Tabu search is a metaheuristic search process that is useful for locating high-quality solutions to complex combinatorial forest harvest scheduling problems. In this work, we illustrate the quality of outcomes produced by a tabu search process when it is applied to four forest management problems, and we statistically compare the effectiveness of tabu search when it uses a range of parameters and enhancements. This illustration of the variability in results is novel to the use of tabu search to address complex agriculture and forest management problems. The addition of enhancements, which allow n-opt moves through the solution space, reversion back to high-quality positions in the solution space, and randomly designated tabu states (tenures), all seem to improve the ability of tabu search to locate near-optimal solutions with regularity. In addition, we assess whether the second-best selection from the tabu neighborhood has any value in improving the outcomes from the search process. We found that the use of 2-opt exchange moves seems essential for developing forest harvest schedules of higher quality, and the use of search reversion can often help improve the quality of solutions. The selection of the second-best solution from the tabu search neighborhood, while of little value when used exclusively, may be valuable when used sparingly and in conjunction with other search process enhancements.
Extreme weather poses increasing risks to agriculture in South Korea Seomjin and Yeongsan River basins. Using observations from the Korea Meteorological Administrations Automated Synoptic Observing System (ASOS) and Automatic Weather Stations (AWS), I investigated spatiotemp oral extremes in temperature, precipitation, wind, and sunshine during 2020-2023. Station records were summarized by year and location, and spatial fields were generated with GIS-based interpolation at 30 x 30 m to 270 x 270 m resolution; precipitation fields included PRISM-style topographic adjustments. Both basins exhibited substantial fluctuations in minimum temperatures over the four years. Coastal areas tended to have higher minimum temperatures, consistent with maritime moderation. While extreme daily minimum temperatures differed between even-and odd-numbered years, extreme daily maximum temperatures were relatively stable; nevertheless, basin-average maximum temperatures increased from 34.1 degrees C (2020) to 34.6 degrees C (2021) and 35.3 degrees C (2023). Precipitation extremes varied markedly, with station maxima up to 361.3 mm day(-1) (Sunchang, 2020) and gridded maxima of approximately 280 mm day-1 in the Seomjin basin. In the Seomjin basin, northeastern sectors recorded higher daily maximum precipitation than southwestern sectors, likely reflecting topographic controls. Maximum instantaneous wind speeds reached 47.4 m s(-1) at Heuksan Island, and daily sunshine duration peaked at 13.6 h at selected coastal stations. We discuss topographic influences and agricultural implications. Because the 4-year period is short, the results are descriptive rather than inferential; we recommend adopting standardized extreme-indices and cross-validated interpolation to improve comparability and uncertainty characterization in future work.
Stand-level growth and yield models are computationally simple and have moderate demands on input information, but their applications have largely been limited to single-species and even-aged stands. State-space and simultaneous approaches that are not explicitly functions of time potentially extend the applicability of stand-level growth and yield models to mixed-species and/or multi-cohort stands where age (and the period of stand growth that often is derived as the difference in ages) may not be an available and/or suitable predictor. The Acadian Forest, dominated by naturally-regenerated and mixed-species stands of primarily multi-cohort structure, offers an ideal framework for a comprehensive assessment of alternative approaches such as time-explicit, state-space, and simultaneous approaches' performance in stand-level growth and yield predictions across a wide range of complex forest stands. We conducted a comparative assessment utilizing an extensive database from this region. It was found that the three approaches were highly consistent in providing relatively accurate and largely unbiased stand-level growth and yield predictions. The time-explicit approach had a simplistic form but similar prediction performances comparable to the other two more complex modeling approaches. In comparison, the simultaneous approach, despite being path-invariant, was computationally challenging and offered limited improvements from the other approaches. Our findings showed potential applicability of stand-level growth and yield models beyond single-species and even-aged forests.
Stochastic differential equations (SDEs) are increasingly prevalent in a variety of fields. They have become routine in areas like pharmacokinetics and finance. Forestry applications, on the other hand, remain uncommon. This is an accessible introduction to the basic concepts and practical use of SDEs, with an emphasis on forest growth modeling. I begin by briefly discussing dynamical system ideas, describing rates of change in a state space instead of using functions of time directly. Rates of change can be specified by finite differences, but a formulation in continuous time with differential equations is often more convenient. Rational parameter estimation necessitates a stochastic representation of the error structure. Besides observation errors, process noise or environmental variability can be important. Both sources of variability can be taken into account with stochastic differential equations. Simple examples are demonstrated using R software.
On the 50th anniversary of SSAFR, we present a brief survey and summary of the previous meetings and how the methods and applications presented have changed. References to previous surveys of SSAFR papers are included. From the 1st symposium in 1975 through the 20th in 2024, a consistent theme has been participation from a wide range of scientists from university, agency, corporate and non-governmental organizations from around the world. Some of the applications covered include fire management, transportation, multicriteria optimization, forest and land management planning, ecological/environmental analysis, biodiversity and sustainability, decision support systems, stochastic methods and hierarchical planning. While some topics from earlier years have lost currency, new topics have gained in popularity. Climate change has not been emphasized often as a specific topic, but it has been addressed in many areas such as fire management, biodiversity and sustainability, ecological/environmental considerations and stochastic methods. As we look to the future, we are confident that systems analysts will continue to provide solutions and insights into the pressing problems and issues addressed by future generations.
