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The competitiveness of forest companies is strongly affected by the costs associated with getting the raw material to the mills. As harvesting costs contribute significantly to this cost, mathematical programming models were developed to optimize the scheduling of harvest activities within and between cut blocks to reduce the overall cost. However, the precedence relationship between harvesting activities occurring concurrently across multiple cut blocks has not been considered in the existing literature. In this paper, a mixed-integer linear programming model is developed to optimize the scheduling of harvesting activities, considering the precedence relationship among harvesting activities. The objective of the model is to minimize the total costs. The model determines the start time and end time of each harvesting activity at each cut block, considering the movement time of machines between cut blocks. The model is applied to the case of a large forest company in British Columbia, Canada. The model’s harvesting cost is only 1.37% higher than the lowest possible harvesting cost, and only 3 assigned machines have an idle time. The detailed harvesting schedule is generated based on the start time, the end time, and the operating time for each activity at each cut block., International Journal of Forest Engineering, 34 (1), ISSN:1494-2119, ISSN:1913-2220

Changing climates are altering the structural and functional components of forest ecosystems at an unprecedented rate. Simultaneously, we are seeing a diversification of public expectations on the broader sustainable use of forest resources beyond timber production. As a result, the science and art of silviculture needs to adapt to these changing realities. In this piece, we argue that silviculturists are gradually shifting from the application of empirically derived silvicultural scenarios to new sets of approaches, methods and practices, a process that calls for broadening our conception of silviculture as a scientific discipline. We propose a holistic view of silviculture revolving around three key themes: observe, anticipate and adapt. In observe, we present how recent advances in remote sensing now enable silviculturists to observe forest structural, compositional and functional attributes in near-real-time, which in turn facilitates the deployment of efficient, targeted silvicultural measures in practice that are adapted to rapidly changing constraints. In anticipate, we highlight the importance of developing state-of-the-art models designed to take into account the effects of changing environmental conditions on forest growth and dynamics. In adapt, we discuss the need to provide spatially explicit guidance for the implementation of adaptive silvicultural actions that are efficient, cost-effective and socially acceptable. We conclude by presenting key steps towards the development of new tools and practical knowledge that will ensure meeting societal demands in rapidly changing environmental conditions. We classify these actions into three main categories: re-examining existing silvicultural trials to identify key stand attributes associated with the resistance and resilience of forests to multiple stressors, developing technological workflows and infrastructures to allow for continuous forest inventory updating frameworks, and implementing bold, innovative silvicultural trials in consultation with the relevant communities where a range of adaptive silvicultural strategies are tested. In this holistic perspective, silviculture can be defined as the science of observing forest condition and anticipating its development to apply tending and regeneration treatments adapted to a multiplicity of desired outcomes in rapidly changing realities.

Planning and managing urban forests for livable cities remains a challenge worldwide owing to sparse information on the spatial distribution, structure and composition of urban trees and forests. National and municipal sources of tree inventory remain limited due to a lack of detailed, consistent and frequent inventory assessments. Despite advancements in research on the automation of urban tree mapping using Light Detection and Ranging (LiDAR) or high-resolution satellite imagery, in practice most municipalities still perform labor-intensive field surveys to collect and update tree inventories. We present a robust, affordable and rapid method for creating tree inventories in any urban region where sufficient street-level imagery is readily available. Our approach is novel in that we use a Mask Regional Convolutional Neural Network (Mask R-CNN) to detect and locate separate tree instances from street-level imagery, thereby successfully creating shape masks around unique fuzzy urban objects like trees. The novelty of this method is enhanced by using monocular depth estimation and triangulation to estimate precise tree location, relying only on photographs and images taken from the street. Experiments across four cities show that our method is transferable to different image sources (Google Street View, Mapillary) and urban ecosystems. We successfully detect > 70% of all public and private trees recorded in a ground-truth campaign across Metro Vancouver. The accuracy of geolocation is also promising. We automatically locate public and private trees with a mean error in the absolute position ranging from 4 to 6 m, which is comparable to ground-truth measurements in conventional manual urban tree inventory campaigns.

Species distribution modelling (SDM) is a valuable tool for predicting the potential distribution of invasive species across space and time. Maximum entropy modelling (MaxEnt) is a popular choice for SDM, but questions have been raised about how these models are developed. Without biologically informed baseline assumptions, complex default SDM models could be selected, even though alternative settings may be more appropriate. Here we explored the effects of various SDM design strategies on distribution mapping of four forest invasive species (FIS) in Canada. We found that if we ignored the underlying FIS biology such as use of biologically relevant predictors, appropriate feature selection and inclusion of dispersal and biotic interactions when we developed our SDMs, we obtained complex SDMs (default) that provided an incomplete picture of the potential FIS invasion. We recommend simplifying SDM complexity and including biologically informed assumptions to achieve more accurate dispersal predictions, particularly when projecting FIS spread across time. We strongly encourage SDM users to perform species-specific tuning when modeling FIS distributions with MaxEnt to determine the best SDM design.

