Down dead wood in a montane beech forest stands on Deshat Mountain. 5. Impact of forestry management practices

Forest management effects on downed dead wood at stand and landscape scales in a temperate forest of the central United States

Down dead wood DDW is important for its role in carbon and nutrient cycflng carbon sequestration wildfire behavior plant reproduction and wildlife habitat.Down dead wood was measured for the first time during forest swvey of Maine by the USDA Forest SaMoa in 19941996 Pieces greater than feet long and greater than3 inches diameter at point of intersection were measured on line transects located on.standard forest nventor plota.Large piles of DOW were sampled using the standard circularplot.Results are presented in 50 tables containing totals aod peE area estimates for volume numbeE of pieces biomass and carbon sumnarized by attributes such as forest type group owner group species and diameter class.Ths inventory indicates Maine timberlands contain approximately 723% billion cubic feet in DOW pieces and an additional .628% billion cubic feet in piles of DDW.Together these contain 68.9 billion pounds 8% of carbon.This is equivalent to an average of approximately 8030 pounds of DOW biornass per acre.

Downed dead wood (DDW) in forest ecosystems is a C pool whose net flux is governed by a complex of natural and anthropogenic processes and is critical to the management of the entire forest C pool. As empirical examination of DDW C net flux has rarely been conducted across large scales, the goal of this study was to use a remeasured inventory of DDW C and ancillary forest attributes to assess C net flux across forests of the Eastern US. Stocks associated with large fine woody debris (diameter 2.6-7.6 cm) decreased over time (-0.11 Mg ha(-1) year(-1)), while stocks of larger-sized coarse DDW increased (0.02 Mg ha(-1) year(-1)). Stocks of total DDW C decreased (-0.14 Mg ha(-1) year(-1)), while standing dead and live tree stocks both increased, 0.01 and 0.44 Mg ha(-1) year(-1), respectively. The spatial distribution of DDW C stock change was highly heterogeneous with random forests model results indicating that management history, live tree stocking, natural disturbance, and growing degree days only partially explain stock change. Natural disturbances drove substantial C transfers from the live tree pool (≈-4 Mg ha(-1) year(-1)) to the standing dead tree pool (≈3 Mg ha(-1) year(-1)) with only a minimal increase in DDW C stocks (≈1 Mg ha(-1) year(-1)) in lower decay classes, suggesting a delayed transfer of C to the DDW pool. The assessment and management of DDW C flux is complicated by the diversity of natural and anthropogenic forces that drive their dynamics with the scale and timing of flux among forest C pools remaining a large knowledge gap.

The quantity and condition of downed dead wood (DDW) is emerging as a major factor governing forest ecosystem processes such as carbon cycling, fire behavior, and tree regeneration. Despite this, systematic inventories of DDW are sparse if not absent across major forest biomes. The Forest Inventory and Analysis program of the United States (US) Forest Service has conducted an annual DDW inventory on all coterminous US forest land since 2002 (~1 plot per 38,850 ha), with a sample intensification occurring since 2012 (~1 plot per 19,425 ha). The data are organized according to DDW components and by sampling information which can all be linked to a multitude of auxiliary information in the national database. As the sampling of DDW is conducted using field efficient line-intersect approaches, several assumptions are adopted during population estimation that serve to identify critical knowledge gaps. The plot- and population-level DDW datasets and estimates provide the first insights into an understudied but critical ecosystem component of temperate forests of North America with global application.

