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The rapid and accurate detection of forest disturbances in temperate forests has become increasingly crucial as policy demands and climate pressure on these forests rise. The cloud-penetrating Sentinel-1 radar constellation provides frequent and high-resolution observations with global coverage, but few studies have assessed its potential for mapping disturbances in temperate forests. This study investigated the sensitivity of temporally dense C-band backscatter data from Sentinel-1 to varying management-related disturbance intensities in temperate forests, and the influence of confounding factors such as radar backscatter signal seasonality, shadow, and layover on the radar backscatter signal at a pixel level. A unique network of 14 experimental sites in the Netherlands was used in which trees were removed to simulate different levels of management-related forest disturbances across a range of representative temperate forest species. Results from six years (2016–2022) of Sentinel-1 observations indicated that backscatter seasonality is dependent on species phenology and degree of canopy cover. The backscatter change magnitude was sensitive to medium- and high-severity disturbances, with radar layover having a stronger impact on the backscatter disturbance signal than radar shadow. Combining ascending and descending orbits and complementing polarizations compared to a single orbit or polarization was found to result in a 34% mean increase in disturbance detection sensitivity across all disturbance severities. This study underlines the importance of linking high-quality experimental ground-based data to dense satellite time series to improve future forest disturbance mapping. It suggests a key role for C-band backscatter time series in the rapid and accurate large-area monitoring of temperate forests and, in particular, the disturbances imposed by logging practices or tree mortality driven by climate change factors. [ABSTRACT FROM AUTHOR]

Natural disturbances (wildfires, droughts, beetle outbreaks) shaped temperate forests for millennia, including dry forests of the western USA. Could they now best restore and adapt dry forests to climate change while protecting nearby communities? Mechanical fuel-reduction treatments (e.g., thinning) reduce landscape heterogeneity and appear ineffective since <1% of the treated area encounters fire each year and fires are still increasing. We propose and analyze a nature-based solution (NbS), using natural disturbances, to see whether it is feasible, how long it might take, and whether it could more effectively restore and adapt dry forests to climate change. We compared 2010–2019 disturbance rates on ~16 million ha of federal dry forests with historical data. We evaluated how much adaptation is achieved by comparing how trees are selected by treatments and disturbances. We found an NbS, which works with natural disturbances and prioritizes community protection, is feasible in western USA dry forests since disturbances are occurring mostly within historical rates. Natural disturbances, unlike mechanical treatments, select survivors that are more likely to be genetically adapted to survive future disturbances and climate change, while perpetuating ecosystem services. Natural disturbances also could ecologically restore forest heterogeneity, better maintain carbon storage, and reduce management needs. A fully developed disturbance-based NbS could more effectively adapt dry forests to climate change within ~30–40 years if active management is reprioritized to protect the built environment and communities near public forests. [ABSTRACT FROM AUTHOR]

Temperate conifer forests stressed by climate change could be lost through tree regeneration decline in the interior of high-severity fires, resulting in type conversion to non-forest vegetation from seed-dispersal limitation, competition, drought stress, and reburns. However, is fire triggering this global change syndrome at a high rate? To find out, I analyzed a worst-case scenario. I calculated fire rotations (FRs, expected period to burn once across an area) across ~56 million ha of forests (~80% of total forest area) in 11 western USA states from 2000 to 2020 for total high-severity fire area, interior area (>90 m inward), and reburned area. Unexpectedly, there was no trend in area burned at high severity from 2000 to 2020 across the four forest types studied. The vulnerable interior area averaged only 21.9% of total high-severity fire area, as 78.1% of burned area was within 90 m of live seed sources where successful tree regeneration is likely. FRs averaged 453 years overall, 2089 years in interiors, and 19,514 years in reburns. Creation of vulnerable interior area in a particular location is thus, on average, a 2000+ year event, like a very rare natural disaster, and reburns that may favor type conversion to non-forest have almost no effect. This means that, from 2021 to 2050 at most, only 3.0–4.2% of total forest area may become a vulnerable interior area, based on a likely high aridity-based climate projection of future fire and a higher scenario, where rates in the exceptional 2020 fire year have become the norm. These findings show that increased management to reduce high-severity fires is not currently needed, as the risk to forests from this global change syndrome is likely quite low up to 2050. Faster and larger disturbances (e.g., severe droughts) are more likely to cause most tree mortality or forest loss that occurs by 2050. [ABSTRACT FROM AUTHOR]

