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Linear programming formulations of forest ecosystem management (FEM) problems proposed in the 1960s have been adapted and improved upon over the years. Generating management alternatives for forest planning is a key step in building these models. Global forests are diverse, and a variety of models have been developed to simulate management alternatives. This paper describes iGen, a forest prescription generator that employs a rule-based system (AI-RBS), an AI technique that is often used for expert systems. iGen was designed with the goal of being able to generate management alternatives for virtually any FEM problem. The prescription generator is not designed for, adapted to, focused on—and ideally not limited to—any specific region, landscape, forest condition, projection method, or yield function. Instead, it aims to maximize generality, enabling it to address a broad range of FEM problems. The goal is that practitioners and researchers who do not have and do not want to develop their own alternative generator can use iGen as a prescription generator for their problem instances. For those who choose to develop their own alternative generators, we hope that the concepts and algorithms we propose in this paper will be useful in designing their own systems. iGen's flexibility can be attributed to three key features. First, users can define the state variable vector for management units according to the available data, models (production functions), and objectives of their problem instance. Second, users also define the types of interventions that can be applied to each type of management unit and create a rule base describing the conditions under which each intervention can be applied. Finally, users specify the equations of motion that determine how the state vector for each management unit will be updated over time, depending on which, if any, interventions are applied. Other than this basic structure, virtually everything in an iGen problem instance is user-defined. iGen uses these key elements to simulate all possible management prescriptions for each management unit and stores the resulting information in a database that is structured to efficiently store the output data from these simulations and to facilitate the generation of optimization models for ultimately determining the Pareto frontier for a given FEM problem. This article introduces iGen, illustrating its concepts, structure, and algorithms through two FEM example problems with contrasting forest management practices: natural regeneration with shelterwood harvests and plantation/coppice. For data and iGen source programs, visit github.com/SilvanaNobre/iGenPaper. [ABSTRACT FROM AUTHOR]

Tree growth models describe the growth and development of forest ecosystems by considering how the dimensions of each simulated tree change within a certain time. These models have commonly used three growth parameters that describe various biological processes and behaviours, considering a sigmoid growth function: (i) the upper asymptote (θ1), which is the maximal yield indicated by a final dimension (such as the maximal stem diameter); (ii) the maximum specific growth rate (θ2), defined as the slope of the tangent at the inflexion point; and (iii) the time elapsed (θ3), defined by the intercept of this tangent with the abscissas. To the best of our knowledge, however, associations between the three parameters have not been documented for tree species. Using diameter growth data from pine trees located in typical mixed and uneven-aged pine-oak forests in the Sierra Madre Occidental, Mexico, our study aims were: (i) to quantify the putative associations between the three growth parameters and (ii) to test the accuracy of a proposed Hybrid Chapman-Richards growth model based on associations between the three growth parameters, but including only one single parameter, relative to the widely used Generalized Algebraic Difference Approach (GADA) based on the Chapman-Richards, Lundqvist and Hossfeld models and the Hybrid Weibull Model. For statistical comparison of the quality of the models, we used the mean relative percentage error, root mean square error, coefficient of determination and Akaike information criterion to assess the quality of the fit. Although the quality of the five growth models studied was similar, from a practical point of view, the proposed Hybrid Chapman-Richards Model (CR-H) is easier to apply than the other models and has a lower data collection and computational cost. The parameter of CR-H can be easily obtained, by measuring just the dominant trees, especially in coniferous forests with irregular ages. Moreover, in contrast to the Chapman-Richards-GADA factor χ0, when θ2 is assumed to be site-specific, the CR-H has always a closed-form solution. [ABSTRACT FROM AUTHOR]

Immersive virtual reality is applied in many human activities. This virtual reality can be used as a training tool for thinning operations in forests. The aim of this study is to describe the complex solution of Thinning Trainer, that we developed. This system uses the SIBYLA growth model for predicting forest-growth development. The model, based on Virtual Reality Modeling Language, was chosen as a virtual reality environment. The CAVE Automatic Virtual Environment was implemented as a hardware tool for the Thinning Trainer, offering an immersive virtual reality of the forest for the users. Mutual connection of hardware, virtual reality and the SIBYLA growth model is established using a software solution called Caveman. Fully automatic system provides users with the possibility to interact and experiment with a virtual forest. [ABSTRACT FROM AUTHOR]

