responses to several silvicultural management regimes, the co-op’s work has extended the analytical framework of yield prediction to evaluate productivity and profitability of forest plantations by constructing a profit function for timber production, which offers additional information about the production of this commodity (Yin et al., 1998). Stand-level models are divided in matrix models and models based on probability density function (Salas et al., 2016). Finally, individual-tree models project the diameter and height increments of individual trees, taking into account variables such as tree size, age of stand, stand density and site index. They can also be classified as spatial or non-spatial models (Barreiro and Tom´e, 2017). Another key feature of projection systems are the simulators which range from standard simulators that combine forest inventories and yield tables to complex ones that include a national inventory database and functions/algorithms, which provide helpful information on forest management and assist policy making decisions (Barreiro and Tom´e, 2017; H¨ark¨onen et al., 2010). An overview of differences between projection systems implemented in Europe and North America are described in depth by Barreiro et al. (2017b). In South America, and specifically in the Neotropics which includes Colombia, the literature does not report the existence of national projections systems, but only that of specific simulators for some of a country’s regions and species available. Among those, one of the most relevant works has been done in Chile, through two simulators: Nothofagus (Martin et al., 2020) and AMPL-CPLEX (Büchner et al., 2019; Instituto Forestal, 2013), aimed at both native forest and plantations (Pinus radiata, Eucalyptus spp. and Pseudotsuga menziesii), respectively. In the Neotropic region, SILVIA from Costa Rica was created to manage and model the growth of Tectona grandis and Gmelina arborea at a stand-level or stand group, including species criteria, site index, thinning programs and growth scenarios. It is open to the public and comprises many equations that users can choose, and recently it is also being used for other species from natural forests (Serrano et al., 2008). In Panama, a simulator using an IPTIM (Integrated Planning for Timberland Management) Assets software and SIMO (SIMulation and Optimization framework), where plot inventories are processed to obtain tree-level volume models, taper curve models and stand-level yield models, is designed to describe forest dynamics, project growth and yield, and support decision-making in Teak plantations (Sepp¨anen and M¨akinen, 2020). Another simulator for T. grandis was built using SIMILE in Venezuela, with the purpose of obtaining growth of plantations, harvest volume and carbon sequestration capacity based on quality index, initial density of plantation and thinning regime (Jerez et al., 2015). In Colombia, there exist some simulator-like tools for estimating the growth and yield of forest plantations, but the majority of them tends to be not as elaborate, or are limited to a particular species, parameter and geographical scope. For example, L´opez et al. (2007) have worked on models for forecasting growth and yield based on basal area and volume, to determine the optimum rotation age of Pinus caribaea in the Orinoquia Region in Colombia. Restrepo Orozco (2010), developed an empirical model based on the Bertalanffy-Chapman-Richards model, aimed at describing the yield and growth of T. grandis and Pinus patula in the Norwest Region in Colombia, specifically in Antioquia, C´ordoba and Sucre Departmentos (an administrative and political divisions of Colombia is called Departamento, in Spanish), considering age and environmental covariables. Barrios et al. (2014) developed equations of total volume and ratio for Eucalyptus grandis, using data from 101 trees collected in plantations located in Quindio Departamento (Central Region of Colombia). L´opez et al. (2015) have developed some models of trunk profiles with an autoregressive structure for errors for Eucalyptus tereticornis growing on the country’s Caribbean region and, Melo and Lizarazo (2017) developed equations to estimate tree volumes by applying a single taper polynomial function. The most complete growth and yield simulator for the Colombian forest plantations is the SimFor v 1.2 Software, which was developed in 2013 by the Institute of Informatics of Southern University of Chile (UACh) for Colombia’s National Corporation of Forestry Research and ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 4 Development (CONIF), for which growth and yield models were calibrated with five-year consecutive data coming from 700 permanent plots, distributed all over the Colombian forest plantations. Models were developed at a stand level, disaggregated to diameter classes. The simulation uses three transition functions (number of trees, basal area and dominant height) as algebraic difference equations. As state variables are known at any given age, the number of trees under each diameter class is estimated by recovering the parameters of a Weibull function. A height-diameter function predicts the height of the mean tree in each diameter class. Then, a taper function is used to predict the total volume grouped by products at each diameter class. Although powerful, there are two main issues that arise with SimFor: the institution (CONIF) which owns the software does not make it available for independent and academic research, and the use of a Beta version of the software with restricted features is not feasible, as the information needed to perform the simulations (i.e. state variables for each stand comprising the total mass of commercial forest plantations on December 31st of 2015, or for any other time period is not yet available). In summary, given that no other viable option exists for the Colombian forest sector, the development of a proper growth and yield simulator was instrumental for evaluating wood supply implications of the proposed 1.5 Mha expansion plan of the PFCm policy and other commercial plantation expansionary paths. 