Biological invasions represent an increasing threat to ecosystems worldwide, with negative ecological and socio-economic impacts, whereas risk assessment and management remain challenging. The development of decision support systems (DSS) has the potential to help decision-makers and managers mitigate invasive species, but few DSS exist for forest invasive alien species (FIAS). The use of DSS in forestry is not new but they represent an asset in decision making in times of increasing complexity of issues foresters face and factors to consider. Yet, few forest DSS address the problem of FIAS. In this review, we identify key elements of the FIAS risk-assessment and management decision-making process, discuss these elements with a model-based DSS development perspective, and summarize outstanding challenges and opportunities for FIAS DSS development. FIAS DSS should not only estimate the probability of FIAS invasion but also consider forest vulnerability and quantify exposure (i.e., value at risk), while allowing different threat scenarios and possible solutions to be compared. Such a complete risk assessment and management calls for integrative modelling approaches that explicitly link different components of FIAS invasion, management, and impact assessment into a DSS. Such integrative modelling is challenging and may require collaboration among experts of different domains. International collaboration is also needed to facilitate data exchange, as the lack of data is one of the main challenges. In many cases, data and ecological knowledge of invasive species are too limited (in quantity or quality) to constitute useful input to DSS or their components (e.g., species distribution model). Another challenge is to better consider the multiple sources of uncertainties inherent to modelling invasions (e.g., host preferences and behavior, forest vulnerability, potential impacts, and cost and benefits of mitigation actions) when assessing FIAS risk and communicating results from risk assessment. Communication with stakeholders and DSS end-users, in fact, appears as one of the keys to successful DSS development and appropriation, not only to ensure that they correspond to end-users’ needs but also to ensure ease of use, functionality, and good visualization of DSS outputs.

Context Selective logging has been commonly mapped using binary maps, representing logged and unlogged forests. However, binary maps may fall short regarding the optimum representation of this type of disturbance, as tree harvest in tropical forests can be highly heterogeneous. Objectives The objective of this study is to map forest disturbance intensities in areas of selective logging located in the Brazilian Amazon. Methods Selective logging activities were mapped in ten forest management units using Sentinel-2 data at 10 m resolution. A spatial pattern analysis was applied to the logging map, using a moving window approach with different window sizes. Two landscape metrics were used to derive a forest disturbance intensity map. This map was then compared with actual disturbances using field data and a post-harvest forest recovery analysis. Results Disturbed areas were grouped into five distinct disturbance intensity classes, from very low to very high. Classes high and very high were found to be related to log landings and large felling gaps, while very low intensities were mainly related to isolated disturbance types. The post-harvest forest recovery analysis showed that the five classes can be clearly distinguished from one another, with the clearest differences in the year of logging and one year after it. Conclusions The approach described represents an important step towards a better mapping of selectively logged areas, when compared to the use of binary maps. The disturbance intensity classes could be used as indicators for forest monitoring as well as for further evaluation of areas under forest management.

Mapping and valuing of forest recreation is time-consuming and complex, hampering its inclusion in forest management plans and hence the achievement of a fully sustainable forest management. In this study, we explore the potential of crowdsourced social media data in tackling the mapping and valuing of forest recreation demand. To do so, we assess the relationships between crowdsourced social media data, acquired from over 350,000 Flickr geotagged pictures, and demand for forest recreation in British Columbia (BC) forests. We first identify temporal and spatial trends of forest recreation demand, as well as the countries of origin of BC forests visitors. Second, we estimate the average number of annual recreational visits with a linear regression model calibrated with empirically collected secondary data. Lastly, we estimate recreational values by deriving the average consumer surpluses for the visitors of BC forested provincial parks. We find that annually, on average, over 44 million recreational experiences are completed in BC forests, with peaks during the summer months and during the weekends. Moreover, a crowdsourced travel cost approach allowed us to value the recreational ecosystem service in five forested provincial parks ranging from ~2.9 to ~35.0 million CAN$/year. Our findings demonstrate that social media data can be used to characterize, quantify and map the demand for forest recreation (especially in peri-urban forests), representing a useful tool for the inclusion of recreational values in forest management. Finally, we address the limitations of crowdsourced social media data in the study of forest recreation and the future perspectives of this rapidly growing research field., PLoS ONE, 17 (8), ISSN:1932-6203