Due to global change, temperate forests are expected to face growing threats to forest health (e.g. insects/disease) and increasing probabilities of severe disturbances (e.g. wildfires), which may result in amplified tree mortality against a backdrop of a changing climate and associated ecosystem/atmospheric feedbacks (i.e. increased rates of dead wood decay/combustion). Despite these expectations, we lack a fundamental understanding of current forest biomass trends among live and dead components across large spatial and temporal domains. The goal of this study was to examine changes in forest biomass components (downed dead wood (DDW), standing dead trees (SDs), and live trees) across coterminous US forests using a nation-wide, multi-decade (∼2006–2010 to ∼2015–2019) repeated forest inventory at the scale of regional ecosystems. It was found that the total biomass stocks of DDW, standing dead, and live trees all increased (18.3%, 14.7%, and 3.9%, respectively) with biomass accumulation in large live trees coupled with increases in the biomass of smaller sized down dead wood illustrating the influence of stand development across US forests at the scale of individual forest ecosystems (i.e. self-thinning). Coupled with this observation, tremendous positive skew of biomass change across all biomass components and size classes demonstrates the ability of severe but episodic disturbance events to produce substantial biomass inputs to SD and DDW pools with legacy effects exceeding the period of this study. Overall, against a backdrop of expected future global change and growing interest in the maintenance of the terrestrial forest carbon pool, the incorporation of dead wood-focused analytics such as decay-related functional traits, microbial/fungal community assessments, or dead/live biomass relationships into broader forest carbon/biomass monitoring efforts is essential.

In natural forest ecosystems, there is often abundant down dead wood (DDW) due to wind disasters, which greatly changes the size and structure of forests. Accurately determining the DDW volume (DDWV) is crucial for sustaining forest management, predicting the dynamic changes in forest resources and assessing the risks of natural disasters or disturbances. However, existing models cannot accurately express the significant spatial nonstationarity or complexity in their spatial relationships. To this end, we established a geographically weighted deep neural network (GWDNN) model that constructs a spatially weighted neural network (SWNN) through geographic location data and builds a neural network through stand factors and remote sensing factors to improve the interpretability of the spatial model of DDWV. To verify the effectiveness of this method, using 2019 data from Liangshui National Nature Reserve, we compared model fit, predictive ability and residual spatial autocorrelation among the GWDNN model and four other spatial models: an ordinary least squares (OLS) model, a linear mixed model (LMM), a geographically weighted regression (GWR) model and a deep neural network (DNN) model. The experimental results show that the GWDNN model is far superior to the other four models according to various indicators; the coefficient of determination R2, root mean square error (RMSE), mean absolute error (MAE), Moran’s I and Z-statistic values of the GWDNN model were 0.95, 1.05, 0.77, -0.01 and -0.06, respectively. In addition, compared with the other models, the GWDNN model can more accurately depict local spatial variations and details of the DDWV in Liangshui National Nature Reserve.

To comply with the demands of the Kyoto Protocol, industrialized countries must reliably estimate the stored carbon (C) in different pools of forest ecosystems. The main objective of this study was to quantify the biomass, C and nutrients stocks in the forest floor, understory, downed dead wood (DDW) and mineral soil of even-aged maritime pine (Pinus pinaster Ait.) stands from three contrasting regions of Portugal. Assessing the specific contribution of DDW to the C and nutrients stocks and how C concentration in the plant material differs from 0.50, the reference value used in many practical applications, were also objectives of this research. Biomass content of forest floor was determined by a quadrat method. Sampling units of 1 m2 were used for the understory. The line intersection method was adopted for sampling DDW and the mineral soil was sampled at three depths. Concentrations of C and nutrients were obtained by chemical analysis of samples from soil and milled plant material. Biomass and C in the trees were obtained using published equations. Total C stocks ranged between 100.6 Mg ha–1 and 308.6 Mg ha–1. Mineral soil shared up to 70-74% of global stored C, being the main cause of the global C stock differences among regions. Phosphorous and potassium were at low to very low levels in the mineral soil and plant material. The contribution of DDW to the C and nutrients pools was negligible. The percentage of C in the plant material ranged between 52% and 54%.