3. Methodology The SCRPFC is a tool that facilitates projections of the growth and yield for any stand in the commercial forest plantations. For the purpose of the SCRPFC and our paper, a stand is an area of commercial plantation homogeneously planted with trees belonging to one type of species, all at the same age, and within the same location. This classification is intended to minimize the noise in the data originated from all the variations mentioned in the introduction such as age, species, and site-quality. The simulator can be described in three stages of operations: (i) the calculation of total growth at a stand level at any given year; (ii) the estimation of distribution of each year’s growth by diameter class; and (iii) the determination of the current volume of available stock appropriate for harvesting in order to wood supply to different forest industries. Generally, in the first stage, the transition equations for stand density, dominant height, and basal area are estimated. In the second stage, growth parameters and volume are calculated for each diameter class. In this estimation, first the parameters of a probability function, Weibull distribution in our case, are calculated to find the number of trees in different diameter classes. After that the dominant diameter and the mean height are calculated for each diameter class, and the calculated value of the mean height and the diameter are used to calculate the total volume in each diameter class at a given point of time (year). In the third stage, using the volume taper model, the volume of available wood of different under-bark diameters (which is commonly used to measure industrial wood) is calculated. The technical details of all three stages are given in Appendix A. The three stages of the simulator represent the simulation steps at a theoretical level. Given the heterogeneity in species type, tree shape, and geographical location of the stands, additional adjustments were required, which include the following: For stage one we used the 52 growth and yield tables generated and already available in the Program on Forests (Profor) project of the World Bank on Colombia (Profor, 2017); while for stage three, we utilized the species-specific taper equations developed by L´opez et al. (2011), with data from the permanent plot network of the commercial forest plantations in Colombia. 4. Empirical exercise The Profor report, published by the World Bank in 2017, estimated the existing commercial plantations of 0.3 Mha, by the end of 2015. The Profor report estimated this area based on Colombian Agricultural Institute’s (ICA by its acronym in Spanish) database of official registration of commercial forest plantations (Held et al., 2017). The Profor dataset is the only database that includes the disaggregated data of commercial forest plantations (that includes species, location, site quality, municipality, administrative division (which is also called Departmento in Colombia), and region for each plantation stand). A new database which includes all these and other features up to the end of 2021 is now being prepared under the Ph.D. research of the first author. In addition, one of the distinguishing features of our Simulator, compared to other simulators, is that it incorporates the ICA database, which is regularly updated as per registration requirements implemented in 2019 (MADR, 2019). The Colombian state reported the commercial plantation area of 0.45 Mha by December 2015 (MADR, 2017b), and about 0.5 Mha as of June 2021. However, the MADR dataset, that reported area of 0.45 Mha, is disaggregated only to the levels of species and administrative district. In addition, the MADR results had not been independently reviewed, while the Profor data was supervised by World Bank specialists. Hence, this dataset does not have sufficient disaggregation for the use in simulation exercises. We, therefore, use the Profor dataset as the base for our analyses of different scenarios. The Profor dataset is only available for the period until December 2015, and therefore we use 2015 as the initial year of our analysis. To account for the reported figure of 0.45 Mha plantations in 2015, as per the MADR data, we use it as a base for one of our six scenarios - Scenario 2. A map of the commercial forest plantations, as per the Profor report for 2015, in Colombia is presented in Fig. 1. A breakdown of this area into species, and administrative districts and regions is shown in Figs. 2 and 3, respectively. As mentioned earlier, in Colombia, the administrative unit is called Departamento in Spanish which we are referring as department/division. The boundaries of different departments are shown in Fig. 1. Next, we identified six scenarios. For all scenarios, we assumed that the main objective of all commercial plantations is the production of wood. It was also assumed that all plantations are thinned and subjected to final harvesting at the age indicated by the growth and yield model of each forest species and site-class considered. For the first two scenarios, we assumed that there is no increase in the commercial plantation area either by public or private sector. In other words, the objectives of the PFCm policy to increase commercial plantations are not executed. In the base scenario (Scenario 1), we assumed that 301,146 ha of commercial forest plantations in 2015, as per the Profor report, is maintained in perpetuity. In Scenario 2, we assumed that 450,000 ha of commercial forest plantations in 2015, as per the MADR report, is maintained in perpetuity. For Scenario 2 modeling, 301,146 ha of Scenario 1 was used as the base and the difference plantation area of 148,584 ha was assigned proportionally to the departments and species to the commercial forest plantations in which plantations of Scenario 1 were registered in 2015. We call these two scenarios as no growth scenarios. Next three scenarios are growth scenarios. In these scenarios, the initial plantation area (0.3 Mha) is incremented, starting in 2016, in order to reach 0.765 Mha in 2035 (Scenario 3), 1.5 Mha in 2025 (Scenario 4), and 2.0 Mha in 2025 (Scenario 5), respectively. The scenario 3 (0.765 Mha) is the goal for commercial forest plantations for wood production that Colombia should have under sustained forest rotation, suggested by Profor (Held et al., 2017). The scenario 4 (1.5 Mha) is the goal set by the National Forest Development Plan in 2000, expected to be reached by 2025 (MMA, et al., 2000), which is also the goal for the 2019 PFCm policy (Martínez-Cort´es et al., 2018b), while the scenario 5 is an alternative goal to the scenario 4. In all these five scenarios, the initial area and the target area are maintained under sustained rotation (i.e., the initial area and the target area never decrease). The sixth scenario is about no new plantation and the harvest of the initial plantation area (0.3 Mha in 2015) starting in 2016 without ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 5 Fig. 1. Geographical distribution of Colombia’s commercial plantations on December 31, 2015. (Source: UPRA, 2017. Not official, without scale.) Yellow dots: the forest plantation stands. Red lines: major highways. The name of political and administrative divisions of Colombia (departaments) are printed in black capitalized letter with their corresponding capital city signaled by a red dot. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 6 Fig. 2. Colombia’s commercial plantations on December 31st, 2015, by species, in ha. Fig. 3. Colombia’s commercial plantations on December 31, 2015, by administrative divisions (departments) and regions, in ha. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 7 replacement; consequently, the commercial plantation area eventually diminishes to zero. The key features of all six scenarios are presented in Table 1. 5. Results We run the Colombian Forest Plantation Growth and Yield Simulator (SCRPFC) for estimating the expected volume of wood available for supply from each scenario for the period 2015–2047. Wood available for supply from commercial forest plantations is the wood that would be obtained from a stand which is subject to thinnings and final harvest at the age that the management regime specifies for the species planted in such stand. The wood logs obtained from the thinnings and final harvest must comply, at least, with the minimum specification for industrial use. In 2047, all stands in scenarios S1 to S5 would have completed, at least, the first rotation period under sustained management (i.e., would have been subject to final harvest and been planted for second rotation). A visual representation of the projected expansion area for the six scenarios is given in Fig. 4. The expansion of areas by species and geographical location is presented in Appendix B & C. Simulation results indicate that wood availability from commercial forest plantations for wood production during the simulation period would range between 71 and 868 million m3 of underbark roundwood (Mm3rsc, for its acronym in Spanish), depending on the simulated scenario. When the initial area for wood production diminishes to zero (S6), Colombia would only have a one-time supply of 71 Mm3rsc of wood available for harvesting. When the plantation area increases to 2 Mha (S5) in 2025, which would then be maintained under sustained rotation, Colombia would have 868 Mm3rsc of wood during the 2015–2047 period, and a similar quantity every 32 years, starting in 2047. The wood available for the period of 2015–2047, for the six simulated scenarios is shown in Fig. 5. The volumes in Fig. 5 were obtained by strictly applying the management regime to each stand that makes up the total area of commercial forest plantation in each one the six scenarios simulated. In other words, the volume was obtained by subjecting every stand to both thinning and final harvesting, at an age as per the guidelines outlined in the usual Colombian silvicultural model for each species considered in the simulation. It does not reflect any other harvesting done for satisfying actual or potential market demand for unprocessed wood. In addition, the calculations reflect volumes of stands which have not reached full maturity. For stands which, as of December 31, 2015, are already at full maturity or past it, we suppose that they are harvested at Table 1 Scenario simulations for expansion of commercial forest plantations in Colombia. SCRPFC Scenario Simulation Description Scenario Code Observations NO INCREASE in the existing area of commercial forest plantations on December 31, 2015, (BASE SCENARIO at 301,146 ha) S1: PROFOR2015 Total area of commercial forest plantations of 301,146 ha is maintained in perpetuity (that is, once an area undergoes the final harvest, an area of equal size must be established within forest plantations). NO INCREASE in the existing area of commercial forest plantations on December 31, 2015, (BASE SCENARIO at 450,000 ha) S2: MADR2015 For modeling purposes, the base of 301,146 ha of the PROFOR2015 scenario was used and 148,584 ha were assigned proportionally (in addition to other criteria) to the departments and species in the commercial forest plantations in which these were registered in 2015. Total area of commercial forest plantations of 450,000 ha is maintained in perpetuity. INCREASE of the existing area of commercial forest plantations to 765,000 ha (Completion date: December 31, 2035) S3: PROFOR2035 Area proposed by the Profor project. Profor’s proposal includes increases in plantation yields and the establishment of 463,584 ha of new pine and eucalyptus plantations at an annual rate consistent with the historical trend of annual establishment of commercial forest plantations in Colombia. For modeling purposes, the base of 301,146 ha of the PROFOR2015 scenario was used and annual stands were added for pine and eucalyptus species in the departments where the plantations were located in 2015. Total area of commercial forest plantations of 765,000 ha is maintained in perpetuity. INCREASE of the existing area of commercial forest plantations to 1,500,000 ha (Completion date: December 31, 2025) S4: PNDF/ PAPFCm1 Proposed area of the National Forest Development Plan- PNDF, to be reached by 2025. This proposed goal is the same as the one in the PFCm policy, developed by UPRA. For modeling purposes, the base of 301,146 ha of the PROFOR2015 scenario was used and, as of 2015, annual stands were added for 16 species in 14 departments located in the 3 strategic development regions for forest plantations for commercial purposes defined in the Policy Guidelines of the PFCm chain. Total area of commercial forest plantations of 1,500,000 ha is maintained in perpetuity. INCREASE of the existing area of commercial forest plantations to 2,000,000 ha (Completion date: December 31, 2025) S5: PNDF/ PAPFCm2 Area proposed in the PNDF / PAPFCm1 scenario (S4 above) and an additional 500,000 ha; the annual planting rates between 2020 and 2025 revised accordingly. The total plantation area of 2,000,000 Table 1 (continued ) SCRPFC Scenario Simulation Description Scenario Code Observations ha to be maintained in perpetuity. DECREASE of the existing area of commercial forest plantations to zero ha S6: PROFOR2015- SR Scenario 1 without replacement of annual harvested area. The total area of plantations reaches zero in 2035. For the purpose of calculating the supply of wood, it has been assumed that the volume (both thinning and final harvest) that should have been harvested until December 31, 2015, and is still standing as of that date, will be harvested in equal quotas each year between 2016 and 2034. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 8 the same order as they were planted, starting with the earliest one being harvested in 2016.4 Table 2 presents a more detailed information on the available volumes for supply for the period of the simulations, showing, among others, the average total annual volumes, stumpage volumes for matured, overmatured, and stands where full maturity has not yet been reached. Other indicators included in the table are the average of the additional volumes that are added for every expansionary goal after 2015, and volumes if the total forest plantations were a normal forest. In the Colombian regional context (Fig. 6), under S1 & S2, approximately half of the wood would be available in the Eje Cafetero y Suroccidente region, a quarter in the Caribe region, and 15% in the Orinoquia one. Meanwhile, for S4 & S5, around half of the wood would be available in Orinoquia, a bit over a quarter in Eje Cafetero y Suroccidente, and 20% in the Caribe region. In the S3 case, 38% of the total wood would be available in the Orinoquia region, 36% in Eje Cafetero y Suroccidente, and 21% in the Caribe region. With regards to species types, between 55% and 78% of all the wood available would correspond to the wood of the species of genres Pinus and Eucalyptus for all the simulated scenarios. If wood from these species is added to wood of Acacia mangium, T. grandis and G. arborea, they would account for 87% to 97% of all of the wood available in all six scenarios simulated. The annual average availability of wood for different industrial use from commercial forest plantations for the six scenarios in Colombia is given in Table 3. The table also includes the details of available wood Fig. 4. Annual planted area of commercial plantations under six scenarios in Colombia. 4 A stand that has reached the age of final harvest according to the management regime for a species is considered a mature one. Detailed data on stands for scenarios simulated and the management regime applied may be provided as per request to the first author. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 9 from final harvesting and thinning. 6. Discussion, policy recommendations, and conclusions For convenience, the analysis under this section is conducted in the absence of the wood supply from other Colombian sources (natural forests, agroforestry systems and trees outside the forest) and from imports of unprocessed wood. So, it is important to bear in mind that the way some findings are presented does not imply that in practice “it must be the case”, but rather that the figures allow to present the findings in such fashion. This is an important issue for wood supply and capacity expansion of the Colombian sawnwood industry, when the levels of wood supply and expansion are related just to wood coming from forest plantations, although in reality half of the current supply for this industry comes from natural forests. Also, the present analysis is done without taking into account the possible positive effects on timber supply from gains in productivity that may be derived from any additional foreseeable intensive plantation management other than the current ones applied to forest plantations in Colombia (e.g., additional improvements in competing vegetation control and fertilization) and any genetic improvement of trees. At present, this is not a common practice in the Colombian commercial forest plantation, and should this change in the future, the model presented in this paper will need to be updated in order to best capture the potential gains. This can be modelled by following the guidelines on how the supply of wood from forest plantations can be affected by these two strategies in Yin and Sedjo (2001) and Yin et al. (1998), respectively. 6.1. Supply and expansion of the manufactured wood products industry 6.1.1. No expansion paths (Scenarios 1 & 2) Due to constraints related to the property and distance to the industrial facilities and markets, among others, for scenarios maintaining initial areas (0.3 Mha and 0.45 Mha) under sustained rotation, the actual Fig. 5. Availability of wood from commercial plantations under six scenarios in Colombia, 2015–2047 (million m3 of underbark roundwood). Table 2 Wood available from commercial plantations for the six scenarios in Colombia (Period: 2015–2047; Volume unit: Mm3rsc). Scenarios S1: PROFOR2015 S2: MADR2015 S3: PROFOR2035 S4: PNDF/ PAPFCm1 S5: PNDF/ PAPFCm2 S6: PROFOR2015-SR Total wood available (A) 155 211 303 665 868 71 Annual Average of (A) above 4.8 6.6 9.5 20.8 27.1 2.2 Available volume of matured and over-matured stands on December 31, 2015 18 22 18 18 18 18 Available volume of not yet matured stands at December 31, 2015 6 7 6 6 6 6 Total availability of wood accumulated during 2015–2047, without the initial volumes on December 31, 2015 (B) 131 182 279 641 844 47 Annual average of (B) above 4.1 5.7 8.7 20.0 26.4 1.5 Annual average of wood available if the forest under sustained rotation had been normalized (Normal Forest) in the period 2015–2047 5.1 7.4 13.6 26.1 34.8 N/A ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 10 Fig. 6. Strategic development regions’ potential area for commercial forest plantation development under the PCFm policy. Source: UPRA, 2017. Dark green: the best potential areas; Light green: the second-best potential areas; and Yellow: the third-best potential areas. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 11 availability of wood would be less than that shown in the simulation results in Table 2 (less than 155, and 211 Mm3rsc, respectively). Instead of being, on average, 4.8 and 6.6 Mm3rsc/year (row two of Table 2), they would be 4.1 Mm3rsc/year and 5.7 Mm3rsc/year (row 6 of Table 2) for Scenario 1 and 2, respectively. In Profor, 2017, the installed production capacity of the pulp, wood-based panels, and sawnwood industries, was estimated at 4.8 Mm3rsc/ year (1.0 Mm3rsc/year for pulp, 0.8 Mm3rsc/year for panels and 3.0 Mm3rsc/year for sawnwood (Martínez-Cort´es et al., 2018b).5 It can be seen that the volume generated by the initial area of 0.3 Mha is insufficient for providing wood that meets the 4.8 Mm3rsc/year potential demand (at a 100% production capacity utilization) of the manufactured wood primary products industry i.e., woodpulp, wood-based panels and sawnwood industries. On the other hand, the 5.7 Mm3rsc/year projected Table 3 Annual average availability of