Gypsy moth (Lymantria dispar L.) is one of the world’s worst hardwood defoliating invasive alien species. It is currently spreading across North America, damaging forest ecosystems and posing a significant economic threat. Two subspecies L. d. asiatica and L. d. japonica, collectively referred to as Asian gypsy moth (AGM) are of special concern as they have traits that make them better invaders than their European counterpart (e.g. flight capability of females). We assessed the potential distribution of AGM in Canada using two presence-only species distribution models, Maximum Entropy (MaxEnt) and Genetic Algorithm for Rule-set Prediction (GARP). In addition, we mapped AGM potential future distribution under two climate change scenarios (A1B and A2) while implementing dispersal constraints using the cellular automation model MigClim. MaxEnt had higher AUC, pAUC and sensitivity scores (0.82/1.40/1.00) when compared to GARP (0.70/1.26/0.9), indicating better discrimination of suitable versus unsuitable areas for AGM. The models indicated that suitable conditions for AGM were present in the provinces of British Columbia, Ontario, Quebec, Nova Scotia and New Brunswick. The human influence index was the variable found to contribute the most in predicting the distribution of AGM. These model results can be used to identify areas at risk for this pest, to inform strategic and tactical pest management decisions.

Forests in the interior of British Columbia, Canada have seen a substantial change in age class structure caused by a mountain pine beetle outbreak that instigated high tree mortality, and consequently, large scale salvage operations. The current age class structure in affected regions implies a midterm timber supply shortage that has the potential to negatively impact the forest industry in affected timber supply areas in the near future. A spatially explicit landscape level forest model for Bulkley timber supply area (TSA), a typical TSA facing these challenges, was developed. Using landscape level planning software we modelled future timber supply as well as age class structure over a 250-year planning horizon for (a) current single entry forest management practices focusing mainly on clearcutting; and (b) alternative management scenarios using multi-entry (thinning) approaches. Alternative scenarios were designed to determine economically viable forest management alternatives while mitigating midterm timber supply shortage, and converting the forest structure in the region towards a more even age-class distribution. Implementing commercial thinnings in stands located within 300 m of existing roads showed the highest potential to successfully mitigate midterm timber supply shortage if entries were scheduled based on culmination of mean annual increment rather than on a fixed minimum harvestable volume. The use of thinnings shortened the overall duration of the midterm timber supply shortage, reaching sustainable harvest levels sooner than if conventional approaches were used, and higher overall timber volumes available for harvest. Alternative approaches to current forest management practices in BC prove to be promising and should be considered where possible.

Forest policy-making can be dramatically enhanced by implementing computer based decision support systems (DSS) during the development phase. While stakeholders usually agree on general policy objectives, the best course of action for achieving them is often unclear. Forest DSS can support the assessment of alternative forest policy frameworks with respect to their impact on multiple variables of interest for stakeholders and decision makers, yet, these tools are often underutilised. In January 2016 a new land use order policy for the Great Bear Rainforest (GBR) in Canada, the largest coastal temperate rainforest in the world, was legally established. The GBR order aims to support ecosystem-based management and legally binding objectives to ensure the long term health of this unique area. This new policy framework will lead to a dramatic decrease in timber harvest levels. We developed 5 alternative forest management scenarios with a less abrupt decline in harvest levels, including carbon sequestration as an option to economically buffer the expected declines in yield. We modelled the development of the forest resources in the area under each scenario over a timeframe of 350 years. In doing so we were able to show how the use of computer based DSS is able to assist policy making by providing a comprehensive assessment of consequences associated with the alternatives, to ensure that long term targets are met. Our results show that currently, the GBR stores around 1.73 Bt carbon, a number that will increase to 1.84 Bt under the GBR order. While it is possible to increase carbon storage by up to 8% when lowering overall timber harvest by 36% over a timeframe of 350 years, naturally, those scenarios with a less dramatic decline in timber harvest were related to an overall lower level of carbon stocks. Combined approaches though, which allow balancing timber harvests with ecosystem integrity, are a powerful alternative to a dramatic and abrupt decrease in harvest levels. The success of combined approaches does heavily depend on timber and carbon markets though. With notoriously cyclical markets the long term economy related to the implementation of the new GBR order remains uncertain when looking at carbon and timber markets only, strongly suggesting to rely on diversification and the creation of added value products.

Economic viability is one of the main considerations in bioenergy and biofuel projects and is impacted by uncertainty in biomass availability, cost, and quality, and bioenergy and biofuel demand and prices. One important aspect of decisionmaking under uncertainty is the viewpoint of the decision maker towards risk, which is overlooked in the biomass supply chain management literature. In this paper, we address this gap by evaluating alternative supply chain designs taking into account uncertain future conditions resulting from changes in biomass availability and cost, and bioproduct and energy prices. Three decision rules, maximax, minimax regret, and maximin, representing, respectively, optimistic, opportunistic, and pessimistic perspectives, are used for evaluation. It is assumed that the decision maker has knowledge about the potential future events, but the likelihood of their occurrence is unknown. According to the results of the case study, investment in bioenergy and biofuel conversion facilities was recommended based on optimistic and opportunistic viewpoints. Production of both bienergy and biofuels would not be profitable under pessimistic conditions. Therefore, investment in only bienergy facilities was prescribed under pessimistic conditions.