This paper presents a model for optimizing the management of single-species, even-aged stands. The model comprises a number of state variables, given by functions initially differentiable with respect to time, which cease to be due to the discontinuities that cause instant silvicultural treatments. Nevertheless, the proposed model maintains its differentiability with respect to the decision variables (timing, type, and intensity of each thinning, and rotation age). This allows for formulation of the problem of optimal management of this type of stands as a linearly constrained smooth optimization problem, which can be efficiently solved by any derivative-based optimization method. The effectiveness of this formulation is shown by using a sequential quadratic programming (SQP) algorithm to design the optimal management of Pinus pinaster Ait. in Asturias (northwestern Spain) from an economic perspective. These results are compared with those obtained using two methods that do not require derivatives. The SQP, as representative of gradient-type methods, proved robust and much more efficient than the derivative-free methods. [ABSTRACT FROM AUTHOR]

This study developed a new process-based forest module for the Soil and Water Assessment Tool (SWAT), based on the Physiological Process in Predicting Growth (3-PG) model (SWAT-3PG). The new model allows for improved biomass assimilation, partitioning (stem, foliage, root), and losses (root turnover, foliage loss, mortality). Evaluation at field-scale showed that SWAT-3PG can replicate the different forest biomass components for evergreen forests well. Testing for deciduous and mixed forests sites using remote-sensed data showed that the model can simulate leaf area index (LAI), net primary productivity (NPP) and actual evapotranspiration (AET) reasonably well and can be used to constrain SWAT-3PG when lack of field data. Sensitivity analysis of SWAT-3PG showed its potential in evaluating the impacts of management and climate on forested ecosystems. SWAT-3PG can also be of importance to forest managers as it can estimate variables such as plant height, diameter at breast height (DBH), and basal area. • The process-based 3-PG model was incorporated in SWAT for tree growth simulation. • Subroutines for evergreen, deciduous, and mixed forests were developed to capture different forest systems. • SWAT-3PG enhances forest simulation with improved biomass assimilation, partitioning, and losses. • SWAT-3PG can be useful to better understand climate and management impacts in forest ecosystems. [ABSTRACT FROM AUTHOR]

Navigation in forest environments is a challenging and open problem in the area of field robotics. Rovers in forest environments are required to infer the traversability of a priori unknown terrains, comprising a number of different types of compliant and rigid obstacles, under varying lighting and weather conditions. The challenges are further compounded for inexpensive small-sized (portable) rovers. While such rovers may be useful for collaboratively monitoring large tracts of forests as a swarm, with low environmental impact, their small-size affords them only a low viewpoint of their proximal terrain. Moreover, their limited view may frequently be partially occluded by compliant obstacles in close proximity such as shrubs and tall grass. Perhaps, consequently, most studies on off-road navigation typically use large-sized rovers equipped with expensive exteroceptive navigation sensors. We design a low-cost navigation system tailored for small-sized forest rovers. For navigation, a light-weight convolution neural network is used to predict depth images from RGB input images from a low-viewpoint monocular camera. Subsequently, a simple coarse-grained navigation algorithm aggregates the predicted depth information to steer our mobile platform towards open traversable areas in the forest while avoiding obstacles. In this study, the steering commands output from our navigation algorithm direct an operator pushing the mobile platform. Our navigation algorithm has been extensively tested in high-fidelity forest simulations and in field trials. Using no more than a 16 × 16 pixel depth prediction image from a 32 × 32 pixel RGB image, our algorithm running on a Raspberry Pi was able to successfully navigate a total of over 750 m of real-world forest terrain comprising shrubs, dense bushes, tall grass, fallen branches, fallen tree trunks, small ditches and mounds, and standing trees, under five different weather conditions and four different times of day. Furthermore, our algorithm exhibits robustness to changes in the mobile platform's camera pitch angle, motion blur, low lighting at dusk, and high-contrast lighting conditions., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Niu, Newlands, Zauner and Tarapore.)

