Forest Dynamics Research Articles

One century of carbon dynamics in the eastern Canadian boreal forest under various management strategies and climate change projections

Partial cutting has lower canopy removal intensities than clearcutting and has been proposed as an alternative harvesting approach to enhance ecosystem services, including carbon sequestration and storage. However, the ideal partial cutting/clearcutting proportion that should be applied to managed areas of the eastern Canadian boreal forest to enhance long-term carbon sequestration and storage at the landscape scale remains uncertain. Our study projected carbon dynamics over 100 years (2010–2110) under a portfolio of management strategies and future climate scenarios within three boreal forest management units in Quebec, Canada, distributed along an east–west gradient. To model future carbon dynamics, we used LANDIS-II, its Forest Carbon Succession extension, and several extensions that account for natural disturbances in the boreal forest (wind, fire, spruce budworm). We simulated the effects of several management strategies on carbon dynamics, including a business-as-usual strategy (clearcutting applied to more than 95 % of the annually managed area), and compared these projections against a no-harvest natural dynamics scenario. We projected an overall increase in total ecosystem carbon storage, mostly because of increased productivity and broadleaf presence under limited climate change. The drier Western region under climate scenario RCP8.5 was an exception, as stocks decreased after 2090 because of the direct negative effects of extreme climate change on coniferous species’ productivity. Under the natural dynamic scenario, our simulations suggest that the Quebec Forest in the Central and Western regions may act as a carbon sink, despite high fire-related carbon emissions, particularly under RCP4.5 and RCP8.5 Conversely, the eastern region periodically switched from carbon sink to source following SBW outbreaks, thus being a weak sink over the simulation period. Applying partial cutting to over 50 % of the managed forest area effectively mitigated the negative impacts of climate change on carbon balance, reducing differences in stand composition and carbon storage between naturally dynamic forests and those managed for timber. In contrast, clearcutting-based scenarios, including the business-as-usual approach, substantially reduced total ecosystem carbon storage— by approximately double (10 tC ha−1 yr−1) compared to partial cutting scenarios (<5 tC ha−1 yr−1). Clearcutting led to higher heterotrophic respiration due to the proliferation of fast-decomposing broadleaves, resulting in lower carbon accumulation compared to partial cuts. Our findings underscore the importance of balancing canopy removal intensities to increase carbon sequestration and storage while preserving other ecosystem qualities under climate change.

Estimation of within-gap regeneration height growth in managed temperate deciduous forests using bi-temporal airborne laser scanning data

Key messageMulti-temporal airborne laser scanning (ALS) data were used to estimate regeneration stem height growth within gaps in uneven-aged deciduous forests. The height and height growth measured in the field were used to calibrate and validate ALS estimates. This method provided highly precise estimates of height and unbiased height increment estimates of regeneration at stem level.ContextAssessing regeneration height growth is essential for evaluating forest dynamics and optimizing silvicultural operations. However, regeneration description at high spatiotemporal resolution has remained limited to restricted areas by the limiting cost constraints of field measurements. Highly precise airborne laser scanning (ALS) data are currently acquired over wide areas. Such datasets are promising for characterizing regeneration dynamics.AimsWe aimed to estimate height and height growth within regenerating areas at the stem level using multi-temporal ALS data.MethodsALS data were acquired from 56,150 ha of uneven-aged deciduous forest in Belgium in 2014 and 2021. Stem tops were detected using local maxima (LM) within regenerating areas in both ALS datasets and matched. Field data were collected in 2021 and used to calibrate the ALS-estimated heights using linear and non-linear models at stem level. Height growth estimation was then validated using field-measured increments.ResultsWithout height calibration, the 2021 ALS-estimated height had a − 1.06 m bias and 1.39 m root-mean-squared error (RMSE). Likewise, the 2014 ALS-estimated height had a − 0.58 m bias and 1.14 m RMSE. The non-linear calibration seemed more appropriate for small regeneration stems (height < 4 m). Using height calibration, the 2021 ALS-estimated height had a − 0.01 m bias and 0.84 m RMSE. In 2014, the bias and RMSE were 0.02 and 0.91 m, respectively. ALS-estimated height growth was unbiased and had an RMSE of 0.10 m·year−1.ConclusionsThis original method is based on the bi-temporal ALS datasets calibrated by limited field measurements. The proposed method is the first to provide unbiased regeneration height growth of regeneration stems in uneven-aged forests and new perspectives for studying and managing forest regeneration.