Characterization of coarse woody debris across a 100 year chronosequence of upland oak–hickory forests

Forest management prescriptions increasingly incorporate snag and downed dead wood (DDW) guidelines. This study utilizes permanent inventory plots to determine dead wood dynamics in 33 balsam fir ( Abies balsamea (L.) Mill.) – spruce ( Picea spp.) (BFSP) and 17 spruce – balsam fir (SPBF) stands in New Brunswick, Canada. Stands were declining, unmanaged, and had a history of recurrent spruce budworm ( Choristoneura fumiferana (Clem.)) outbreaks and aerial insecticide spraying. Fixed-area sampling matched remnants of 1165 dead trees and 864 corresponding pieces of DDW to plot trees that died over the last 15–18 years with known year and cause of death. Declining BFSP stands had the highest accumulation of dead wood (196 m3/ha) compared with SPBF and nondeclining BFSP (122 m3/ha and 77 m3/ha, respectively). Dead wood dynamics were influenced by cause of death, as a function of differences in tree height at death affecting snag decay, fragmentation, and fall. One-half of all dead trees never made a significant contribution to the snag population (25% uprooted and 25% stem breakage), and attrition resulted in only 50% of snags standing with a mean height of 6 m 15–20 years after death. This study will be of direct value to those managing or modeling dead wood dynamics in similar forests.

Learning from a “benign neglect strategy” in a national park: Response of saproxylic beetles to dead wood accumulation

Natural amounts of dead wood in a forest vary considerably, depending on living tree biomass, decomposition rates, and rates of dead-wood development. In natural forests, dead wood is created by the senescence of trees and natural disturbances. However, dead-wood amounts in many forest ecosystems worldwide nowadays are largely influenced by human activities, such as timber and fuel wood production and post-disturbance salvage logging. The biodiversity of saproxylic insects is usually positively correlated with the amount of dead wood, and dead-wood amount affects species composition and functional characteristics of saproxylic assemblages. Dead-wood amount is in turn correlated with dead-wood diversity, and several studies highlight the importance of dead-wood diversity for saproxylic biodiversity, which suggests that habitat heterogeneity is a major driver behind the positive relationship between dead-wood amount and biodiversity. The strength of this relationship is mediated by temperature. Effects of both temporal forest continuity and spatial connectivity are often linked to differences in dead-wood amount. Frequent interactions and correlations between dead-wood amount and other habitat factors indicate that future studies should aim more precisely at unraveling the importance of individual factors for saproxylic biodiversity, which will help to improve conservation strategies to counteract negative effects of anthropogenically altered dead-wood amount and diversity. Such conservation strategies, particularly in Europe and North America, include passive and active measures to retain dead wood in managed forests and to restore amounts and diversity of dead wood similar to levels in natural forests. More research is needed in the subtropics and tropics where conservation strategies rarely consider dead wood, although the few existing studies suggest that dead wood is an important factor for biodiversity in these regions.

