Disturbance Agents Research Articles

Poleward migration of tropical cyclones induced severe disturbance of boreal forest above 50°

With global warming, tropical cyclones (TCs) are moving to northern latitudes with devastating effects on boreal forests and significant ecological and socioeconomic consequences in the northern hemisphere. Recently, TCs disturbances have been documented in the northern temperate and even the southern boreal forest zone. Here we report and quantify the impact of TC Lingling (2019), which damaged the boreal forests >50° latitude in a remote area of Sakhalin Island, Northeast Asia. A multi-step algorithm was used to identify disturbed forested areas together with Sentinel-2 imagery to recognize windthrow patches caused by TCs and evaluate tree species composition. We found extensive damage to boreal forests caused by TC Lingling, with forested area losses of >80 km2. The affected areas mainly belonged to zonal dark coniferous forests, which account for 54 km2 of windthrows. In contrast, a lower impact was recorded in deciduous broadleaf and larch forests. TC Lingling caused a high proportion (>50 %) of large gaps (>10 ha), however, gaps of such extent have not been previously recorded in these dark coniferous forests. Hence, our study highlights the potential of TCs as the new disturbance agent responsible for extensive disturbances of boreal forests at more northern latitudes than previously thought. This implies the significant role of TCs in disturbance regimes and boreal forest dynamics. We suggest that continued poleward migration of TCs may lead to an unprecedentedly large area of disturbed boreal forests resulting in complex changes in diversity and ecosystem functioning. Our findings are crucial for identifying potential shifts in boreal forest structure and dynamics under ongoing global climate change and altered forest disturbance regimes.

Ecological factors affecting the recent Picea abies decline in Slovenia: the importance of bedrock type and forest naturalness

Norway spruce (Picea abies [L.] Karst.) has been at the centre of controversy for many decades. Recent evidence of its profound disturbance-induced damage and consequent stock depletions across forest landscapes in Europe has reinforced doubts regarding the sustainability and prospects of this tree species in the future. Like many other European countries, Slovenia has experienced significant Norway spruce mortality and a decrease in growing stock primarily as the result of several disturbance agents (bark beetle outbreaks, an ice storm, windthrows). We investigated a countrywide spruce growing stock decline based on data between 2010 and 2018. Particular focus was placed on identifying the main ecological drivers of this decline, namely geological conditions, climatic parameters, soil attributes, topographic factors and forest stand characteristics. The effects of potential predictors on the relative change (%) in spruce volume (m3 ha-1) during the period 2010-2018 were analysed with Generalized Additive Models. Based on a national dataset including forest compartments (n = 6355) with a spruce growing stock decline > 10%, we found mixed support for ecology-based hypotheses. While spruce decline responded to bedrock type as predicted (i.e., greater relative decline in carbonate compared to silicate compartments), higher forest naturalness (preservation of tree species composition) was not associated with a lower decline. Spruce decline was amplified by higher potential evapotranspiration and soil clay content but showed a strong negative relationship with spruce proportion in the year 2010. General trends along the gradients of other selected predictors (stoniness/rockiness and heat load index) were less pronounced. The results suggest that most of these ecological predictors interact with geology and forest naturalness in affecting Norway spruce decline. Our analysis reveals that bedrock type can play an important role due to its mitigating effects. However, forest naturalness is of secondary significance as intensified large-scale forest disturbances likely override its buffering potential.

Linking disturbance history to current forest structure to assess the impact of disturbances in tropical dry forests

Tropical dry forests are widespread, harbour vast amounts of carbon and unique biodiversity, and underpin the livelihoods of millions. A variety of natural and anthropogenic disturbances affect tropical dry forest canopy, yet our understanding of how these disturbances impact on forest structure and ecosystem functioning, and how forests develop after different disturbances, is partial. This translates into knowledge gaps regarding long-term outcomes of disturbances on forest structure as well as which of these outcomes signify recovery vs forest degradation. Here, we use a rich dataset of remotely-sensed, high-resolution forest indicators in a multilevel Bayesian regression framework to understand the effect of different disturbance agents (partial clearing, fire, logging, drought and riparian changes) on aboveground biomass, and woody cover in the Argentine Dry Chaco. Our models show that post-disturbance trajectories of forest structural indicators differ markedly among different disturbance agents. For example, riparian changes affected biomass most strongly but had the fastest recovery, whereas logging had a generally lower impact and mostly affected tree cover, but recovery was slow or never occurred. Importantly, even three decades after the disturbance event, woody cover and biomass exhibited higher values for natural disturbances compared to anthropogenic disturbances. Furthermore, anthropogenic disturbances had slower recovery rates than natural disturbances. Overall, our approach shows the potential of remote-sensing indicators and space-for-time substitution to unravel the diverse vegetation response of different disturbance agents. Given the high and rising human pressure on dry forests in the Chaco and globally, our findings also show the long-lasting effects that anthropogenic disturbances have on these valuable forests.