Endemic and elusive trophic interactions: The first comprehensive description of the diet of short-eared dogs (Atelocynus microtis) in Amazon rainforests

The short-eared dog (Atelocynus microtis) is the only endemic Amazonian canid species, which is also elusive and rarely recorded across its distribution, making it one of the least known canid species in the world. Even though it is considered to be a carnivore species, it has been reported to consume other food items, such as fruits. However, no comprehensive analysis of its diet is currently available in the literature. Here we report the first comprehensive analysis of the diet of wild and re-introduced individuals of A. microtis in the western Amazon (southeastern Peru). Its diet includes at least 34 distinct food items, including arthropods, vertebrates (fish, amphibians, reptiles, birds, and mammals), fruits, and seeds. Our study confirms the potential of A. microtis to be considered omnivorous, as well as expands the known range of food items in its diet. As a mesocarnivore with an omnivorous diet, A. microtis has important potential implications for forest dynamics, such as seed dispersal and regulating prey populations, which should be further investigated.

Temporal Shifts in Flower-Visiting Butterfly Communities and Their Floral Resources along a Vegetation Type Altered by Anthropogenic Factors

Habitat disturbance driven by human activities poses a major threat to biodiversity and can disrupt ecological interactions. Butterfly–plant mutualisms represent an ideal model system to study such anthropogenic impacts, as butterflies exhibit intimate dependencies on larval host plants and adult nectar sources, rendering them highly sensitive to habitat changes affecting the availability of these floral resources. This study examined flower-visiting butterfly communities and their associations with flowering plants in a landscape altered by anthropogenic factors in central Mexico. The study area encompassed a mosaic of vegetation types, including native juniper forests, agricultural lands, and introduced eucalyptus plantations, representing different degrees of human-induced habitat modification. Monthly surveys were conducted over a single year, covering both rainy and dry seasons, to analyze butterfly and plant diversity, community composition, and interactions. Results showed the highest diversity in juniper forests, followed by eucalyptus and agricultural sites. Seasonal turnover was the primary driver of community changes, with habitat-based segregation persisting within seasons. Butterfly diversity strongly correlated with flower abundance, while plant richness played a secondary role. SIMPER and indicator species analyses identified key taxa contributing to compositional dissimilarities among habitats and associated with specific vegetation types and seasons. Our research provides insights into temporal dynamics structuring butterfly–plant interactions across this forest disturbance spectrum, highlighting how habitat changes and seasonality shape these mutualistic communities in changing landscapes.

Changes in Spatiotemporal Pattern and Its Driving Factors of Suburban Forest Defoliating Pest Disasters

Forest defoliating pests are significant global forest disturbance agents, posing substantial threats to forest ecosystems. However, previous studies have lacked systematic analyses of the continuous spatiotemporal distribution characteristics over a complete 3–5 year disaster cycle based on remote sensing data. This study focuses on the Dendrolimus superans outbreak in the Changbai Mountain region of northeastern China. Utilizing leaf area index (LAI) data derived from Sentinel-2A satellite images, we analyze the extent and dynamic changes of forest defoliation. We comprehensively examine the spatiotemporal patterns of forest defoliating pest disasters and their development trends across different forest types. Using the geographical detector method, we quantify the main influencing factors and their interactions, revealing the differential impacts of various factors during different growth stages of the pests. The results show that in the early stage of the Dendrolimus superans outbreak, the affected area is extensive but with mild severity, with newly affected areas being 23 times larger than during non-outbreak periods. In the pre-hibernation stage, the affected areas are smaller but more severe, with a cumulative area reaching up to 8213 hectares. The spatial diffusion characteristics of the outbreak follow a sequential pattern across forest types: Larix olgensis, Pinus sylvestris var. mongolica, Picea koraiensis, and Pinus koraiensis. The most significant influencing factor during the pest development phase was the relative humidity of the year preceding the outbreak, with a q-value of 0.27. During the mitigation phase, summer precipitation was the most influential factor, with a q-value of 0.12. The combined effect of humidity and the low temperatures of 2020 had the most significant impact on both the development and mitigation stages of the outbreak. This study’s methodology achieves a high-precision quantitative inversion of long-term disaster spatial characteristics, providing new perspectives and tools for real-time monitoring and differentiated control of forest pest infestations.

