Modelling and prediction of wind damage in forest ecosystems of the Sudety Mountains, SW Poland

Windstorms are one of the most important disturbance factors in European forest ecosystems. An understanding of the major drivers causing observed changes in forests is essential to improve prediction models and as a basis for forest management. In the present study, we use machine learning techniques in combination with data sets on tree properties, bioclimatic and geomorphic conditions, to analyse the level of forest damage by windstorms in the Sudety Mountains over the period 2004-2010. We tested four scenarios under five classification model frameworks: logistic regression, random forest, support vector machines, neural networks, and gradient boosted modelling. Gradient boosted modelling and random forest have the best predictive power. Tree volume and age are the most important predictors of windstorm damage; climate and geomorphic variables are less important. Forest damage maps based on forest data from 2020 show lower probabilities of damage compared to the end of 20th and the beginning of 21st century.

Evaluation of Abiotic Controls on Windthrow Disturbance Using a Generalized Additive Model: A Case Study of the Tatra National Park, Slovakia

Windthrows are the most important type of disturbance occurring in the forests of Central Europe. On 19 November 2004, the strong northeastern katabatic winds caused significant damage and land cover change to more than 126 km2 of spruce forests in the Tatra National Park. The risk of subsequent soil erosion and accelerated runoff has increased in the affected habitats. Similar situations may reoccur this century as a consequence of climate change. A geographical approach and detailed research of the damaged area with more comprehensive statistical analyses of 47 independent variables will help us to obtain a deeper insight into the problem of windthrow disturbances. The results are based on a detailed investigation of the damaged stands, soil, and topography. A comprehensive input dataset enabled the evaluation of abiotic controls on windthrow disturbance through the use of a generalized additive model (GAM). The GAM revealed causal linear and nonlinear relationships between the local dependent quantitative variables (the damage index and the uprooting index) and independent variables (various soil and topography properties). Our model explains 69% of the deviance of the total damage. The distribution of the wind force depended upon the topographical position—mainly on the distance from the slope’s foot lines. The soil properties (mainly the soil skeleton, i.e., rock fragments in stony soils) affect the rate and manner of damage (uprooting), especially on sites with less wind force. Stem breakage with no relation to the soil prevailed in places with high force winds. The largest number of uprooted trees was recorded in localities without a soil skeleton. The spruce’s waterlogged shallow root system is significantly prone to uprooting. The comprehensive research found a significant relationship between the abiotic variables and two different measures of forest damage, and can expand the knowledge on wind impact in Central European forests.

Long-term exposure to more frequent disturbances increases baseline carbon in some ecosystems: Mapping and quantifying the disturbance frequency-ecosystem C relationship

Disturbance regimes have a major influence on the baseline carbon that characterizes any particular ecosystem. Often regimes result in lower average regional baseline C (compared to those same systems if the disturbance processes were lessened/removed). However, in infrequently disturbed systems the role of disturbance as a “background” process that influences broad-scale, baseline C levels is often neglected. Long-term chronosequences suggest disturbances in these systems may serve to increase regional biomass C stocks by maintaining productivity. However, that inference has not been tested spatially. Here, the large forested system of southeast Alaska, USA, is utilized to 1) estimate baseline regional C stocks, 2) test the fundamental disturbance-ecosystem C relationship, 3) estimate the cumulative impact of disturbances on baseline C. Using 1491 ground points with carbon measurements and a novel way of mapping disturbance regimes, the relationship between total biomass C, disturbance exposure, and climate was analyzed statistically. A spatial model was created to determine regional C and compare different disturbance scenarios. In this infrequently disturbed ecosystem, higher disturbance exposure is correlated with higher biomass C, supporting the hypothesis that disturbances maintain productivity at broad scales. The region is estimated to potentially contain a baseline 1.21–1.52 Pg biomass C (when unmanaged). Removal of wind and landslides from the model resulted in lower net C stocks (-2 to -19% reduction), though the effect was heterogeneous on finer scales. There removal of landslides alone had a larger effect then landslide and wind combined removal. The relationship between higher disturbance exposure and higher biomass within the broad ecosystem (which, on average, has a very low disturbance frequency) suggest that disturbances can serve maintain higher levels of productivity in infrequently disturbed but very C dense ecosystems. Carbon research in other systems, especially those where disturbances are infrequent relative to successional processes, should consider the role of disturbances in maintaining baseline ecosystem productivity.