Uncovering Early Traces of Bark Beetle Induced Forest Stress via Semantically Enriched Sentinel-2 Data and Spectral Indices

Forest ecosystems are shaped by both abiotic and biotic disturbances. Unlike sudden disturbance agents, such as wind, avalanches and fire, bark beetle infestation progresses gradually. By the time infestation is observable by the human eye, trees are already in the final stages of infestation—the red- and grey-attack. In the relevant phase—the green-attack—biochemical and biophysical processes take place, which, however, are not or hardly visible. In this study, we applied a time series analysis based on semantically enriched Sentinel-2 data and spectral vegetation indices (SVIs) to detect early traces of bark beetle infestation in the Berchtesgaden National Park, Germany. Our approach used a stratified and hierarchical hybrid remote sensing image understanding system for pre-selecting candidate pixels, followed by the use of SVIs to confirm or refute the initial selection, heading towards a 'convergence of evidence approach’. Our results revealed that the near-infrared (NIR) and short-wave-infrared (SWIR) parts of the electromagnetic spectrum provided the best separability between pixels classified as healthy and early infested. Referring to vegetation indices, we found that those related to water stress have proven to be most sensitive. Compared to a SVI-only model that did not incorporate the concept of candidate pixels, our approach achieved distinctively higher producer’s accuracy (76% vs. 63%) and user’s accuracy (61% vs. 42%). The temporal accuracy of our method depends on the availability of satellite data and varies up to 3 weeks before or after the first ground-based detection in the field. Nonetheless, our method offers valuable early detection capabilities that can aid in implementing timely interventions to address bark beetle infestations in the early stage.

Adaptive Fuzzy Containment and Vibration Control for Multiple Flexible Manipulators With Model Uncertainties

This article investigates the cooperative vibration control problem for a flexible manipulator network with model uncertainties and boundary disturbances guided by multiple dynamic leaders. Different from the previous research on a single flexible manipulator, this article focuses on the containment control problem of multiple flexible manipulators. To this end, the boundary control algorithm is proposed for leader agents without disturbance and follower agents with disturbance and uncertainties. The fuzzy logic systems are applied to deal with uncertain and continuous functions in the system model. By constructing the appropriate Lyapunov function, not only the vibrations can be suppressed, but also the containment error between the convex hull spanned by the multiple leaders and all followers can be converged to zero by designing a distributed containment feedback control law. Furthermore, the control algorithm can ensure that all the signals in the closed-loop system are uniformity ultimately bounded; meanwhile, vibration amplitude and error converge to a small compact set. At last, the simulation results prove the effectiveness of the proposed control method.

Attributing a Causal Agent and Assessing the Severity of Non-Stand Replacing Disturbances in a Northern Hardwood Forest using Landsat-Derived Vegetation Indices

Non-stand-replacing disturbances are major drivers of northern hardwood forest dynamics, but are more challenging to characterize using satellite imagery than stand-replacing events. This study proposes a hurdle approach in which disturbance causal agents are first attributed to permanent sample plots that were either partially harvested, had sustained damage from an ice storm or remained undisturbed during the observation period, reaching an overall accuracy of 82.9%. Ordinary least square regression was then used to develop disturbance-specific models to assess the severity of partial harvests and damage from ice storms, with r-squared values of 0.57 and 0.59, respectively. The disturbance-specific models included a different set of predictors, confirming the importance of attributing a causal agent to a disturbance before assessing its severity. The sequence of models was implemented regionally to produce severity maps for two disturbance events, revealing within-stand variability in the severity that could be useful for the planning of future silvicultural actions. Although the proposed models offer acceptable performance, more research is needed to include additional disturbance agents and develop models that better capture the small variations in the spectral reflectance caused by low-severity disturbances, especially in the case of low-intensity partial harvests.