This review summarizes the intricate relationship between climate change and forest ecosystems in the Northwest Iberian Peninsula, outlining both their resilience and vulnerabilities. The study asserts the significant impact of climate change on these ecosystems, reinforcing earlier theories about their responsive behavior to global climatic alterations. However, the impacts are highly localized, contingent upon specific forest compositions, topography, and interaction with other environmental stressors. The temperate forests of the Northwest Iberian Peninsula manifest a delicate balance of resilience and vulnerability in the face of these phenomena. Notably, the study underscores that this region's forest ecosystems remain a relatively uncharted research territory, promising fruitful prospects for future exploration. Although existing studies offer vital insights into the climate change impacts, there is a stark need for further research to gain a deeper understanding of, and formulate appropriate responses to, the challenges that these specific ecosystems confront in the wake of climate change. [ABSTRACT FROM AUTHOR]

Understanding the ecological role of fire in forests is essential for proper management and conservation programs. The objectives of this study were: (1) to reconstruct the history of fires in a temperate forest in Sierra Madre Occidental; and (2) to interpret the impacts of fire and climate on forest structure. Sixty tree cross-sections with fire scars were analyzed, and descriptive statistics of fire history were generated. Additionally, growth cores were analyzed, and the ages of trees of different diameter categories were calculated. The synchrony between fire history and tree establishment was determined, and precipitation and Palmer Drought Severity Index (PDSI) values were correlated with the number of trees established per year. The presence of 137 fire scars was determined, which allowed the reconstruction of 41 fire events over the period 1855–2019; however, only the period 1940–2015 was used to compare tree recruitment, as tree establishment was detected in this period. The mean fire interval (MFI) was 2.28 years in general, and 12.17 years for extensive fires. As regards vegetation, a continuous recruitment pattern was observed, typical of a frequent low-intensity fire regime, although peak regeneration occurred after extensive fires. The correlation analysis showed that the number of trees established per year was influenced by the wet conditions that occurred in December of the previous year and the dry conditions in September and October of the previous year. This finding demonstrates the historical influence of fire and climate on the structure of the current stand in the study area. Therefore, the present study highlights the importance of including fire in forest management programs, considering the natural fire regime to which the species in this ecosystem are already adapted. [ABSTRACT FROM AUTHOR]

Frequent forest fires cause air pollution, threaten biodiversity and spoil forest ecosystems. Forest fire vulnerability assessment is a potential way to improve the ability of forests to resist climate disasters and help formulate appropriate forest management countermeasures. Here, we developed an automated hybrid machine learning algorithm by selecting the optimal model from 24 models to map potential forest fire vulnerability over China during the period 2001–2020. The results showed forest aboveground biomass (AGB) had a vulnerability of 26%, indicating that approximately 2.32 Gt C/year of forest AGB could be affected by fire disturbances. The spatiotemporal patterns of forest fire vulnerability were dominated by both forest characteristics and climate conditions. Hotspot regions for vulnerability were mainly located in arid areas in western China, mountainous areas in southwestern China, and edges of vegetation zones. The overall forest fire vulnerability across China was insignificant. The forest fire vulnerability of boreal and temperate coniferous forests and mixed forests showed obviously decreasing trends, and cultivated forests showed an increasing trend. The results of this study are expected to provide important support for the forest ecosystem management in China. [ABSTRACT FROM AUTHOR]