Criteria and indicator (C&I) frameworks are frequently used for assessing sustainable forest management. Despite their suitability to assess performance, less attention is given to translating them into strategic forest management planning processes and practices that are of cross-cultural compatibility. Such compatibility is particularly relevant in landscape-level plans that involve Indigenous communities, or multiple groups with various interests. Our study addresses this gap by developing targets and compatible practices that can complement C&I suitable for integrating Indigenous forest management goals and timber production interests. The process for developing C&I is informed by values expressed by four Indigenous communities in central British Columbia (BC) through close revision of traditional use studies, land use plans developed by communities, one focus group discussion, and validation of the results by community representatives. The set of targets and compatible forest management practices we propose are based on a precautionary approach and a synthesis of technical studies conducted in BC. The outcomes are suited to inform both stand- and landscape-level forest management planning and can be considered a reference system to monitor change and facilitate the resolution of multiple interests on the land, reconciling holistic Indigenous values and timber production.

Background There are high estimates of the potential climate change mitigation opportunity of using wood products. A significant part of those estimates depends on long-lived wood products in the construction sector replacing concrete, steel, and other non-renewable goods. Often the climate change mitigation benefits of this substitution are presented and quantified in the form of displacement factors. A displacement factor is numerically quantified as the reduction in emissions achieved per unit of wood used, representing the efficiency of biomass in decreasing greenhouse gas emissions. The substitution benefit for a given wood use scenario is then represented as the estimated change in emissions from baseline in a study’s modelling framework. The purpose of this review is to identify and assess the central economic and technical assumptions underlying forest carbon accounting and life cycle assessments that use displacement factors or similar simple methods. Main text Four assumptions in the way displacement factors are employed are analyzed: (1) changes in harvest or production rates will lead to a corresponding change in consumption of wood products, (2) wood building products are substitutable for concrete and steel, (3) the same mix of products could be produced from increased harvest rates, and (4) there are no market responses to increased wood use. Conclusions After outlining these assumptions, we conclude suggesting that many studies assessing forest management or products for climate change mitigation depend on a suite of assumptions that the literature either does not support or only partially supports. Therefore, we encourage the research community to develop a more sophisticated model of the building sectors and their products. In the meantime, recognizing these assumptions has allowed us to identify some structural, production, and policy-based changes to the construction industry that could help realize the climate change mitigation potential of wood products., Carbon Balance and Management, 16 (1), ISSN:1750-0680

The introduction of the Asian gypsy moth into novel environments continues with frequent interceptions in North America. There is a concern that these subspecies will pose a greater threat to the forests and urban environments of North America than the established gypsy moths (Lymantria dispardispar L.), due to their greater capacity for female flight. Asian gypsy moth populations vary in many key traits, including female flight capabilities. The potential impacts of female flight, in combination with the other key traits, on the ecology and spread of this insect are first discussed in this communication. This also provides the first review of most of the current literature on the variations in flight capability and flight distance of gypsy moth populations, as well as variation in other traits of concern and the potential methods of identification, with special attention paid to the Asian subspecies Lymantria dispar japonica Motschulsky and Lymantria dispar asiatica Vinkovskij. There are currently good tools for identifying the general origin of introduced gypsy moth populations, but these do not provide enough information to effectively manage introductions. Gypsy moth key traits differ among populations, even within each subspecies of the gypsy moth, so introduction of gypsy moths from other world areas into locations where the gypsy moth is already present could result in unwanted changes in gypsy moth biology. It also appears that the introduction of flight-capable females could enhance a population’s dispersal capability and require modifications to management protocols used for flightless females. Therefore, rapid tools to assess key traits in introduced populations are needed to adequately plan for, or deal with, new introductions into novel habitats, Forests, 12 (1), ISSN:1999-4907