Lianas increase lightning-caused disturbance severity in a tropical forest.

Lightning is an important agent of plant mortality and disturbance in forests. Lightning-caused disturbance is highly variable in terms of its area of effect and disturbance severity (i.e. tree damage and death), but we do not know how this variation is influenced by forest structure and plant composition. We used a novel lightning detection system to quantify how lianas influenced the severity and spatial extent (i.e. area) of lightning disturbance using 78 lightning strikes in central Panama. The local density of lianas (measured as liana basal area) was positively associated with the number of trees killed and damaged by lightning, and patterns of plant damage indicated that this occurred because lianas facilitated more electrical connections from large to small trees. Liana presence, however, did not increase the area of the disturbance. Thus, lianas increased the severity of lightning disturbance by facilitating damage to additional trees without influencing the footprint of the disturbance. These findings indicate that lianas spread electricity to damage and kill understory trees that otherwise would survive a strike. As liana abundance increases in tropical forests, their negative effects on tree survival with respect to the severity of lightning-related tree damage and death are likely to increase.

Differentiating effects of salvage logging and recovery patterns on post-fire boreal forests in Northeast China using a modified forest disturbance index

ABSTRACT Forests are resilient to a range of disturbances, but combinations of severe natural and anthropogenic disturbances (e.g. wildfire and logging) may inhibit forest recovery and lead to forest degradation. Recent studies have explored long-term forest-disturbance detection and forest-recovery dynamics by using free and open-access remote-sensing images. However, mapping consecutive multiple disturbance agents is challenging using existing automated change-detection algorithms because the reduced canopy reflectance and the smoothing of consecutive disturbance signals mean that the initial disturbance cannot be spectrally separated from the second disturbance. Furthermore, uncertainty remains about post-disturbance vegetation dynamics and the effects of forest recovery under the interaction of burn severity, biological-legacy management, and active forest restoration (i.e. artificial regeneration and assisted natural regeneration). This contributes to biases in long-term forest-recovery monitoring, which are not conducive to the guidance of post-fire vegetation recovery. Here, we propose a modified disturbance index to separate the spectral characteristics of fire and forest logging using normalized tasseled-cap components (brightness and wetness) and detect the spatiotemporal distribution of post-fire logging by means of an index threshold and image differencing. On this basis, the recovery patterns of the post-fire forest are differentiated by considering the cumulative effect of fire, post-fire logging, and recovery approaches. The method is tested in the burn areas of the 5.6 Fire in the Greater Hinggan Mountain area (the largest forest fire in recorded history in China), giving an overall accuracy of 85% in post-fire forest logging mapping. Our results confirm that biological legacies (i.e. trees, logs, and snags) were removed across many areas in the fire, with activities peaking in the second year after the fire and located chiefly in areas of moderate and high burn severity. By identifying post-fire logging, the fluctuation and high disturbance index of the conventional temporal trajectory in the early stage of forest recovery are explained. The large-scale salvage logging slowed the recovery of the post-fire forest ecosystem and influenced the recovery process through the interaction of burn severity and active forest restoration. In areas of high burn severity, assisted natural regeneration (i.e. natural regeneration with artificial aids such as clearing the snags, weeding, digging pits, and supplemental planting) preserved biological legacies and achieved a higher proportion of forest recovery, second only to non-logged areas where natural regeneration (i.e. forestry recovering naturally without any artificial intervention) occurred. By contrast, salvage logging followed by artificial regeneration (i.e. clear-cutting all dead or damaged trees followed by tree planting or artificial seeding) hindered vegetation recovery in the early stage, but it improved the recovery rate in years 10–20 and approached the recovery proportion of non-logged areas where natural regeneration occurred as the recovery progressed and habitat conditions improved. The proposed method is shown to offer important advantages in detecting post-fire salvage logging, and it provides improved guidance for forest managers in developing strategies for forest recovery.