Spatial patterns of damage and tree mortality in a selectively logged Atlantic Forest

Selective logging, a common disturbance in mixed-species and uneven-aged forests, can cause substantial collateral stand damage and tree mortality. Here we explore damage patterns and some mechanisms that increase post-harvest tree mortality in a selectively logged subtropical Atlantic Forest in Argentina. We investigate the spatial relations of felled and damaged trees through spatial point pattern analysis and evaluate the relationships between mortality and different endogenous (size - diameter at breast height: DBH; and wood density: WD) and exogenous (damage and neighboring basal area: NBA) factors. The permanent plots were logged in 1999, and the fates of all pre-logging live trees ≥10 cm DBH were evaluated 20 years later. Of the monitored 3973 trees, 381 with damaged concentrated within 10.5 m of felled tree stumps. Over the next twenty years mean mortality was higher and more variable for damaged than undamaged trees (47 % ± 10 % SE and 39 % ± 2 % SE, respectively), and the presence of damage interacted with the other analyzed factors. For undamaged trees, the probability of mortality declined with DBH and NBA but not with WD. For damaged trees, instead, the probability of mortality was related to an interaction between DBH, WD, and NBA. For damaged trees <30 cm DBH, mortality increased with WD and NBA, whereas for damaged trees ≥30 cm DBH, mortality peaked at both extremes of the WD range. For these large trees with low WD, the probability of mortality decreased with NBA, whereas for trees with high WD, the opposite was observed. Our findings suggest that selective logging affects the dynamics of forests by spatially concentrating damage and may alter subsequent tree deaths. This could have, long-term effects on forest structure. Increases in logging intensity would increase overall damage and spatially isolate trees (i.e., lower NBA), rendering them more vulnerable to wind damage and other external factors. Increased tree mortality will reduce forest carbon stocks and thereby jeopardize global efforts to mitigate climate change.

Climatic and disturbances influence on tree-rings of Larix gmelinii in the southeast coastal area

The vast region of North East Asia is covered by primary mixed conifer-broadleaved forests which include a range of different tree species. A key factor in the dynamics of these ecosystems is wind disturbance. According to reports, this factor will be increasingly important as a result of the poleward migration of tropical cyclones, a characteristic of which is strong wind. At the same time, global climate change may reduce the recovery potency of some species and lead to new combinations of species. Gmelin Larch is one of the key early succession species in the north of the region. In the southeastern part of its range (Russian Far East), this species has not been widely studied by dendroclimatologists and there are no dendroecological studies available. This study shows how the seasonal growth of Larix gmelinii responds to changes in climate, specifically to variations in precipitation and temperature. The study has established that these trees are more affected by rising temperatures than by consistent precipitation levels, provided there is no shortage of water. Interestingly, after the 1970s there was a change in the climate sensitivity of Larix gmelinii in June (the month with the strongest correlation). It went from a negative correlation with temperature to a positive correlation with precipitation. By using tree ring data, we were able to reconstruct the past history of forest disturbance. The peaks in this chronology coincide with those in earlier published dendroecological reconstructions for other species. They indicate that the radial growth of larch is sensitive to canopy changes. We recorded two release peaks in the 1960s and 2000s, during the period of meteorological observations. We attributed the first peak to the most powerful tropical cyclone Emma (1956). We assume also that the second peak reflects the recent intensification of tropical cyclones in the region. In our opinion, the change in microclimate as a result of disturbance has altered the relationship to climate in such a way that disturbance may cause tree growth to be dependent on precipitation. At the same time, such low correlations do not support a conclusion about the strong negative influence of the current climate on the trees.