wood from commercial forest plantations for the six scenarios in Columbia (By harvest type and industrial use); All volume values in Mm3rsc. Scenario Harvest type Industrial use* Sub-Period Total 2015–2047 Percent 2015 2016–2022 2023–2030 2031–2038 2039–2047 S1: PROFOR2015 Total 0.7 3.0 4.2 3.7 5.3 4.8 100 Final harvest High quality sawnwood 0.2 1.0 1.9 1.2 2.3 1.9 39 Low quality sawnwood 0.1 0.6 0.9 0.8 1.2 1.0 21 Wood-based pannels, pulp, and forest bioenergy 0.1 0.5 0.7 0.7 0.9 0.8 16 Thinnings Wood-based pannels, pulp, and forest bioenergy 0.3 0.8 0.7 0.9 0.9 1.1 23 S2: MADR2015 Total 0.9 3.7 5.9 5.6 7.0 6.6 100 Final harvest High quality sawnwood 0.3 1.3 2.5 1.9 3.0 2.5 38 Low quality sawnwood 0.2 0.8 1.3 1.3 1.6 1.4 22 Wood-based pannels, pulp, and forest bioenergy 0.1 0.6 1.1 1.1 1.3 1.2 18 Thinnings Wood-based pannels, pulp, and forest bioenergy 0.4 1.0 0.9 1.2 1.2 1.4 22 S3: PROFOR2035 Total 0.7 3.0 5.4 9.1 15.8 9.5 100 Final harvest High quality sawnwood 0.2 1.0 2.1 2.5 6.5 3.4 36 Low quality sawnwood 0.1 0.6 1.1 1.8 3.6 2.0 21 Wood-based pannels, pulp, and forest bioenergy 0.1 0.5 0.8 1.3 2.4 1.4 15 Thinnings Wood-based pannels, pulp, and forest bioenergy 0.3 0.8 1.5 3.4 3.2 2.6 27 S4: PNDF/ PAPFCm1 Total 0.7 3.6 15.1 24.6 33.2 20.8 100 Final harvest High quality sawnwood 0.2 1.0 3.2 7.2 13.0 6.7 32 Low quality sawnwood 0.1 0.6 2.6 6.1 8.2 4.8 23 Wood-based pannels, pulp, and forest bioenergy 0.1 0.5 1.9 4.2 5.5 3.3 16 Thinnings Wood-based pannels, pulp, and forest bioenergy 0.3 1.4 7.3 7.0 6.4 6.0 29 S5: PNDF/ PAPFCm2 Total 0.7 3.6 18.2 33.0 45.5 27.1 100 Final harvest High quality sawnwood 0.2 1.0 3.4 9.4 18.0 8.7 32 Low quality sawnwood 0.1 0.6 2.8 8.3 11.2 6.2 23 Wood-based pannels, pulp, and forest bioenergy 0.1 0.5 2.1 5.6 7.5 4.2 16 Thinnings Wood-based pannels, pulp, and forest bioenergy 0.3 1.4 9.9 9.6 8.6 7.9 29 S6: PROFOR2015- SR Total 0.7 2.8 2.6 0.9 0.0 2.2 100 Final harvest High quality sawnwood 0.2 1.0 1.5 0.5 0.0 1.0 43 Low quality sawnwood 0.1 0.6 0.6 0.2 0.0 0.5 21 Wood-based pannels, pulp, and forest bioenergy 0.1 0.5 0.5 0.1 0.0 0.3 15 Thinnings Wood-based pannels, pulp, and forest bioenergy 0.3 0.7 0.1 0.0 0.0 0.5 20 High quality sawnwood (Min. diameter > 20 cm), Low quality sawnwood (Max. diameter < 20 cm & min. Diameter > 15 cm), Wood-based pannels, pulp, and forest bioenergy (Max. diameter < 15 cm & min. Diameter > 5 cm. * Industrial use has been defined based solely on the size of the logs for the industry of traditional primary wood forest products (sawn wood, boards and pulp), and excludes wood for energy from forest biomass, which is included within of the innovative wood forest products industry. Within the classification, no reference is made to the industry of traditional higher value-added wood forest products (eg. paper and cardboard, furniture, structures and wood carpentry and other products of secondary processing), since almost all the products of this industry go through the pulp, sawing and board industries. 5 In 2016 the wood supply of the Colombian woodpulp industry was provided entirely from commercial forest plantations; for the wood-based panels, it comprises wood mainly from commercial forest plantations and negligible amounts of sawndust and other sawnwood industry residues of wood from natural forests. The supply of wood for the sawnwood industry was made up by a mix of both sources: natural forests and commercial forest plantations, with an increasing share of wood from the latter source during the recent years (Martinez-Cortes et al., 2018b). Production capacity and expansion figures are referred to the equivalent cubic meters of roundwood excluding bark needed to produce an amount of manufactured wood products. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 12 from the initial area of 0.45Mha, although enough to satisfy industry demand, does not allow for any considerable demand increases from the industry. In addition, as we mentioned earlier, the details of the figure of 0.45 Mha plantation area are not available at the same level as of the figure of 0.30Mha, and therefore the wood availability of 5.7 Mm3rsc/ year may be questioned. Hence, this makes the dilemma on which initial area to use of little importance for our discussion. This shortage of wood was an issue already suspected during the redesigning process of the PFCm policy in 2017, but given that no actual calculations were performed, it was only mentioned in a rather descriptive fashion. One important contribution that we hope to provide with our simulations is that, now that the figures on wood availability from the initial area of forest plantation have become available, those stakeholders that argued that there is a shortfall in wood supply from the commercial forest plantations in Colombia can now back their argument by an empirical analysis. 6.1.2. Three expansion paths (Scenarios 3–5) Maintaining under sustained rotation the areas of 0.765 Mha (S3), 1.5 Mha (S4) and 2.0 Mha (S5), Colombia would have, on average, 9.5 Mm3rsc/year, 20.8 Mm3rsc/year and 27.1 Mm3rsc/year, of available wood on its commercial forest plantations for wood production (14 Mm3rsc/year, 26 Mm3rsc/year and 35 Mm3rsc/year, respectively, under the concept of Normal Forest).6 In the following 30 years, this raw material would allow for expansions of the sawnwood industry (with estimated current installed capacity of 3.0 Mm3rsc/year) by approximately two, three and five times, respectively (three, four and six times when the forest mass in each scenario reach the behaviour of a Normal Forest). To date, and to the best of our knowledge, there has been no expansion on installed capacity of this industry or the rest of the Colombian forest industries. Therefore, the simulations in this paper are performed using the above rate, without loss of generality. At the same time, the 9.5 Mm3rsc/year, 20.8 Mm3rsc/year and 27.1 Mm3rsc/year (14 Mm3rsc/year, 26 Mm3rsc/year and 35 Mm3rsc/year, under a Normal Forest) average production would allow for the expansion of the CIPTPI (group of industries of pulp, wood-based panels (boards), and innovative manufactured wood forest products), by approximately two, five and six its current (2017) installed capacity, respectively (four, six and eight times if the forest mass is a Normal Forest).7 Under S3, if the Colombian sawnwood industry remains at its current installed capacity (3,0 Mm3rsc/year) and operates at full capacity, starting from the 2023–2030 period, its demand could be entirely satisfied with wood coming from commercial forest plantations (currently about 50% of its total supply comes from natural forests). This industry can also be expanded to a capacity production of 4 Mm3rsc/ year during the period 2031–2038, and then to 10 Mm3rsc/ year during the 2039–2047 period. For the same time periods, the 2017- CIPTPI production capacity (1,8 Mm3rsc/year) could be expanded near to 5 Mm3rsc/year and 6 Mm3rsc/year, respectively. Under S4, the installed capacity of the sawnwood industry could increase to around 6 Mm3rsc/year during 2023–2030, and to 13 Mm3rsc/year during 2031–2038. At the same time, the CIPTPI could increase its installed capacity to 9 Mm3rsc/year during the years between 2023 and 2030, and then to 11 Mm3rsc/year during the years of 2031 to 2038. Under S5, sawnwood industry expansion could reach 6 Mm3rsc/year during 2023–2030, and up to 18 Mm3rsc/year during the period of 2031–2038. In turn, the installed capacity of the CIPTPI could be expanded to 12 Mm3rsc/year during 2023–2030, and then to 15 Mm3rsc/year for 2031–2038. In the previous paragraphs, we have projected industry expansion for S4 and S5 only up to the period of 2031–2038 while Table 3 shows a peak of production in period 2039–2047. However, when analyzed under the focus of a Normal Forest, the figures for average volume of wood available for supply showed in the last row of Table 2 are closer to the figures under column corresponding to period 2031–2038 for S4 and S5. Hence no additional expansion is projected for the period of 2039–2047 for the mentioned scenarios. The above analysis factors in the different expansion rates for each scenario, given that they have to be completed by a specific year, as shown in Fig. 4. For S3, the expansion starts in 2018 with an initial establishment of 4335 ha, and gradually increases over 17 years at an average rate of 2450 ha/year, translating into an establishment of 45,884 ha in 2035, when the target area of 0.765Mha is reached. For S4, the annual planting rate is approximately 10 times that of S3, in order for the total area under S4 to reach 1.5 Mha by 2025, as indicated in the PFCm policy. Finally, for S5, the plantation rate between, 2021 and 2025 is even higher than that of S4, since the objective of S5 is to reach a commercial forest plantation area of 2 Mha by 2025. As shown in the same figure, the annual planting rate up to 2020 is the same for both S4 and S5, due to the necessary time it takes for changes of such magnitude to be implemented. Note that, as Fig. 5 illustrates, the projected volumes for all scenarios during the period 2016–2022 are pretty close, which makes comparison of no additional importance to the discussion. 6.1.3. Harvests without replacement (Scenario 6) If the initial area of commercial forest plantations for wood production in Colombia (0.3 Mha) were to be harvested without replacement (S6), and using a harvest rate of area equivalent to 3 Mm3rsc/ year as per Profor (2017), the initial area would only provide wood for the years up to 2038, and perhaps a few months in 2039, for the operation at full capacity of the current industries of pulp, wood-based panels, and sawnwood. After 2039, the total and average volumes available would be zero. 6.2. Viability of alternative forest policy goals and their impact on the forest markets The above results seem to indicate that no scenario that promotes the diminishing of the initial area of commercial forest plantations for wood production in Colombia is a viable one. Decreasing the initial area by any degree, or bringing it to zero, would put under risk the existence of the Colombian commercial forest plantation for wood production value chain (PFCm value chain), an important value chain with more than six and half decades of generating multiple societal benefits, including, according to (MADR, 2017a), 40,000 jobs directly related to establishing, managing and harvesting forest plantations. Simulation results also point out that scenarios with zero increase of the 2015 initial area (0.3 Mha and 0.45 Mha), but with uninterrupted maintenance of existing area under sustained rotation, are also not viable. Under these scenarios, the 4.1 Mm3rsc/year and 5.7 Mm3rsc/ year of wood availability, respectively, during 2015 to 2047, on average, would be insufficient for supplying the unprocessed wood market, and for the expansion of the country’s manufactured wood primary products industry. The already-delayed industry expansion is much needed to meet the increasing demand for manufactured wood primary products in Colombia (pulp, panels and sawnwood). This demand was estimated to be around 5.5 Mm3rsc of equivalent wood in 2013, with a shortfall in domestic supply of 1.8 Mm3rsc of wood equivalent, which was covered by imports (Held et al., 2017). It should be pointed out that almost the entire demand for primary products is for national consumption; in 2013 6 We also calculated the annual averages of wood availability using the concept of Normal Forest. The results are given in the last row of Table 2. 7 Innovative manufactured wood forest products include forest bioenergy, forest bio-composites, and chemical, cosmetic and food products derived from wood, among others. As of 2017, innovative manufactured wood forest products industry in Colombia is negligible, so the current (2017) installed capacity of the CIPTPI is the sum of woodpulp and wood-based panels, i.e., 1,8 Mm3rsc/ year. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 13 Colombia exported only 3% of the mentioned demanded volume (Held et al., 2017). It is also estimated that 7.3 Mm3rsc of equivalent wood for manufactured wood primary products will be demanded annually in Colombia by 2022, and this demand will increase to 9.2 Mm3rsc of equivalent wood per year by 2030, and up to 10.6 Mm3rsc of equivalent wood per year by 2038 (these estimations do not include an increase in exports nor the potential domestic demand generated by the implementation of the PFCm policy) (Martínez-Cort´es et al., 2018b).8 It seems that a decision of not increasing the initial area of commercial forest plantations for wood production in Colombia, an economic activity for which the country has comparative advantages (Norton et al., 2008), would result in maintaining the negative trade balance of Colombia’s wood forest products. This balance has been negative for a long time, due to the continuous imports of pulp, paper and paperboard, but it has exacerbated in the last two decades due to substantial increases in imports of products for the pulp and paper industry, wood-based panel industry and