Natural disturbances as drivers of tipping points in forest ecosystems under climate change – implications for adaptive management

AbstractAs climate continues to change, disturbances may increasingly navigate forest ecosystems towards tipping points, causing irreversible state shifts and a loss of biodiversity and ecosystem services. In this review, I elaborate the Special Issue topic ‘Natural disturbances as tipping points of forest ecosystems under climate change’ featured by Forestry and suggest a suit of adaptive measures to mitigate increasing disturbances and their impacts on forest ecosystems. The Special Issue contains seven case studies assessing drought, fire, wind and bark beetle disturbances in Europe, North America and Africa. Despite high severities and/or frequencies, disturbances have not yet induced a shift of the investigated forest ecosystems towards an alternative state. Instead, forests have shown high resistance, resilience or both. For instance, one case study reveals that short-interval fires in European beech forests may not even significantly alter tree species composition due to the high resprouting ability of beech. Yet, other case studies identify distinct differences in resilience amongst ecoregions, and indicate that climate change and disturbance interactions might tip the future carbon balance of forests from sink to source. Many forest ecosystems are likely able to cope with future increases in disturbance activity to some degree. However, tipping points might vary across ecosystems dominated by different disturbance agents. While wind and bark beetles mainly affect canopy trees, fire and drought also directly impair tree regeneration, thus reducing the capacity of ecosystems to recover and reorganize. Hence, forest ecosystems in which fire and drought are the dominant disturbance agents might approach tipping points earlier than forests dominated by other agents if disturbance activity continues to increase. Several proactive and reactive adaptive measures are available to mitigate increasing disturbances, but more research is needed to develop robust and region-specific strategies to prevent tipping points in forest ecosystems.

Tree mortality in mature temperate forests of central Mexico: a spatial approach

Tree mortality is an important process of forest stand dynamics and knowledge of it is fundamental to implement adequate management strategies. Subject to several factors, tree mortality can induce different spatial patterns on the remaining live and dead trees. While spatially clustered tree mortality in young forests is often driven by competition, in old-growth forests, spatially clustered tree mortality is often caused by disturbance agents. This study is focused on a spatiotemporal analysis of tree mortality in a mature temperate forest located in central Mexico dominated by Pinus montezumae and Alnus firmifolia. We used tree locations from a permanent plot (300 × 300 m) measured over a 20-year period. The results, from applying point pattern analysis, showed that the spatial pattern of all dead trees was clustered at short to medium distances, but showed no clear deviation from complete spatial randomness at longer distances. Similar results were found for P. montezumae and A. firmifolia. Using the bivariate mark-connection function (alive and dead trees), no tree mortality caused by competition was discernable, only A. firmifolia showed a tendency toward competition-introduced mortality around 15 m. Regarding forest structure, alive trees retained a clustered distribution and size heterogeneity at different distances during the measurement period. Thus, there was evidence that the resulting spatial pattern of tree mortality could be explained by disturbance agents such as droughts rather than tree competition. Therefore, the results of this study can contribute to implement management strategies based on the principles of continuous cover forestry and provide novel information regarding tree mortality in Mexican montane forests.

Disturbance of Wind Damage and Insect Outbreaks in the Old-Growth Forest of Changbai Mountain, Northeast China

The changing climate is worsening the threats to forests, such as insect outbreaks, fires, and drought, especially old-growth forest, which is more susceptible to disturbance. Therefore, it is important to detect the disturbance areas, identify the disturbance agents, and evaluate the disturbance intensity in old-growth forest. We tried to derive the forest disturbance information based on multiple remote sensing datasets (Global Forest Change, MODIS, and ERA5-Land) from 2000 to 2021 in Changbai Mountain, Northeast China, and explored their relationship with climate factors. The results showed that (1) wind damage and insect outbreaks are two main forest disturbance agents, (2) the increasing temperature during overwintering periods and the decreasing precipitation during activity periods increase the risk of insect outbreaks, and (3) disturbances lead to significant changes in forest structure and functional indices, which can be well captured by the remote sensing data. In the study, we creatively combined low-frequency remote sensing images and high-frequency meteorological data to determine the specific time of wind damage. The final results suggested that the vulnerability of old-growth forest to climate change may be mainly reflected through indirect implications, such as the increased risk of strong winds and insect disturbances.

