Spatial exploration, dendrometric characteristics and prediction models of wood production in a stand of Acacia schaffneri in Durango, Mexico

Degraded vegetation is the result of a process that affects structural and functional characteristics. Tree species from the Acacia genus are very important to the ecosystem in semi-arid lands due to their participation in the recovery of highly degraded areas. One of the most important species among this genus is A. schaffneri. The status of a forest stand is determined according to its structure, including height, stratum and density. Remote sensing is a valuable method for estimating volumetric stocks and associated changes in forest populations over established periods of time. The objective of this research was to estimate wood volume of A. schaffneri using remote sensing, and to complement that information with the results obtained from an estimation method based on forest measurements. The results obtained showed that the crown area was the dendrometric variable that can be used in a wood volume prediction model. In the exploratory analysis between dendrometric variables and remote sensing showed low and negative associations were observed in the four stations analyzed. There are conservation problems due to anthropogenic activities, among which stands out the intensive grazing that results in a decrease of the natural regeneration capacity of Acacia schaffneri.

Growth Response to Weed Control and Fertilisation in Mid-Rotation Plantations of Eucalyptus pellita in South Sumatra, Indonesia

We report on a study of mid-rotation weed control and nutrient management in Eucalyptus pellita plantations in South Sumatra. The study was established at two contrasting sites (representing high and low productivity for the region) that had previously carried three rotations of Acacia mangium. A combination of weed control, nitrogen (N), and phosphorus (P) fertiliser were applied at 1 and 2 years after establishment. We found that the addition of up to 250 kg N ha−1 applied either at 1 year or 2 years after planting did not improve growth. The application of P (30 kg P ha−1) at age 1 year (in addition to 12 kg P ha−1 applied at planting) did not enhance tree growth either. Keeping the plantation free from weed competition throughout rotation (full weed control) enhanced wood volume up to age 4 years at the high-productivity site, while it improved wood volume up to the end of rotation at age 6 years at the low-productivity site. An additional experiment assessing the effect of weed control in the early phase of plantation establishment revealed that weed competition reduced young tree growth of E. pellita substantially. The results of the studies support the current practice of plantation management of E. pellita in the region that applied only P fertiliser at planting time and that kept trees free from weed competition before canopy closure. Full weed control throughout rotation is worth practicing at lower-productivity sites to achieve maximum productivity.

Introducing a New Approach in Stand Tending Planning and Thinning Block Designation by Using Mixed Integer Goal Programming

Long-term management plans have been developed for nearly all of the forests in Turkey. These plans are applied at a sub-district management unit level and may contain guidance for both intermediate yield and final yield harvests. To implement an intermediate yield plan, which involves the scheduling of forest thinnings (stand tending), consideration in Turkey is given to the advantages of working in the same terrain and the same general area each year. Therefore, compartments are often clumped together to create thinning blocks, taking into consideration the thinning priority of the stands, road conditions, site index, age, and proximity of the compartments. Further, when preparing annual budgets and planning to meet the market’s needs, forest enterprises require an even flow of intermediate wood volume each year. In this paper, we introduce a new approach in stand tending planning designed to schedule an equal amount of intermediate wood volume each year and to create thinning blocks by minimizing the distance to pre-defined ramps (landings). We developed both linear and nonlinear goal programming models to minimize both the deviations from a harvest volume (annual intermediate yield allowable cut) target and the deviations from a target value determined for the distances (total and average) of the centroid of each compartment to the hypothetical forest ramps. By using the extended version of Lingo 16, we solved the problem with different weights for the deviations in volume and distance that ranged from 0.0 to 1.0, in 10% intervals, which created 11 scenarios. We carefully analyzed the results of each scenario by taking into consideration the wood volume and distance of compartments to the ramps. The best scenario using the linear model produced a deviation in volume scheduled for the entire decade of 6 m3, while the deviation in total distance between harvest areas and ramps was 59.7 km. Scenario 5, with weights of 0.6 for volume and 0.4 for distance, produced these results, where compartments were closest to one another. The best scenario using the nonlinear model also produced a deviation in volume of 0 m3 and the total average deviation in distance between harvest areas and ramps was 8.7 km. Scenario 3, with weights of 0.8 for volume and 0.2 for distance, produced these results. The approach and models described through this study may be appropriate for further integration into forest management planning processes developed for the planning of Mediterranean forests.

Deforestation and Biomass Production in Miombo Forest in Huambo (Angola): A Balance between Local and Global Needs

Miombo is one of the most widely distributed ecosystems in Angola, with a great social and environmental value. Thus, the rural population uses the biomass as fuel and miombo provides important ecosystem services, such as its carbon sequestration capacity. The objectives of this work were (i) to assess deforestation in miombo forest in Huambo province (Angola) during the last 20 years, (ii) to evaluate carbon storage capacity of miombo, and (iii) to calculate the charcoal productive capacity of those forests. From 2000 to 2019, 359,130 ha (12.96%) were deforested in Huambo province. Thirty-six woody species were identified as major components of miombo forest, the most frequent being Albizia anthunesiana, Brachystegia spiciformis, Julbernardia paniculata, Monote spp., Brachystegia boemii, Isoberlinea angolensis, Anisophyllea boehmii, Syzygium guineense, and Erythrophleum africanum. The total biomass estimated in miombo forest was 195.05 Mg ha−1 (55.02 Mg ha−1 radical and 140.04 Mg ha−1 area), with a total wood volume of 78.57 m3 ha−1. This represents values of 91.67 Mg ha−1 of accumulated carbon and 336.13 Mg ha−1 of CO2 equivalent. The potential charcoal productivity was 15,359.9 kg ha−1, corresponding to 24.78 trees ha−1. The Annual Allowable Cutting Volume was 10.77 m3 ha−1 year−1, 14.13 m3 ha−1 year−1, 21.17 m3 ha−1, and 32.85 m3 ha−1 year−1 for rotation lengths of 55, 40, 25, and 15 years, respectively, corresponding to a potential annual charcoal productivity of 2107.08 Kg ha−1 year−1, 2762.96 Kg ha−1 year−1, 4139.21 Kg ha−1, and 422.56 Kg ha−1 year−1. However, deforestation rates in the last 19 years and low charcoal productive capacity could compromise the sustainability of the Miombo ecosystem and its value as an ecosystem service provider in the province if appropriate management strategies are not developed.