Quantitative criteria for assessing demographic sustainability of tree populations would be useful in forest conservation, as climate change and a growing complex of invasive pests are likely to drive forests outside their historic range of variability. In this paper, we used CANOPY, a spatially explicit, individual-tree model, to examine the effects of initial size distributions on sustainability of tree populations for 70 northern hardwood stands under current environmental conditions. A demographic sustainability index was calculated as the ratio of future simulated basal area to current basal area, given current demographic structure and density-dependent demographic equations. Only steeply descending size distributions were indicated to be moderately or highly sustainable (final basal area/initial basal area ≥0.7 over several tree generations). Five of the six principal species had demographic sustainability index values of <0.6 in 40%-84% of the stands. However, at a small landscape scale, nearly all species had mean index values >1. Simulation experiments suggested that a minimum sapling density of 300 per hectare was required to sustain the initial basal area, but further increases in sapling density did not increase basal area because of coincident increases in mortality. A variable slope with high q-ratios in small size classes was needed to maintain the existing overstory of mature and old-growth stands. This analytical approach may be useful in identifying stands needing restoration treatments to maintain existing species composition in situations where forests are likely to have future recruitment limitations. [ABSTRACT FROM AUTHOR]

In late successional forests, stand development processes are often more easily monitored and are more closely related to key ecological parameters when using structural criteria rather than stand age or time since stand-replacing disturbance. In this paper, the effects of various disturbance regimes on long-term structural change and resilience in 70 primary northern hardwood stands were analyzed using the CANOPY individual-tree model. Compared to a ‘dichotomous’ disturbance regime of small gap dynamics with infrequent severe disturbance, the historic natural disturbance regime of periodic low- and moderate-severity disturbances produced a more complex landscape mosaic similar to the current landscape. Under the natural disturbance regime, mean residence time in each of 8 structural stages was short (8–35 years) and followed descending monotonic distributions. Mean residence time in old growth was 87 years. Old-growth stands with stable size distributions were much more frequent when defined by relevant structural criteria than when defined by their past history (timing and severity of disturbances). Repeated mild and moderate disturbances often caused stand structure to retrogress to mature or earlier old-growth stages without undergoing stand replacement. However, simulation experiments often demonstrated structural resilience to repeated mild disturbance, even at the 0.5 ha scale. In some cases, disturbances accelerated the development of more complex structure typical of late transition or steady-state stands. Recovery from heavy partial canopy removal was markedly faster than recovery after stand-replacing disturbance. Stands recovered to an old-growth condition with a stable size distribution (‘quasi-steady state’) 175 years after disturbances removing 60% of the aggregate crown area, compared to 280 years after a disturbance with no residual trees. High dominance of these landscapes by old-growth forest (78% of total area) is due not only to the low frequency of stand-replacing disturbance, but also to the structural resilience of old growth to periodic episodes of low- and moderate-severity disturbance. [ABSTRACT FROM AUTHOR]

Late-successional forests often have complex disturbance histories that can result in stands with widely varying structure, ranging from young pole stands to uneven-aged old growth. Arranging stands in chronosequences, however, is problematic because ‘stand age’ is not a meaningful concept for multi-aged stands and ‘time since last stand-replacing disturbance’ often cannot be determined from tree-ring evidence. In this paper, we describe a systematic approach for classifying developmental stages in late-successional forests using structural metrics known to be correlated with key ecological properties such as total biomass, carbon storage, stand production rates, and wildlife habitat. While conceptually based on the amount of aggregate crown area occupied by different size classes of trees, the computations in this study, for ease of use, are based entirely on absolute and relative basal area of four size classes (saplings, poles, mature, and large trees). Eight forest structural stages are recognized, including four stages of old growth (early-, mid-, late-transition, and steady state). The method was used to classify developmental stages of 70 primary northern hardwood stands ( Acer–Betula–Tsuga ) in large landscape reserves in upper Michigan, USA. The degree to which the developmental stages mimic underlying temporal trends in stand dynamics was investigated with the aid of 30-year permanent plot records in primary forests and multi-century simulations using the CANOPY forest dynamics model. Results indicated good correspondence between the postulated developmental sequence in the 70 field stands compared with CANOPY simulations of structural changes over time and changes observed on the permanent plots. Results support the Bormann–Likens hypothesis that the number of large trees reaches a maximum toward the end of the lifespan of an even-aged cohort and subsequently declines in the steady state. While most of the field plots were uneven-aged, both simulations and field data suggest that developmental pathways of even-aged and multi-aged stands after disturbance are very similar and are difficult to distinguish based on the form of the size distributions. In the study area landscapes, 78% of the stands were classified as old growth, with 39% in early or mid-transition and 39% in late transition or steady state. The method should be useful, with appropriate site-specific modifications, in evaluating the degree to which stands meet structural goals under ecological forestry methods, in monitoring responses to environmental change, and in examining biotic changes along a gradient of structural development following disturbance. [ABSTRACT FROM AUTHOR]