Xishuangbanna, located in south Yunnan, southwest China, is the northern border of the tropical zone. It maintains large areas of tropical rainforest called tropical seasonal rainforest. Like most tropical rainforests all over the world, these tropical seasonal rainforests are under high pressure of long_term disturbance caused by forest utilization. Amomum villosum, a shade_tolerant perennial herb, prefers to grow in forest gaps. It is one of the main cash crops of local people as its fruit is widely used in Chinese traditional medicine. It has been widely planted in tropical seasonal rainforest understorey in Xishuangbanna. To promote its growth and fruit yield by raising the light level of habitat, the forest shrub and herb layers are cleaned and about 60% 70% of trees are thinned. As a result, A. villosum planting has become the most serious disturbance to the tropical seasonal rainforest. Net primary productivity ( NPP ) is the primary element of nutrient cycling and energy flow within an ecosystem. It reflects the ability of a plant community to use natural resources. Most of the studies on forest NPP change after disturbance have focused on secondary forest, and few studies report the impact on NPP of forest canopy damage. This paper aims to determine the effect of A. villosum planting on forest NPP , and to study if that disturbance is the current most important limiting factor on NPP of the rainforest in Xishuangbanna. The study was carried out at Menglun, Xishuangbanna. Three primary seasonal rainforest sites and three disturbed rainforest sites with A. villosum plantation were chosen for the study and one 0.25 hm 2 plot was established at each site. All six study sites were distributed along ravines, within 21°55′ 21°59′N,101°08′ 101°13′E and at altitude of 650 800 m. Pometia tomentosa is the dominant tree species of the top tree layers at all research sites. At each plot, all trees and lianas with diameter at breast height ( DBH ) ≥5 cm were numbered and marked at breast height, and their DBH were measured annually. The biomass ( B ) and its annual increment ( ΔB ) of the research plots was estimated using the allometric regression equation relating tree mass to DBH of Xishuangbanna tropical rainforest. The amount of dead wood on all plots was recorded annually. At the same time, 20 litter fall traps were placed at each plot and litter was collected every half month. Leaf herbivory was measured by leaf samples and the total leaf herbivory ( G ) was estimated through annual leaf litterfall. The primary net productivity was calculated using the NPP equation NPP = ΔB+L+G, in which L is annual litterfall together with dead wood. The shrub and herb biomass were determined by the harvest method and their biomass increment was estimated by biomass divided by age. The biomass increment for shrub and herb was approximate to NPP . The results show that the annual mean NPP (mean±SE) of the primary rainforest is 23.47±2.12 t·hm -2 ·a -1 , with 22.04±2.09 t·hm -2 ·a -1 in the tree layer, 0.75±0.08 t·hm -2 ·a -1 in the shrub layer, 0.43±0.05 t·hm -2 ·a -1 in woody liana and 0.25±0.03 t·hm -2 ·a -1 in the herb layer. The allocation of NPP of the tree layer was: for litterfall, 11.75±0.54 t·hm -2 ·a -1 ; for tree fall, 0.62±0.21 t·hm -2 ·a -1 ; for leaf herbivory, 0.66±0.05 t·hm -2 ·a -1 ; and for biomass accumulation, 9.01±2.70 t·hm -2 ·a -1 . Compared to the primary rainforest, the NPP of the tree layer, shrub layer, woody liana and total community of the disturbed rainforest decreased 26.1%, 65.7%, 86.1% and 22.5% respectively, but the herb NPP increased 536% because of the dominance of A. villosum. Similarly, litterfall and biomass accumulation of the tree layer decreased 25.5% and 53.4% respectively. The tree fall increased 356% relative to the primary forest due to the change of microenvironment after disturb

To prevent local species extinction and to counteract population declines, we must ensure species have access to resources they require for life. This can be done through ecological restoration where previously depleted resources are reintroduced. If the restoration is conducted as a one‐off action in a large area, it resembles a natural resource pulse, which should lead to increased abundance of individuals, accompanied possibly by increased species richness. Species–energy relationship and underlying theory enable predictions about how different features of resource pulses affect species richness. We conducted a large‐scale, controlled, randomized and replicated field experiment to study the effect of a resource addition on polypore species richness in a previously managed boreal forest landscape in Finland. We manipulated the amount and distribution of dead wood and studied the effects on polypore assemblages on added and natural dead wood during 9 years after manipulation (2004–2012). By adding dead wood, species richness grew, mainly through increasing abundances: a large amount of dead wood resulted in higher abundance, higher number and faster accumulation of species than a small amount of dead wood. For a given abundance, dead wood addition contained fewer species than natural dead wood. This is most probably because added dead wood was of low diversity and provided habitat only for a limited number of species. Species richness on natural dead wood increased substantially during the study period, and this increase was not related to the resource manipulation. Thus, habitat improvement through natural succession can occur within a relatively short time period irrespective of human intervention. Synthesis and applications. We demonstrate how the introduction of dead wood additions can strengthen polypore populations. The species taking advance of the introduced resource were primarily common species, instead of rare or red‐listed species. Thus, we recommend ensuring the natural formation of dead wood while the populations of the common species supporting ecosystem functions can be increased by adding dead wood in the landscape.

Effect of dead wood enrichment in the canopy and on the forest floor on beetle guild composition

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.