Development of fishing vessel shipyard in traditional Lampulo, Banda Aceh

The construction of ships at the Lampulo shipyard has not all used the rules according to naval architecture. But there may be ineffectiveness in the use of raw materials such as a lot of wasted wood volume. This research was conducted to know the types of wood and equipment used for traditional shipbuilding and know the process of traditional shipbuilding. This research used a survey method and data was collected by interviewing and observation. This research is located in the Kutaraja Ocean Fishery Port, Banda Aceh conducted from March to April 2021. The results showed that the types of wood commonly used as raw materials for shipbuilding in traditional shipyards were bangkirai wood (Shore Laevifolia Endert), laban wood (Vitex Punesceus Vahl), balau wood (Hopea Calebica Burck), meranti merah wood (Shorea Acuminata Dyer), tembusu wood (Fagraea Fragrans Roxb), bungur wood (Lagerstroemia Speciosa Pers), and merbau wood (Intsia Bijuga). The equipment used still uses non-electronic equipment, only drill work that uses electricity. Meanwhile, the traditional shipbuilding process generally begins with laying the keel and installing the crest. Next, continued by frames installation, hull plank then upper hull main frame. Hereinafter, deck floor installation, hatches manufacture, and superstructure construction. The final stage of shipbuilding process is machining, painting, installing engines, propellers, and steering. Thus it can be said that the construction of a fishing vessel in Lampulo still traditionally a hereditary habits.

Bioenergy yield of Eucalyptus urophylla clones and its relationship with the mean annual increment of wood volume

This study aimed to evaluate the energy yield and wood characteristics of Eucalyptus urophylla clones with different mean annual increment of wood volume (MAI). The clones presented MAIs of 39.2, 54.1 and 70.0 m3 ha-1 yr-1 in the field experiment at six years after planting when the trees were cut down to evaluate the wood basic density and higher heating values. The energy density, dry mass and energy yield were estimated. The MAI of E. urophylla clones influenced the wood basic density, dry mass, and energy yield, but did not influence the higher heating value and energy density. Clone 3 had the highest MAI, and also had higher energy yield and dry mass, but lower wood basic density. The difference between the most and the least productive clones was 242,648 MJ ha-1 yr-1. The results reinforce the importance of evaluating the wood quantity production (MAI) to select Eucalyptus clones for energy purposes.

Simulação de redes neurais artificiais para estimativa de volume de madeira florestal a partir do DAP / Simulation of artificial neural networks for estimation of forest wood volume from DAP

O inventário florestal usa a altura (H) e o diâmetro na altura do peito (DAP) para determinação do volume de madeira. O grande problema é ajustar equações hipsométricas adequadas para estimar a altura. As equações são testadas e avaliadas por critérios estatísticos. A medição de alturas em povoamentos florestais é uma atividade onerosa, uma vez que, em comparação com a medição do diâmetro, sua obtenção não é fácil. Uma alternativa promissora consiste no uso de redes neurais artificiais (RNA), sistemas computacionais paralelos constituídos por unidades de processamento simples conectadas entre si de maneira específica para desempenhar determinada tarefa. Diante disso, o trabalho propõe usar técnicas de inteligência artificial para estimação do volume de madeira em uma floresta usando somente o DAP. Baseado em dados da literatura (Pesquisa: Modelos para quantificação do volume de diferentes sortimentos em plantio de Eucalyptus urophylla X Eucalyptus grandis.), foram gerados dados aleatórios de H e DAP entre o mínimo do DAP e H, 2,0 cm e 4,4 m, e o máximo, 28,9 cm e 32,9 m, respectivamente, no Excel. A partir desses dados, calculou-se o volume estimado de madeira pela fórmula de Takata (H e DAP), escolhida entre outros modelos por apresentar baixo erro-padrão da estimativa, além do baixo erro-padrão da estimativa em percentagem (Syx%), o modelo de Takata tem apresentado um alto coeficiente de determinação no inventario de fazendas de eucalipto. Sendo assim, este modelo se mostrou ligeiramente superior aos demais, tornando-se o mais adequado para estimativa da variável volume total em povoamentos de Eucalyptus urograndis, em Brasília. A partir dos dados treinou-se uma rede neural artificial (RNA) utilizando como variável contínua de entrada o DAP e de saída o volume calculado pela equação de Takata. A rede neural foi obtida pelo software PYTHON usando a função MLPRegressor (verbose=True, max_iter=10000, hidden_layer_sizes=(n)). Com isso foram testadas várias redes neurais artificiais para realizar a regressão entre volume de madeira calculado pela equação de Takata e DAP, e a melhor Rede Neural Artificial foi com 10 neurônios na camada oculta, apresentou r=0,99. A RNA é uma ferramenta do machine learning para o inventario florestal na determinação do volume de madeira a partir do DAP, principalmente quando já se tem banco de dados.