The impacts of ecological disturbances on the diversity of biosynthetic gene clusters in kauri (Agathis australis) soil

BackgroundThe ancient kauri (Agathis australis) dominated forests of Aotearoa New Zealand are under threat from a multitude of ecological disturbances such as forest fragmentation, biodiversity loss, climate change, and the spread of the virulent soil pathogen Phytophthora agathidicida. Taking a wider ecosystem-level approach, our research aimed to explore the impacts of forest disturbance and disease outbreaks on the biosynthetic potential and taxonomic diversity of the kauri soil microbiome. We explored the diversity of secondary metabolite biosynthetic gene clusters (BGCs) in soils from a range of kauri forests that varied according to historical disturbance and dieback expression. To characterise the diversity of microbial BGCs, we targeted the non-ribosomal peptide synthetase (NRPS) and polyketide synthetase (PKS) gene regions for sequencing using long-read PacBio® HiFi sequencing. Furthermore, the soil bacterial and fungal communities of each forest were characterized using 16 S rRNA and ITS gene region sequencing.ResultsWe identified a diverse array of naturally occurring microbial BGCs in the kauri forest soils, which may offer promising targets for the exploration of secondary metabolites with anti-microbial activity against P. agathidicida. We detected differences in the number and diversity of microbial BGCs according to forest disturbance history. Notably, soils associated with the most undisturbed kauri forest had a higher number and diversity of microbial NRPS-type BGCs, which may serve as a potential indicator of natural levels of microbiome resistance to pathogen invasion.ConclusionsBy linking patterns in microbial biosynthetic diversity to forest disturbance history, this research highlights the need for us to consider the influence of ecological disturbances in potentially predisposing forests to disease by impacting the wider health of forest soil ecosystems. Furthermore, by identifying the range of microbial BGCs present at a naturally high abundance in kauri soils, this research contributes to the future discovery of natural microbial compounds that may potentially enhance the disease resilience of kauri forests. The methodological approaches used in this study highlight the value of moving beyond a taxonomic lens when examining the response of microbial communities to ecosystem disturbance and the need to develop more functional measures of microbial community resilience to invasive plant pathogens.

Extreme precipitation reduces the recent photosynthetic carbon isotope signal detected in ecosystem respiration in an old-growth temperate forest.

The successful utilization of stable carbon isotope approaches in investigating forest carbon dynamics has relied on the assumption that the carbon isotope compositions (δ13C) therein have detectable temporal variations. However, interpreting the δ13C signal transfer can be challenging, given the complexities involved in disentangling the effect of a single environmental factor, the isotopic dilution effect from background CO2 and the lack of high-resolution δ13C measurements. In this study, we conducted continuous in situ monitoring of atmospheric CO2 (δ13Ca) across a canopy profile in an old-growth temperate forest in northeast China during the normal year 2020 and the wet year 2021. Both years exhibited similar temperature conditions in terms of both seasonal variations and annual averages. We tracked the natural carbon isotope composition from δ13Ca to photosynthate (δ13Cp) and to ecosystem respiration (δ13CReco). We observed significant differences in δ13Ca between the two years. Contrary to in 2020, in 2021 there was a δ13Ca valley in the middle of the growing season, attributed to surges in soil CO2 efflux induced by precipitation, while in 2020 values peaked during that period. Despite substantial and similar seasonal variations in canopy photosynthetic discrimination (Δ13Ccanopy) in the two years, the variability of δ13Cp in 2021 was significantly lower than in 2020, due to corresponding differences in δ13Ca. Furthermore, unlike in 2020, we found almost no changes in δ13CReco in 2021, which we ascribed to the imprint of the δ13Cp signal on above-ground respiration and, more importantly, to the contribution of stable δ13C signals from soil heterotrophic respired CO2. Our findings suggest that extreme precipitation can impede the detectability of recent photosynthetic δ13C signals in ecosystem respiration in forests, thus complicating the interpretation of above- and below-ground carbon linkage using δ13CReco. This study provides new insights for unravelling precipitation-related variations in forest carbon dynamics using stable isotope techniques.