Biological invasion is considered the subsequent most important threat to biodiversity after habitat destruction and is documented as a main cause of global biodiversity loss and species extinction. Species distribution models can be used to identify areas that are at risk for invasions by harmful invasive alien species (IAS) if IAS have not yet spread to all suitable habitats. We tested the potential of combining two or more independent but complementary modelling methods to enhance the accuracy of spatial predictions. We used the modelling tools Maxent, GARP and BIOCLIM with presence-only data of the IAS Yushania maling (Maling bamboo), from Darjeeling, Himalaya to develop distribution maps. Modelling tools were chosen based on their performance with presence-only data (Area under curve (AUC) > 0.7) as well as their differences in underlying modelling concept and statistics. The models combine occurrence records with topographic, climatic, and vegetative predictors derived from satellite data. By combining the 3 selected models in an ensemble approach we were able to minimize the spatial uncertainty related to suitable habitat prediction for Yushania maling. While both GARP and BIOCLIM consistently performed at an AUC > 0.7, both our ensemble model and Maxent performed better with an AUC of 0.95 and 0.94 respectively. Moderately and highly suitable habitats for Yushania maling predicted by models correlated well with survey records except for GARP, where we found the model to over-predict suitability outside of the species’ known ecological niche. Our findings identify the best modelling approach enhancing overall explanatory power of habitat suitability models. Our findings show that an ensemble approach should be used to ensure appropriate mitigation measures are applied in the appropriate places, enhancing overall effectiveness both ecologically as well as economically. It was shown that Yushania maling is indeed a threat to the ecosystems in the region, and while the species’ potential habitat may decrease in some areas with climate change, other areas will become more suitable for it.

Invasive species pose significant threats to forest ecosystems. Early intervention strategies are the most cost-effective means to control biological invasions, but are reliant on robust biosurveillance. State-of-the-art genomic approaches can provide an unprecedented opportunity to access detailed information on the invasion process and adaptive potential of invasive insects that pose an immediate threat to forests environments. Genomics can improve diagnostics of the invader and identify its route of invasion by determining the source population(s), assess its probability of establishment and patterns of spread, as well as provide evidence of adaptation. Applied biosurveillance efforts by plant health regulatory agencies will benefit substantially from the detailed insights that genomic data bring to our understanding of biological invasions.

Early intervention, effective management, and regulations are essential to mitigate the potential negative impacts of invasive forest insects. Biosurveillance provides the necessary knowledge to inform management, and regulatory practices. Genomic approaches can contribute valuable information to this process. Unfortunately, adoption and incorporation of genomic tools into biosurveillance frameworks is not straightforward. To realize the full potential of genomic knowledge, researchers must work together with end users to ensure full adoption, standardization, validation, and interpretation of genomic results.

Using forest-based biomass to produce bio-energy and bio-fuels could provide economic, environmental, and social benefits for communities. However, variability in biomass availability and high cost of delivered feedstock impact the profitability of the supply chain. Therefore, optimization models were developed in previous studies to design cost effective and profitable biomass-based supply chains at strategic level. Medium term variations in biomass supply and demand are not usually accounted for in strategic models. This may affect the feasibility of strategic plans prescribed by the optimization model at tactical level. To solve this issue, an integrated model is developed in this paper that includes strategic and tactical decisions simultaneously in order to optimize forest-based biomass supply chains. In addition to yearly variations in biomass supply, which can occur due to changes in harvest level, monthly variations in biomass availability, bioenergy/biofuels demand, and losses during preprocessing and storage of biomass are incorporated in the model. Other unique features of this model compared to the few integrated models developed in previous studies are as follows. (1) Decision regarding opening a new conversion facility is made yearly, not just at the beginning of the planning horizon. (2) A multi-product (heat, electricity, bio-oil and pellets) supply chain is considered. (3) The impact of fossil-based energy prices on bio-conversion investment decisions are accounted for in the model. (4) The optimization problem is modeled in a way that the global optimum solution is obtained within a reasonable time. Using a case study in Interior British Columbia, it is shown in the paper that the capacity of conversion technologies and the amount of procured biomass prescribed by the strategic model would not be sufficient to meet the monthly demand of bioenergy. Moreover, the net present value of the strategic model is overestimated due to underestimating the demand and procurement cost, and ignoring storage costs. It is shown that these issues are resolved using the integrated model.

Knowledge of the driving forces behind indigenous participation in the market is essential for practitioners intending to integrate conservation and development policies in indigenous territories. Nevertheless, empirical research on the determinants of market integration among indigenous peoples is still scarce. This article uses household survey data and multivariate techniques to examine the drivers of market integration among indigenous groups in the Ecuadorian Amazon. We use multiple measures of market integration, including the sale of crops, timber, and wildlife; the use of credit; and participation in wage labor. The results show that the way in which indigenous peoples integrate into the market depends on their endowments of human, financial, and physical capital. More educated households are able to engage in commercial agriculture and nonagricultural wage work, whereas uneducated poor households in communities in conflict with outsiders are pushed to engage in poorly paid agricultural wa...