Infestation Phases and Impacts of Dryocoetes confusus in Subalpine Fir Forests of Southern British Columbia

Subalpine fir mortality and stand decline are increasingly evident in British Columbia (B.C.). This long-term study confirmed Dryocoetes confusus to be the major disturbance agent in high-elevation subalpine forests, killing over two-thirds of subalpine fir in eleven one-hectare study plots. D. confusus infestations in mature stands can be described as early-, mid-, or late-phase. The transition from the early- through late-phase is characterized by a lowered stem density as high levels of D. confusus attack and remove the largest trees, while other mortality factors kill smaller trees. Initially, live subalpine fir density and D. confusus activity varied among plots. By a final assessment, very little difference was observed in live stems per hectare. Mortality from all factors ranged from 0.5% to 5% annually, reaching as high as 80% in-stand mortality with >6 times more dead than live volume. When subalpine fir density was reduced to <400 sph, the D. confusus attack rate declined. Cumulative mortality increased the average gap size in plots from 11 m2 to 18 m2. Our study also showed that D. confusus might be able to switch to a univoltine life cycle, taking advantage of warmer and longer growing seasons that, in part, could explain the rapid increase in mortality in stands.

Drift Algal Accumulation in Ice Scour Pits Provides an Underestimated Ecological Subsidy in a Novel Antarctic Soft-Sediment Habitat.

Ice scouring is one of the strongest agents of disturbance in nearshore environments at high latitudes. In depths, less than 20 m, grounding icebergs reshape the soft-sediment seabed by gouging furrows called ice pits. Large amounts of drift algae (up to 5.6 kg/m2) that would otherwise be transported to deeper water accumulate inside these features, representing an underestimated subsidy. Our work documents the distribution and dimensions of ice pits in Fildes Bay, Antarctica, and evaluates their relationship to the biomass and species composition of algae found within them. It also assesses the rates of deposition and advective loss of algae in the pits. The 17 ice pits found in the study area covered only 4.2% of the seabed but contained 98% of drift algal biomass, i.e., 60 times the density (kg/m2) of the surrounding seabed. Larger ice pits had larger and denser algal accumulations than small pits and had different species compositions. The accumulations were stable over time: experimentally cleared pits regained initial biomass levels after one year, and advective loss was less than 15% annually. Further research is needed to understand the impacts of ice scouring and subsequent algal retention on ecosystem functioning in this rapidly changing polar environment.

Iridescent Beetle Adornments Suggest Incipient Status Competition among the Earliest Horticulturalists in Bears Ears National Monument

AbstractAnthropological research has long theorized that emergent food-producing economies catalyzed high levels of inequality in human societies, as evident in the earliest use of jewelry made from gold, copper, and other precious minerals among early agricultural populations. Although the US Southwest appears to have been an exception, we report the discovery of two Basketmaker II period necklaces constructed of green iridescent scarab beetle femora, which suggests a homologous association between emergent agriculture and inequality. Drawing insight from ethnography, archaeology, entomology, and evolutionary ecology, we hypothesize that these and other jewelry items of Basketmaker II culture were visually prominent, honest signals of socioeconomic capital that emerged during a period of surplus food production and incipient wealth accumulation. It appears that Basketmaker II societies—like other emergent food-producing economies around the world—grappled with the opportunities and challenges that arise with surplus production, albeit in a distinct way that involved visually striking insect and feather adornments as status signals. Archaeologists may have previously overlooked this behavior due to Western biases that privilege precious metals and minerals as prestige objects and archaeological biases that tend to view insects as food or agents of site disturbance.

Vegetation disturbances characterization in the Tibetan Plateau from 1986 to 2018 using Landsat time series and field observations