sawnwood industry. By 1996, Colombia was already reporting a negative trade balance of about 325 million of American dollars (MUSD); this figure came from 391 MUSD in imports and 66 MUSD in exports, which included the following product net balances: roundwood (+0.2 MUSD), wood furniture (􀀀 6.9 MUSD), sawnwood (􀀀 1.5 MUSD), wood-based panels (􀀀 13.0 MUSD), and pulp, paper and paperboard (􀀀 303.5 MUSD) (Martínez-Cort´es, 1998). Based on data from Profor (2017), in 2014, this trade balance reached 􀀀 1044 MUSD (1044.6 MUSD in imports and 0.6 MUSD in exports, with the trade balance being negative for all products in both monetary and physical terms). If the trade balance is observed in physical units (volume), it can be noted that, during the last two decades, Colombia has had a negative trade balance in volume (i.e. volume of wood forest products imported greater than volume of wood forest products exported) and that this deficit has increased substantially in all wood forest products but specially for panels as well as pulp, paper, and paperboard products. The results indicate that scenarios of increasing the 2015 initial area to 0.765 Mha, 1.5 Mha and 2 Mha, and keeping these target areas under sustainable rotation, are viable options. Under these scenarios, once the total mass of forest plantations has reached, on average, the level of a “normal forest”, the projected amounts, respectively, of 14 Mm3rsc/ year, 26 Mm3rsc/year, and 35 Mm3rsc/year of wood available would allow for the supplying of the unprocessed wood market with national wood, the expansion of the manufactured wood primary products industry, meeting future national demand for these primary products, as well as the development of the domestic and exports markets for the manufactured wood products in general. An expansion of manufactured wood primary products industry usually allows the flourishing of the manufactured wood secondary products industry (also known as the major value-added wood products industry); i.e. an industry whose output is products such as: paper, and paperboard and packaging, laminated wood, wood furniture, among others. It is also expected that enough raw material (wood) would influence the development of innovative manufactured wood products industry such as: forest bioenergy products, chemical, food and cosmetic wood products, and bio composites industries. The difference between the first expansion scenario (S3) and the last two (S4 & S5) lies in the available time and the magnitude of these endeavours. Under the 0.765 Mha target (S3) scenario, projected to be reached by 2035, the manufactured wood primary products industry would have enough raw material from the unprocessed wood market to conduct its first expansion as early as in the period between 2023 and 2030, when 5.4 Mm3rsc/year of wood is available. However, this expansion would be insufficient to meet the domestic demand for its products during that period (i.e 7.3 Mm3rsc of equivalent wood/year). Only during 2031–2038 would the unprocessed wood market have a sufficient amount of raw material (9.1 Mm3rsc/year), that would allow for the expansion of said industry to such a size that would make it capable of completely meeting the demand of the Colombian market for pulp, boards, and sawnwood (i.e. 9.2 Mm3rsc of equivalent wood per year). This implies that, up to 2030, Colombia would continue to increase its imports, and that, up to 2038, all imports and national production of the manufactured wood primary products industry would be exclusively dedicated to meeting the domestic consumption needs.9 Only during the 2039–2047 period, when the production in the commercial forest plantations for supplying the unprocessed wood market would reach 14 Mm3rsc/year (under a normal forest focus), would the manufactured wood primary products industry be able to expand to the point where it would be able to both meet the total demand of 10.6 Mm3rsc of equivalent wood per year (mostly domestic consumption), and marginally develop the exports markets for the same products. Under the 1.5 Mha scenario (S4) (the policy goal of the National Forest Development Plan of Colombia and the PFCm policy to be achieved by Dec 2025), the final industrial expansion size would be 12 Mm3rsc/year, more than that under the 0.765 Mha scenario. Furthermore, what happens in this latter scenario for the forest markets between 2039 and 2047 could happen 15 years sooner under the 1.5 Mha one. For the 2023–2030 period, and then during the 2031–2038 period, the unprocessed wood market could be supplied with 15 Mm3rsc/year and 26 Mm3rsc/year, respectively; these amounts would allow for the expansion of the manufactured wood primary products industry to entirely meet the domestic consumption during such periods (i.e 7.3 Mm3rsc and 9.1 Mm3rsc of wood equivalent/year). Starting in 2023–2030, Colombia would have an excess of raw material for additional expansions of the manufactured wood primary products industry, to account for an expected additional demand to be generated due to the implementation of the PFCm policy. This additional demand is expected to be generated especially by fulfilling policy goals related to the development of an innovative manufactured wood forest products industry in Colombia (e.g. forest bioenergy, which in 2017 was in its infancy), an increase of per-capita national consumption of wood and its manufactured products (whose figures of 12 m3/per capita for 2015 are deemed to be pretty low (Martínez-Cort´es et al., 2018b)), the recovery of some wood forest products market segments that the manufactured wood products industry has lost in the country’s economy (such as those in the construction sector), and the development of the export markets for Colombian wood forest products. For the 2.0 Mha scenario (S5), the quantity of 35 Mm3rsc/year of wood available for harvesting once the total mass of forest plantations is considered a “Normal Forest”, represents an additional 9 Mm3rsc/year potential expansion of the Colombian manufactured wood primary products industry as compared to S4. The annual volume harvested under S5 is comparable in order of magnitude to the annual harvest of Chile, which, with an area of 2.4 Mha of forest plantations under sustained rotation, harvested 43.6 Mm3rsc in 2015 (Gisling et al., 2017). In terms of the cost, the average cost of per hectare (establishment and management for the first four years without including the cost of land) is USD1,420 (2017). Hence, the total costs of S3, S4, and S5 scenarios will be 0.66, 1.7, and 2.4 billion USD (2017), respectively. The socio-economic benefits of these scenarios, in terms of expansion of forest industry to meet domestic demand, employment potential, increased export, and contributions to trade balance, are already discussed earlier. A deeper economic analysis, which is beyond the scope of this paper, will provide a comprehensive picture of economic ranking of these scenarios, and should be the subject of future research. 