Using data from a household survey covering colonists and indigenous communities in the Ecuadorian Amazon, this paper analyzes the socioeconomic determinants of legal and illegal smallholder timber harvesting. The results of a multinomial probit model reveal that non-harvesting households are statistically likely to be poor, to receive nonfarm income, to have smaller areas in primary forest and to reside nearer population centers. Illegal logging is more likely to be carried out by poor households that do not have nonfarm income, have larger areas in forest and reside farther away from urban areas. Legal loggers, in contrast, are likely to come from wealthier households that have legal property rights to the land they possess or control but do not take part in nonfarm employment. Ethnicity has no effect on the likelihood of harvesting timber (either legally or illegally) and has only a marginally significant effect on non-harvesting households. The implications of these findings for policy are explored in the conclusions.

Forests around the world are experiencing the cumulative effects of rapid social and environmental change. Building resilience in the forestry sector has thus become of major importance in many countries, including Canada. While British Columbia (BC) generates the highest revenue from the forestry sector in Canada, the planning and management of forests in this province face several limitations that hinder the application of resilience thinking in a fully integrated way that accounts not only for ecosystem processes but also the close interconnection between forests and people. Community forestry in BC provides experience gained over 20 years that can form the basis for a more holistic, long-term approach to enhance the resilience of forested landscapes. Based on interviews with managers of 5 case study community forests (CFs), and a survey of all CFs in BC over three consecutive years, we present pilot practices to manage forests for resilience at the stand- and landscape-levels. Findings show that these practices mainly focus on (1) age and species diversification, (2) introduction of more drought-tolerant species, (3) systematic long-term monitoring of productivity and forest health, (4) wildfire risk management, and (5) introduction of enhanced silviculture such as thinning, rehabilitation and fertilization. Between 2016 and 2018, 38 CFs in BC invested more than CAD 4.5 million in enhanced silvicultural practices using their own funds. The area-based tenure of CFs motivated not only long-term planning and investment, but also shifted the mindset among residents towards a more multi-functional and dynamic view of the forest. Building adaptive capacity and social license, CFs foster a future where forest health and community well-being are compatible. These lessons can be scaled to BC and other forested landscapes in Canada and around the world. Scaling mechanisms include: (1) facilitating knowledge exchange; (2) increasing multi-stakeholder collaboration; (3) replication and mainstreaming of effective practices; (4) rethinking the forest tenure system; and (5) systematic research and monitoring to learn from pilot studies that could inform strategic interventions with landscape-scale impact. Multi-functional forests which are increasingly affected by climate change and novel disturbances could particularly benefit from the insights shared in this paper to build social-ecological resilience.

For the review at hand, Clarivate Analytic's web of science search platform was searched for the keyword combination forest + plantation . The search found 944 articles with the mentioned keywords in their topic that were published between 2010 and 2017. The top 3 subtopics identified were soil , carbon and water in order of abundance. The overview over current research in each of these subtopics to plantation forests naturally show strong overlaps with biodiversity as well as ecological aspects of plantation forests. Given the fact that the assessed research is coming from a wide geographic area, it is specifically interesting to see that general challenges or expectations towards plantation forests do not differ dramatically between those geographies. Overall, there is clear consensus that more plantation forests will be required to meet increasing timber demand, and that productivity in existing forests should be increased. The conversion of natural forests into plantation forests comes with unfavourable consequences with respect to many ecological parameters in the majority of the cases. However, conversion of abandoned or degraded lands into forest plantations can have positive consequences. Overall, there is an increasing interest in plantation forests that are managed for other ecosystem services alongside timber production. Initial research into the possibilities associated with close-to-nature management alternatives, such as mixing species, or uneven-aged management show promising results, consolidating ecological benefits and economic expectations.

We used the portfolio method to examine how a forest company can lower investment risk by producing a mix of timber products. We derived optimum combinations of pine (Pinus patula) saw timber production and eucalypt (Eucalyptus grandis) pulpwood production at landscape level. Our results indicate that producing a product mix rather than a single product improves aggregated financial returns and lowers investment risk over multiple rotation periods. The optimum mixture depended on past timber price correlations for pulpwood and sawn timber in South Africa between 1980 and 2011. This ideal mixture is comprised of areal ratios of about 45% saw timber and 55% pulpwood. Our example shows how economic risk of a forest investment can be reduced by creating a portfolio of a number of products. The risk that an investor has to accept for each monetary unit that is expected in return can be reduced by over 40% when comparing the risk–return combinations of a pure pine saw-timber stand with that of a portfolio of forest products. The risk associated with the production can be reduced by 20% when growing a portfolio of products rather than eucalypt pulpwood only.Keywords: diversification, economic resilience, Eucalyptus grandis, financial theory, mixed species, Pinus patula, portfolio analysis, risk