Disturbances in vegetated land could dramatically affect the process of vegetation growth and reshape the land cover state. The overall greenup of vegetation on the Tibetan Plateau (TP) has almost served as a consensus to date. However, we still lack consistent acquisitions on the timing, the spatial patterns, and the temporal frequency of vegetation disturbance over the TP, limiting the capacity for planning land management strategies. Therefore, we explored the spatiotemporal pattern and variation of vegetation disturbances across the TP during the past decades and analyzed the disturbance agents. We utilized 37-year Landsat time series images and field observations coupled with a temporal segmentation approach to characterize the spatiotemporal pattern of vegetation disturbances across the TP for the period 1986–2018. The results from this study revealed that 75.71 M ha (accounting for 29.34% of TP’s area) vegetation area underwent at least one disturbance, of which 8.44 M ha area ever experienced large-scale disturbances (disturbance area greater than 0.9 ha and disturbance magnitude (the difference between the spectral value of pre-disturbance and that of post-disturbance) over 0.2). Further, the spatial distributions of these large-scale disturbances varied over time: before 2002, the disturbed sites were evenly distributed over the southeast part of the TP probably induced by overgrazing and unscientific livestock management, while after 2002, most disturbances were concentrated in the south of the Yarlung Tsangpo, mainly caused by anthropogenic activities, such as urban area, roadways, railway, and water control projects. This study presents an effort to characterize vegetation disturbances and their variations over the past decades on the TP, which provides crucial insights toward a complete understanding of vegetation dynamics and its causal relationship with human activities.

Modeling the susceptibility of an uneven-aged broad-leaved forest to snowstorm damage using spatially explicit machine learning.

Snowstorms are disturbance agents that have received relatively little research attention rather than significant disturbances that they pose to forest ecosystems. In this study, we modeled the interactions between snowstorms and different characteristics of a forest stand in northern Iran and spatially visualized the susceptibility of the stand to damage caused by snowstorms using the random forest (RF) and logistic regression (LR) methods. After a severe snowstorm in November 2021 that caused stem breakage and uprooting of individual trees, the location of 185 damaged trees was identified via field surveys and used for generating an inventory map of snowstorm damage. The thematic maps of fourteen explanatory variables representing the characteristics of damaged trees and the study forest were produced. The models were trained with 70% of the damaged trees and validated with the remaining 30% based on the area under the receiver operating characteristic curve (AUC). The results indicated the better performance of RF compared to LR in both training (0.934 vs. 0.896) and validation (0.925 vs. 0.894) phases. The RF model identified slope, aspect, and wind effect as the variables with the greatest impacts on the forest stand sustainability to snowstorm damage. Approximately 30% of the study area was categorized as high and very high susceptible to snowstorms. Our results can enable forest managers to tailor more informed adaptive forest management plans in readiness for snowstorm seasons and recovery from their damage.

Significant increase in natural disturbance impacts on European forests since 1950.

Over the last decades, the natural disturbance is increasingly putting pressure on European forests. Shifts in disturbance regimes may compromise forest functioning and the continuous provisioning of ecosystem services to society, including their climate change mitigation potential. Although forests are central to many European policies, we lack the long-term empirical data needed for thoroughly understanding disturbance dynamics, modeling them, and developing adaptive management strategies. Here, we present a unique database of >170,000 records of ground-based natural disturbance observations in European forests from 1950 to 2019. Reported data confirm a significant increase in forest disturbance in 34 European countries, causing on an average of 43.8 million m3 of disturbed timber volume per year over the 70-year study period. This value is likely a conservative estimate due to under-reporting, especially of small-scale disturbances. We used machine learning techniques for assessing the magnitude of unreported disturbances, which are estimated to be between 8.6 and 18.3 million m3 /year. In the last 20 years, disturbances on average accounted for 16% of the mean annual harvest in Europe. Wind was the most important disturbance agent over the study period (46% of total damage), followed by fire (24%) and bark beetles (17%). Bark beetle disturbance doubled its share of the total damage in the last 20 years. Forest disturbances can profoundly impact ecosystem services (e.g., climate change mitigation), affect regional forest resource provisioning and consequently disrupt long-term management planning objectives and timber markets. We conclude that adaptation to changing disturbance regimes must be placed at the core of the European forest management and policy debate. Furthermore, a coherent and homogeneous monitoring system of natural disturbances is urgently needed in Europe, to better observe and respond to the ongoing changes in forest disturbance regimes.