8 Demand figures are preliminary and were estimated by using an analysis similar to a “gap model” during the redesigning of Colombia’s forest plantation policy in 2016 and 2017. 9 Recall that demand figures were estimated under the assumption of a no growth of exports, and in 2013, the base year for the demand estimation, Colombia exported negligible quantities of wood forest products. ´O.G. Martínez-Cort´es et al. Forest Policy and Economics 138 (2022) 102722 14 7. Final thoughts: SCRPFC & the Colombian Forest Sector Model (CFSM) The apparent usefulness of the SCRPFC in analyzing and evaluating policy goals was demonstrated in the preceding sections. Information related to the available volumes for supply provides key elements in understanding the interactions among some variables affecting the supply and demand of wood forest products in Colombia: the extension of the forest plantations, the supplying of wood to the unprocessed wood market, the current and potential size of the manufactured wood products industry, and the supplying of the markets of manufactured wood products. However, the interactions among the above-mentioned variables are far more complex than that discussed in the preceding sections. These variables are not working in isolation, but they are affected by other groups of variables from other parts of the forest sector, such as: the wood available for supply from natural forests, agroforestry systems and trees outside the forests; the behaviour of the economic agents in the unprocessed wood market, which is influenced by what happens in the manufactured wood products market; and by the behaviour and actions of economic agents within each market, which are in turn influenced by the performance of the Colombian and the global economies, to name a few. As such, the simulations presented in this paper are the first input needed to estimate a more complete and powerful benchmark, useful in conducting the analysis of the PFCm policy: the wood forest product markets behaviour. The design of the SCRPFC and the volume estimation exercises are part of the Phase I of the CFSM, a sectoral model developed by Martínez-Cort´es (2022) as part of his doctoral thesis research, in order to estimate the supply and demand for wood forest products in the Colombian context, and estimate the potentially achievable quantities and prices of wood forest products for the years that follow. These and other more complex interactions that happen within and outside of the forest sector limits are what is simplified into core relations within the CFSM. The forecasts generated by the CFSM would provide benchmarks on the required quantities of wood traded in the unprocessed wood market (a part of which would come from the wood available for supply from Colombian commercial forest plantations), and the prices at which the trades would happen, as well as the quantities of manufactured wood products that economic agents would trade in the market for these products together with the agreed upon price. The CFSM analyses that addresses the question that how the expected quantities and prices for wood and manufactured wood products in the following years synthetize the expected behaviour of the (wood) forest markets in the long run, will be presented in the future publications. The findings of these publications will provide a better benchmark for feedback and recommendations on the viability of alternative policy goals, such as: the extension of Colombia’s forest plantation area, the final size of the manufactured wood products industry, and the development of the country’s unprocessed wood market as wells as the manufactured wood products one. Contributions of authors Oscar Geovani Martinez-Cortes: Research conceptualization; data collection and curation; data analysis and model building; programming, model validation; visualization; and writing - original draft, and revisions as per comments & editing. Shashi Kant: Intellectual and theoretical inputs on research conceptualization; data requirements and curation; data analysis and model building, model validation; and different version of the manuscript. Henrieta Isufllari: Support in data collection, policy analysis, preparation of the first draft, editing, and incorporation of the reviewers’ suggestions. Declaration of Competing Interest Authors declare no competing interests. Acknowledgements This research was made possible with the financial and non-financial support of the Graduate Department of Forestry, University of Toronto, Unidad de Planificacion Rural Agropecuaria de Colombia (UPRA), and the research grant of the 2nd author from Natural Science and Engineering Research Council of Canada, [RGPIN-2019-05199]. The authors would also like to acknowledge the valuable inputs/ suggestions of the first author’s Ph.D. supervisory committee members and William F. Hyde and the valuable support at UPRA received from Felipe Fonseca, Daniel Aguilar y Alejandro Florez, and Luis Fernando Parra, specifically in building the simulator and programming in R, and the comments on the original draft and editing of the paper by Ximena Laverde. The authors would like to express our appreciation for the constructive comments and suggestions made by the two anonymous reviewers. 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: Oscar Geovani; Kant Martínez Cortés, "An analysis of wood availability under six policy scenarios of commercial forest plantations in Colombia = Un análisis de la disponibilidad de madera bajo seis escenarios de política de plantaciones forestales comerciales en Colombia", Colombia:Forest Policy and Economics, 2022. Consultado en línea en la Biblioteca Digital de Bogotá (https://www.bibliotecadigitaldebogota.gov.co/resources/3711905/), el día 2025-05-08.

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An analysis of wood availability under six policy scenarios of commercial forest plantations in Colombia = Un análisis de la disponibilidad de madera bajo seis escenarios de política de plantaciones forestales comerciales en Colombia

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