Forests provide countless ecological, societal, and climatological benefits. With changing climate, maintaining certain services may lead to a decrease in the quantity or quality of other services available from that source. Accordingly, our research objective is to analyze the effects of the provision of a certain ecosystem service on the economically optimized harvest schedules and how harvest schedules will be influenced by climate change. Based on financial portfolio theory, we determined, for two case study regions in Austria and Slovakia, treatment schedules based on nonlinear programming, which integrates climate-sensitive biophysical risks and risk-averting behavior of the management. In both cases, results recommend reducing the overaged stocking volume within several decades to establish new ingrowth, leading to an overall reduction of age and related risk, as well as an increase in growth. Under climate change conditions, the admixing of hardwoods towards spruce–fir–beech (Austria) or spruce–pine–beech (Slovakia) stands should be emphasized to account for the changing risk and growth conditions. Moreover, climate change scenarios either increased (Austria) or decreased (Slovakia) the economic return slightly. In both cases, the costs for providing the ecosystem service “rock fall protection” increases under climate change. Although in the Austrian case there is no clear tendency between the management options, in the Slovakian case, a close-to-nature management option is preferred under climate change conditions. Increasing tree species richness, increasing structural diversity, replacing high-risk stands, and reducing average growing stocks are important preconditions for a successful sustainable management of European mountain forests in the long term.

Imagery from medium resolution satellites, such as Landsat, have long been used to map forest disturbances in the tropics. However, the Landsat spatial resolution (30 m) has often been considered too coarse for reliably mapping small-scale selective logging. Imagery from the recently launched Sentinel-2 sensor, with a resampled 10 m spatial resolution, may improve the detection of forest disturbances. This study compared the performance of Landsat 8 and Sentinel-2 data for the detection of selective logging in an area located in the Brazilian Amazon. Logging impacts in seven areas, which had governmental authorization for harvesting timber, were mapped by calculating the difference of a self-referenced normalized burn ratio (ΔrNBR) index over corresponding time periods (2016–2017) for imagery of both satellite sensors. A robust reference dataset was built using both high- and very-high-resolution imagery. It was used to define optimum ΔrNBR thresholds for forest disturbance maps, via a bootstrapping procedure, and for estimating accuracies and areas. A further assessment of our approach was also performed in three unlogged areas. Additionally, field data regarding logging infrastructure were collected in the seven study sites where logging occurred. Both satellites showed the same performance in terms of accuracy, with area-adjusted overall accuracies of 96.7% and 95.7% for Sentinel-2 and Landsat 8, respectively. However, Landsat 8 mapped 36.9% more area of selective logging compared to Sentinel-2 data. Logging infrastructure was better detected from Sentinel-2 (43.2%) than Landsat 8 (35.5%) data, confirming its potential for mapping small-scale logging. We assessed the impacted area by selective logging with a regular 300 m × 300 m grid over the pixel-based results, leading to 1143 ha and 1197 ha of disturbed forest on Sentinel-2 and Landsat 8 data, respectively. No substantial differences in terms of accuracy were found by adding three unlogged areas to the original seven study sites.

This paper compares land use patterns of mestizo colonists and indigenous populations in the central Ecuadorian Amazon, based on data from a household survey covering mestizo colonist, Kichwa and Shuar households. As expected, colonists mostly engage in commercial agriculture and cattle ranching, but there are substantial differences in land use patterns between the Shuar and the Kichwa. The Shuar engage in cash cropping and cattle ranching, and on average, devote even more land to agricultural uses than mestizo colonists in this sample. In contrast, the Kichwa engage more in subsistence crop production and less in commercial agriculture. Such different patterns appear related to local conditions, earlier migratory and settlement patterns, and the level of exposure to markets. The implications of this for policy are explored in the conclusions.

This study presents economically optimal management of uneven-aged mixed mountain forests that takes into account tree growth variability. We divided 9846 silver fir (Abies alba), beech (Fagus sylvatica), and spruce (Picea abies) trees measured on 898 forest inventory plots in the Snežnik and Leskova dolina management units (4905 ha, Dinaric mountains, Slovenia) into three growth classes (slow-, medium-, and fast-growing trees) to simulate optimal forest management over a period of 100 years with respect to changing tree growth, stand density, diameter distribution, and tree species composition. We developed a density-dependent and stage and growth-structured matrix transition model which—simultaneous to the long-term stand dynamics projection—scheduled optimal harvesting to maximize the net present value using a nonlinear approach. The ecology of tree species was considered by using tree species-specific and stand-density and diameter-dependent logistic functions for ingrowth, transition, and mortality. The model projected a shift in tree species composition from fir-dominated to beech-dominated forests within 100 years. A change from harvesting slow- and fast-growing trees as if they all had medium growth to growth-sensitive harvesting increased the net revenue and maintained the uneven-aged stand structure. Optimal harvest diameters varied among growth classes, time periods, and tree species according to the economic maturity of individual trees and ranged from 12 (pre-commercial thinning) to 72 cm (target diameter). The simulation highlights the potential of improved bio-economic models for increasing yield from uneven-aged forests and scheduling optimal management regimes with multiple objectives.