Development and implementation of a spruce bark beetle susceptibility index: A framework to compare bark beetle susceptibility on stand level

The spruce bark beetle (spruce bark beetle) (Ips typographus) is one of the major disturbance agents in European forests. Damage by spruce bark beetle is expected to increase in the future, as a result of e.g. increased temperatures. However, not all forest stands are equally vulnerable. Therefore, describing the relative difference in susceptibility of different forest stands to spruce bark beetle infestation and to try to estimate changes in susceptibility under different management or climate scenarios is necessary to support decision making on forest management. We present a spruce bark beetle susceptibility index, which describes the relative susceptibility of forest stands to spruce bark beetle infestation. The index is based on empirical findings and expert opinion, and takes both climatic and stand variables into account. The index can be implemented in forest simulation programs. The susceptibility index was implemented in Heureka, a forest decision support system. To demonstrate the use of the index, simulations were run for three management scenarios: baseline; even-aged management focused on conifers, longer rotation: same as baseline but with longer rotation periods and mixed forest: same as baseline but retaining a higher share of broadleaves. For this purpose, an area of 2451 ha consisting of 751 stands was used. The index value per stand per five-year time period was obtained from the simulations. The index was calculated individually, per management strategy, for all 751 stands and thereafter mean index and harvest volume was obtained for the whole area. Mean susceptibility was higher, and harvest slightly lower, in the longer rotation scenario, compared with the baseline, while there were no differences between baseline and mixed. At individual stand level, the differences are more nuanced and, for example, certain stands have lower susceptibility in the mixed compared with the baseline scenario. The ability to simulate forest development and simultaneously get a measure of spruce bark beetle susceptibility will enable forest owners to identify vulnerable stands and evaluate effects of different management decisions to reduce the risk for future economic losses.

Drivers of invasion by laurel wilt of redbay and sassafras in the southeastern US.

Timely responses to mitigate economic and environmental impacts from invading species are facilitated by knowledge of the speed and drivers of invasions. Quantify changes in invasion patterns through time and factors that governed time-to-invasion by laurel wilt, one of the most damaging, non-native disturbance agents invading forests of the United States. We analyzed county-level occurrence data (2004-2021) for laurel wilt across the southeastern United States. A Cox proportional hazards modeling framework was used to elucidate drivers of invasion. As of 2021, laurel wilt had been detected in 275 counties and made 72 discrete jumps (averaging 164km ± 16SE) into counties that did not share a border with a previously invaded county. Spread decelerated from 40km/yr to 24km/yr after 5years, with a marked decline in the number of counties invaded in 2021 (16) compared with 2020 (33). The Cox proportional hazards model indicated that proxies for anthropogenic movement and habitat invasibility increased invasion risk. The recent decline in number of counties invaded could be due to disruptions to travel and/or surveys from the coronavirus pandemic, but exhaustion of the most suitable habitat, such as counties in the southeastern US with warm annual temperatures and high densities of host trees, could have also contributed to this trend. This work suggests that without a shift in spread driven by additional insect vectors, that rates of range expansion by laurel wilt might have peaked in 2020 and could continue decelerating. The online version contains supplementary material available at 10.1007/s10980-022-01560-3.

Where forest may not return in the western United States

Droughts that are hotter, more frequent, and last longer; pest outbreaks that are more extensive and more common; and fires that are more frequent, more extensive, and perhaps more severe have raised concern that forests in the western United States may not return once disturbed by one or more of these agents. Numerous field-based studies have been undertaken to better understand forest response to these changing disturbance regimes. Meta-analyses of these studies provide broad guidelines on the biotic and abiotic factors that hinder forest recovery, but study-to-study differences in methods and objectives do not support estimation of the total extent of potentially impaired forest succession. In this research, we provide an estimate of the area of potentially impaired forest succession. The estimate was derived from modeling of an 18-year land cover and Normalized Difference Vegetation Index (NDVI) time series supported by an extensive ancillary dataset. We estimate an upper bound of approximately 3470 km2 of disturbed forest that may not return or reattain prior composition and structure. Based on the data used, fire appears to be the main disturbance agent of impaired forest succession, although climatic factors cannot be discounted. The numerous field studies routinely cite distal seed sources as a factor that hinders forest recovery, and we estimate that 20 % of the upper bound estimate has no forest cover within a 4.4-ha neighborhood. Our upper bound estimate is about 0.5 % of the 2001 mapped extent of western United States forests. The estimate is cognizant of measurement and modeling uncertainties (i.e., upper bound) and uncertainties related to successional rates and trajectories (i.e., potential).