The Long-Term Effects of Wind Disturbance on a Sitka Spruce-Western Hemlock Forest

Wind is an important disturbance in many forested regions, but research has largely focused on immediate to short-term (<10 years) effects on species composition and structure of stands and landscapes. We used a set of ten, 0.4-ha plots established in 1935 and measured every 5–13 years to examine the cumulative effects of multiple wind disturbance events in the coastal forests of Oregon. Since 1935 there have been ten documented wind events in coastal Oregon with hurricane-force winds. Most of the eight windstorms since 1962 noticeably influenced at least one plot; however, no individual storm clearly influenced all plots. Net rate of biomass accumulation of plots was negative when biomass mortality exceeded 29–41 Mg/ha per 5-year period (or 3.4%–5.8% per 5 years). In contrast, wind disturbance did not clearly reduce NPP (Net Primary Production) in any plot until biomass mortality exceeded 50%. Major wind-related mortality episodes in individual plots did not necessarily strongly influence the average loss of biomass across all plots. For example, a biomass loss of 88% in one plot resulted in an average loss of only 3.4% across all plots. In contrast, the cumulative effect of multiple plots with repeated wind-related mortality did decrease biomass at the multi-plot level. Depending on the plot, wind caused 16%–59% of the total mortality over time, and the proportion of wind-related mortality has increased 5- to 8-fold since 1940. The majority (80%) of wind-related mortality was “immediate”, but some trees survived up to 35 years after being significantly wind damaged. Despite western hemlock having a wind-related mortality rate that was at least twice that of Sitka spruce, the number of stems of the former species increased over time. This trend may be related to the predominant recovery mechanism which was the release of existing small trees and the fact that the majority of ingrowth was western hemlock. This study suggests that wind disturbance is a heterogeneous, gradual process and that while individual events have a detectable impact on structure and function, the largest impacts, at least in systems where it reoccurs each decade, are cumulative.

Using climate envelope models to identify potential ecological trajectories on the Kenai Peninsula, Alaska

Managers need information about the vulnerability of historical plant communities, and their potential future conditions, to respond appropriately to landscape change driven by global climate change. We model the climate envelopes of plant communities on the Kenai Peninsula in Southcentral Alaska and forecast to 2020, 2050, and 2080. We assess 6 model outputs representing downscaled climate data from 3 global climate model outputs and 2 representative concentration pathways. We use two lines of evidence, model convergence and empirically measured rates of change, to identify the following plausible ecological trajectories for the peninsula: (1.) alpine tundra and sub-alpine shrub decrease, (2.) perennial snow and ice decrease, (3.) forests remain on the Kenai Lowlands, (4.) the contiguous white-Lutz-Sitka spruce complex declines, and (5.) mixed conifer afforestation occurs along the Gulf of Alaska coast. We suggest that converging models in the context of other lines of evidence is a viable approach to increase certainty for adaptation planning. Extremely dynamic areas with multiple outcomes (i.e., disagreement) among models represent ecological risk, but may also represent opportunities for facilitated adaptation and other managerial approaches to help tip the balance one way or another. By reducing uncertainty, this eclectic approach can be used to inform expectations about the future.

Complex mountain terrain and disturbance history drive variation in forest aboveground live carbon density in the western Oregon Cascades, USA

Forest carbon (C) density varies tremendously across space due to the inherent heterogeneity of forest ecosystems. Variation of forest C density is especially pronounced in mountainous terrain, where environmental gradients are compressed and vary at multiple spatial scales. Additionally, the influence of environmental gradients may vary with forest age and developmental stage, an important consideration as forest landscapes often have a diversity of stand ages from past management and other disturbance agents. Quantifying forest C density and its underlying environmental determinants in mountain terrain has remained challenging because many available data sources lack the spatial grain and ecological resolution needed at both stand and landscape scales. The objective of this study was to determine if environmental factors influencing aboveground live carbon (ALC) density differed between young versus old forests. We integrated aerial light detection and ranging (lidar) data with 702 field plots to map forest ALC density at a grain of 25 m across the H.J. Andrews Experimental Forest, a 6369 ha watershed in the Cascade Mountains of Oregon, USA. We used linear regressions, random forest ensemble learning (RF) and sequential autoregressive modeling (SAR) to reveal how mapped forest ALC density was related to climate, topography, soils, and past disturbance history (timber harvesting and wildfires). ALC increased with stand age in young managed forests, with much greater variation of ALC in relation to years since wildfire in old unmanaged forests. Timber harvesting was the most important driver of ALC across the entire watershed, despite occurring on only 23% of the landscape. More variation in forest ALC density was explained in models of young managed forests than in models of old unmanaged forests. Besides stand age, ALC density in young managed forests was driven by factors influencing site productivity, whereas variation in ALC density in old unmanaged forests was also affected by finer scale topographic conditions associated with sheltered sites. Past wildfires only had a small influence on current ALC density, which may be a result of long times since fire and/or prevalence of non-stand replacing fire. Our results indicate that forest ALC density depends on a suite of multi-scale environmental drivers mediated by complex mountain topography, and that these relationships are dependent on stand age. The high and context-dependent spatial variability of forest ALC density has implications for quantifying forest carbon stores, establishing upper bounds of potential carbon sequestration, and scaling field data to landscape and regional scales.