Industrial silviculture is known to reduce snag density, but snag dynamics in industrial forests are poorly understood. I developed a simulation model that integrated a snag model and a well-known forest growth model, the forest vegetation simulator (FVS). A new snag model was developed by averaging the outputs of four independently created snag models. The four models were for Douglas-fir snags in forests west of the Cascade Crest in Oregon, Washington, and British Columbia. Forest growth and snag dynamics were simulated under a typical silvicultural regime and current occupational safety and environmental regulations. The results indicate that management practices like those simulated yield: (1) small and medium diameter snags at moderate densities (20 snags per hectare (sph)) for short periods of time (5–10 years); (2) a snag population with high temporal variation fluctuating between 4.2 and 22.5 sph; (3) mean densities of small, medium, and large snags equal to approximately 3.9, 6.2, and 0.1 sph/decade; and (4) a soft snag density of 0.1 sph/decade. Snag recruitment curves generated through simulations showed that to increase mean snag density per decade by 1 sph, the number of snags retained must be increased by about 1.4 sph. The mean density of snags per decade produced under the typical silvicultural regime was projected to be about 20% that found in unmanaged stands. The density of large snags was projected to be less than 1% that found in unmanaged stands. Sensitivity analysis showed that simulator output was slightly sensitive to error in snag model parameter estimates. Considering the lack of long-term empirical studies on snag dynamics, and the dearth of information on compliance with safety and environmental regulations, models like this one represent the best available scientific information upon which to base forest management decisions affecting snag resources. [Copyright &y& Elsevier]

The development of U.S. national park vegetation management policies is briefly traced from 1872, when Yellowstone National Park was created, to the present. Ambiguities in legislative policies are described and partially resolved. Alternative vegetation management objectives, consistent with those policies, are evaluated using quantitative data from a giant sequoia-mixed-conifer forest community in Kings Canyon National Park. It is concluded from an analysis of this data that structural maintenance objectives are biologically infeasible in this forest community because the community does not have a fully regulated or steady-state distribution of aggregation types. Since such a steady-state distribution of aggregation types is probably not present in most forest communities, the Park Service is generally restricted to pursuing process maintenance objectives for vegetation within national parks and monuments. It is also pointed out that implementation of some process maintenance objectives is complicated by the need to return the forest community to its pre-fire exclusion state before reintroducing fire to the ecosystem. To do otherwise would perpetuate the changes in species composition and structure that have resulted from more than three-quarters of a century of fire exclusion. A new alternative for managing vegetation in national parks that is based on a high resolution description of the presettlement forest community, called the reconstruction-simulation approach, is also presented. [ABSTRACT FROM AUTHOR]

Here we present a framework for identifying areas with high dead wood potential (DWP) for conservation planning needs. The amount and quality of dead wood and dying trees are some of the most important factors for biodiversity in forests. As they are easy to recognize on site, it is widely used as a surrogate marker for ecological quality of forests. However, wall-to-wall information on dead wood is rarely available on a large scale as field data collection is expensive and local dead wood conditions change rapidly. Our method is based on the forest growth models in the Motti forest simulator, taking into account 168 combinations of tree species, site types, and vegetation zones as well as recommendations on forest management. Simulated estimates of stand-level dead wood volume and mean diameter at breast height were converted into DWP functions. The accuracy of the method was validated on two sites in southern and northeastern Finland, both consisting of managed and conserved boreal forests. Altogether, 203 field plots were measured for living and dead trees. Data on living trees were inserted into corresponding DWP functions and the resulting DWPs were compared to the measured dead wood volumes. Our results show that DWP modeling is an operable tool, yet the accuracy differs between areas. The DWP performs best in near-pristine southern forests known for their exceptionally good quality areas. In northeastern areas with a history of softer management, the differences between near-pristine and managed forests is not as clear. While accurate wall-to-wall dead wood inventory is not available, we recommend using DWP method together with other spatial datasets when assessing biodiversity values of forests. [ABSTRACT FROM AUTHOR]