Forests are under stress due to variety of climatic and non-climatic factors. Therefore for suitably managing the forests, vulnerability of the forests needs to be understood. The present paper attempts to estimate the vulnerability of various temperate forests of Western Himalaya due to climate change by analyzing the patterns of different taxonomical indices, based on primary data i.e., vegetation data. The paper presents a novel approach for climate change vulnerability assessment based on field data through a bottom-up approach. The vulnerability of the forests was assessed through the IPCC framework by suitably selecting indicators (taxonomy indices and climatic parameters) for the three dimensions of vulnerability i.e., exposure, sensitivity and adaptive capacity. The field data were collected from 17 different temperate forests distributed at the elevation "1600 to 3500 m" in Uttarakhand and Himachal Pradesh, India. Abundance and richness for each forest were collected by randomly laying ten quadrats of size 0.1 ha each. The analysis resulted into identifying the most and the least vulnerable temperate forests of the western Himalaya to climate change. The analysis showed that the Neoza Pine; Moist Deodar; Ban Oak and Dry Broadleaved and Coniferous forest were the most vulnerable forests in the Himalayan temperate forests due to climate change. Moreover, the variation in the levels of the vulnerability status of the selected forests was insignificant with elevational range as well as exposure to climate. The proposed method will serve for vulnerability estimation of forests due to climate change based on the actual realization of the species in the field. [ABSTRACT FROM AUTHOR]

Forest loss and degradation are central problems in the context of climate change and biodiversity conservation. The identification of areas of loss relies on accurate base maps. Central datasets in this context are the products of the Global Land Analysis & Discovery (GLAD) project. Although the GLAD forest cover products are primarily intended to serve as a near real-time flag for areas of forest loss, its historic datasets are increasingly also being used in ways that go beyond this initial focus. To date, very little information is available on the performance of GLAD data in temperate regions. This study aims to address this research gap by comparing the GLAD baseline forest cover maps for the years 2000 and 2010 with UK national forest datasets. The results showed substantial commission errors, which highlight potential problems when deviating from the GLAD datasets' intended use. GLAD data appear to be less useful in regions with a high proportion of medium to low-density canopy cover. In such cases, its application in forest models should only be used in conjunction and cross-calibration with good quality reference data. [ABSTRACT FROM AUTHOR]

Today, climate change is assumed by many researchers and scholars as a certainty and is presented as the biggest challenge humanity has ever faced. It is commonly accepted that anthropogenic greenhouse gas emissions are the main cause that is accelerating the process. Therefore, it is urgent to find solutions to mitigate climate change, mainly because the intense effects have already been felt, in many cases in the form of the occurrence of extremely violent weather events. Forests are undoubtedly one of the most effective and easiest ways to provide the function of carbon sinks. However, it is essential and convenient to analyze the permanence time of this carbon in forests, because this permanence time depends directly on the forest management model used. This article aims to analyze forest management models from the perspective of carbon residence time in temperate forests, dividing the models into three types, namely carbon conservation models, carbon storage models, and carbon substitution models, according to their ability to contribute to functioning as carbon sinks, thereby contributing to the mitigation of climate change. [ABSTRACT FROM AUTHOR]

Research Highlights: This research highlights the importance of environmental gradients in shaping tree growth responses to global change drivers and the difficulty of attributing impacts to a single directional driver. Background and Objectives: Temperature increases associated with climate change might strongly influence tree growth and forest productivity in temperate forest species. However, the direction and intensity of these effects at the dry edge of species range are still unclear, particularly given the interaction between local factors and other global change drivers such as land use change, atmospheric CO2 increase and nitrogen deposition. While recent studies suggest that tree growth in cool temperate forests has accelerated during the last decades of the 20th century, other studies suggest a prevalence of declining growth, especially in dry-edge populations. Materials and Methods: Using historical forest inventories, we analyzed last century tree growth trends (1930–2010) along an elevation gradient (1350–1900 meters above sea level (m a.s.l.)) in a dry edge scots pine (Pinus sylvestris L.) forest in Central Iberian Peninsula. Growth was estimated as decadal volume increments in harvested trees of different size classes from 1930 to 2010 (1930–1940, 1939–1949, 1949–1959, 1959–1968, 1989–1999, 2000–2010). Results: Our results showed opposite growth trends over time depending on elevation. While tree growth has accelerated in the low end of the altitudinal gradient, tree growth slowed down at higher elevations (1624–1895 m a.s.l.). Moreover, the magnitude of growth reduction along the altitudinal gradient increased with tree age. Conclusions: Throughout the last 80 years, growth trends in a rear-edge Pinus. sylvestris forest has shown divergent patterns along an altitudinal gradient. Specifically, environmental conditions or other factors, may have become more adverse for growth at high altitudes and have improved at low altitudes. This suggests that local factors such as topography can modulate the impact of climate change on forest ecosystems. [ABSTRACT FROM AUTHOR]