Spatial and topographic trends in forest expansion and biomass change, from regional to local scales

Natural forest growth and expansion are important carbon sequestration processes globally. Climate change is likely to increase forest growth in some regions via CO2 fertilization, increased temperatures, and altered precipitation; however, altered disturbance regimes and climate stress (e.g. drought) will act to reduce carbon stocks in forests as well. Observations of asynchrony in forest change is useful in determining current trends in forest carbon stocks, both in terms of forest density (e.g. Mg ha(-1) ) and spatially (extent and location). Monitoring change in natural (unmanaged) areas is particularly useful, as while afforestation and recovery from historic land use are currently large carbon sinks, the long-term viability of those sinks depends on climate change and disturbance dynamics at their particular location. We utilize a large, unmanaged biome (>135 000 km(2) ) which spans a broad latitudinal gradient to explore how variation in location affects forest density and spatial patterning: the forests of the North American temperate rainforests in Alaska, which store >2.8 Pg C in biomass and soil, equivalent to >8% of the C in contiguous US forests. We demonstrate that the regional biome is shifting; gains exceed losses and are located in different spatio-topographic contexts. Forest gains are concentrated on northerly aspects, lower elevations, and higher latitudes, especially in sheltered areas, whereas loss is skewed toward southerly aspects and lower latitudes. Repeat plot-scale biomass data (n = 759) indicate that within-forest biomass gains outpace losses (live trees >12.7 cm diameter, 986 Gg yr(-1) ) on gentler slopes and in higher latitudes. This work demonstrates that while temperate rainforest dynamics occur at fine spatial scales (<1000 m(2) ), the net result of thousands of individual events is regionally patterned change. Correlations between the disturbance/establishment imbalance and biomass accumulation suggest the potential for relatively rapid biome shifts and biomass changes.

Use of historical logging patterns to identify disproportionately logged ecosystems within temperate rainforests of southeastern Alaska

The forests of southeastern Alaska remain largely intact and contain a substantial proportion of Earth's remaining old-growth temperate rainforest. Nonetheless, industrial-scale logging has occurred since the 1950s within a relatively narrow range of forest types that has never been quantified at a regional scale. We analyzed historical patterns of logging from 1954 through 2004 and compared the relative rates of change among forest types, landform associations, and biogeographic provinces. We found a consistent pattern of disproportionate logging at multiple scales, including large-tree stands and landscapes with contiguous productive old-growth forests. The highest rates of change were among landform associations and biogeographic provinces that originally contained the largest concentrations of productive old growth (i.e., timber volume >46.6 m³/ha). Although only 11.9% of productive old-growth forests have been logged region wide, large-tree stands have been reduced by at least 28.1%, karst forests by 37%, and landscapes with the highest volume of contiguous old growth by 66.5%. Within some island biogeographic provinces, loss of rare forest types may place local viability of species dependent on old growth at risk of extirpation. Examination of historical patterns of change among ecological forest types can facilitate planning for conservation of biodiversity and sustainable use of forest resources.

Mapping threats to power line corridors for Connecticut rights-of-way management

Trees are a major threat to power line security across forested regions of the world. We developed a decision support system for identifying locations in Connecticut, USA where trees have grown tall enough to make contact with transmission lines during storms. We used the Random Forest algorithm, danger tree presence/absence data, and 25 raster environmental datasets to develop (1) an understanding of the abiotic environmental settings that host danger trees and (2) a spatially explicit map of danger tree distributions across Connecticut power line corridors. Danger trees were prevalent in locations (1) with an infrequent history of storms; (2) forested and residential land uses; and (3) low to middle elevations. Products from this research can be transferred to adaptive right-of-way management because they present managers with key information on where danger trees are likely to occur, and the methods presented herein have great potential for future application to other regions managers seek to identify high priority areas for danger tree removal.

Disturbance and landscape dynamics in a changing world

Disturbance regimes are changing rapidly, and the consequences of such changes for ecosystems and linked social-ecological systems will be profound. This paper synthesizes current understanding of disturbance with an emphasis on fundamental contributions to contemporary landscape and ecosystem ecology, then identifies future research priorities. Studies of disturbance led to insights about heterogeneity, scale, and thresholds in space and time and catalyzed new paradigms in ecology. Because they create vegetation patterns, disturbances also establish spatial patterns of many ecosystem processes on the landscape. Drivers of global change will produce new spatial patterns, altered disturbance regimes, novel trajectories of change, and surprises. Future disturbances will continue to provide valuable opportunities for studying pattern-process interactions. Changing disturbance regimes will produce acute changes in ecosystems and ecosystem services over the short (years to decades) and long-term (centuries and beyond). Future research should address questions related to (1) disturbances as catalysts of rapid ecological change, (2) interactions among disturbances, (3) relationships between disturbance and society, especially the intersection of land use and disturbance, and (4) feedbacks from disturbance to other global drivers. Ecologists should make a renewed and concerted effort to understand and anticipate the causes and consequences of changing disturbance regimes.