For the review at hand the ISI web of knowledge was searched for the keyword combination forest + management + planning . Close to 200 articles were found with the mentioned keywords in their topic that were published between 2013 and 2015. The 'top 5' sub-topics found amongst them are climate change , productivity , decision support , carbon and growth modelling in order of abundance. The overview over current research in each of these 5 sub-topics to forest management planning naturally show strong overlaps with climate change being the most abundant, followed by productivity and decision support. Few major breakthroughs can be reported for the time span under consideration, however, there is constant progress towards the development of fast and precise decision support tools that are spatially explicit and able to manage for multiple objectives. As a matter of course this progress is based on numerous detailed findings in the field stemming from a vast variety of topics, with the management of mixed species stands standing out as a topic of increasing interest. An emerging sub-topic that needs mentioning is urban forestry, for which detailed management activities are yet to be developed, possibly based on findings from non-urban forest management.

Western redcedar (WRC) is a highly desirable species in British Columbia's Coastal Western Hemlock zone, both from a management and a conservation perspective. However, it is also highly palatable for ungulates. Existing countermeasures against browsing all have high costs and imperfect results in common. We used the portfolio method to display how diversification can help to lower investment risk. Using risk-return ratios of a WRC and Douglas-fir (DF), we derived species portfolios that yield maximum financial return per unit of risk. Financial indicators were calculated based on Monte Carlo simulations, which consider timber price fluctuation and browsing risk. Results show how economic risks of a forest investment could be reduced by creating a species portfolio. The optimum portfolio leading to most beneficial risk-return combination is 75% WRC and 25% DF if browsing is lowered using protective measures that double planting costs; and 30% WRC and 70% DF if no protective measures are applied. Accordingly, the most desirable risk-return combination is that of a mixed-species forest, whereas the 2 species don't have to be grown in intimate mixtures. Our research sketches a path forward that can help to ensure WRC will remain an important asset in BC's timber portfolio.

Shifts in tree species distributions caused by climatic change are expected to cause severe losses in the economic value of European forestland. However, this projection disregards potential adaptation options such as tree species conversion, shorter production periods, or establishment of mixed species forests. The effect of tree species mixture has, as yet, not been quantitatively investigated for its potential to mitigate future increases in production risks. For the first time we use survival time analysis to assess the effects of climate, species mixture and soil condition on survival probabilities for Norway spruce and European beech. Accelerated Failure Time (AFT) models based on an extensive dataset of almost 30,000 trees from the European Forest Damage Survey (FDS) – part of the European-wide Level I monitoring network – predicted a 24% decrease in survival probability for Norway spruce in pure stands at age 120 when unfavorable changes in climate conditions were assumed. Increasing species admixture greatly reduced the negative effects of unfavorable climate conditions, resulting in a decline in survival probabilities of only 7 %. We conclude that future studies of forest management under climate change as well as forest policy measures need to take this, as yet unconsidered, strongly advantageous effect of tree species mixture into account.

Tree plantations are widely considered a sustainable and economically feasible way to foster reforestation of degraded tropical lands. However, the greatest obstacle to their implementation is the 5–10 years period before initial returns through tree harvesting are realized. This study evaluated the feasibility of generating returns in this period by intercropping hardwood plantations with annual crops. In an agroforestry trial established in eastern Panama, the costs and revenues of intercropping five native and one exotic (Tectona grandis) tree species with three different agricultural treatments––maize-beans, pigeon pea and cassava––were assessed. All tree-crop combinations, except those with cassava, generated positive net cash flows during the first years. Over the modeled rotation period of 25 years, the agrisilvicultural systems showed up to 50 % higher net present values (NPV) than pure forestry (given a 6 % interest rate), while most tree-crop combinations exceeded the NPV of pure agriculture. T. grandis intercropped with pigeon pea showed the best economic performance. The NPVs of the agrisilvicultural systems were less sensitive to changes in costs or revenues than either pure forestry or pure agriculture. Accordingly, the final felling value required for intercropping treatments to meet the desired interest rate of 6 % was up to 90 % lower than that for pure forest plantations. This effect was strongest for native tree species, as their slower growth allowed for longer periods of intercropping. Results suggest that intercropping hardwood plantations can be an effective tool for improving financial feasibility of reforestation while providing increased food security in rural areas.