Phylogenetic relatedness and habitat affect seedling abundance of a mid-montane humid evergreen broad-leaved forest in the Gaoligong Mountains, Southwestern China

The neighborhood effect has become an important framework with which to study the mechanisms that maintain the coexistence of tree species. Phylogenetic relatedness among neighboring plants directly affects species coexistence and the maintenance of tree diversity. And some studies have reported that seedling performance is negatively correlated with phylogenetic relatedness, which termed phylogenetic negative density dependence. Soil-borne fungal pathogens affected seedling performance of phylogenetically related host species, i.e., phylogenetic Janzen–Connell effect. Seedlings may be particularly vulnerable to habitat and neighbor characteristics. Although previous studies have demonstrated the influence of neighborhood effects, phylogenetic relatedness, and habitat filtering on seedling survival, growth, and mortality, the effect of variation in these factors on seedling abundance remains unclear. To address this question, we used a 4-ha (200 m × 200 m) and monitored four-year (2020–2023) seedling dataset from a mid-montane humid evergreen broad-leaved subtropical forest in the Gaoligong Mountains, Yunnan, Southwestern China, and which consisted of 916 seedlings belonging to 56 species. The results of generalized linear mixed models showed no significant effect of conspecific adult neighbors on seedling abundance at any of the intervals evaluated. In contrast, we found evidence of phylogenetic distance density dependence in the forests of the Gaoligong Mountains. Specifically, there was a significant positive effect of the relative average phylogenetic distance between heterospecific adult neighbors and focal seedlings on focal seedling abundance in 2020; however, the relative average phylogenetic distance between heterospecific seedling neighbors and focal seedlings had a significant negative effect on seedling abundance over the four-year period (2020–2023). Among the habitat factors, only light (canopy opening) had a negative effect on seedling abundance in all four years. Light resources may be a limiting factor for seedlings, and determine seedling dynamics in subtropical forests. Overall, our results demonstrated that phylogenetic density dependence and habitat filtering affected subtropical seedling abundance. Our findings provide new evidence of the impact of phylogenetic density dependence on seedling abundance in a subtropical mid-montane humid evergreen broad-leaved forest and highlight the need to incorporate the neighborhood effect, phylogenetic relatedness, and habitat factors in models assessing seedling abundance.

Contribution of small nocturnal lemurs to seed dispersal in Madagascar: A review

AbstractAnimal seed dispersers are crucial in tropical forests because they provide beneficial impacts to plants, from organisms to communities. Besides frugivorous species, omnivorous, small‐bodied, and nocturnal animals might also disperse seeds in their habitats; yet we know relatively little about their role and impacts. The Cheirogaleidae (dwarf and mouse lemurs) in Madagascar are examples of such animals, whose seed dispersal role has been overlooked until recently. Here, I provide an overview of their potential contribution to seed dispersal based on their ecological traits and future directions for studying seed dispersal ecology in Madagascar's forest ecosystems. The limited literature, published between 1971 and 2022, on the feeding ecology and seed dispersal services of the Cheirogaleidae shows that they could potentially disperse small‐sized seeds (&lt;15 mm). Also, they could surprisingly take seeds relatively long distances away from the parents (up to 1 km) despite their small body mass, both in disturbed and undisturbed forest habitats. The passage of seeds through their guts could also enhance seed germination and seedling survival. Only four Cheirogaleid species out of 40 are currently demonstrated to be effective seed dispersers. Studying the seed dispersal by small‐bodied and nocturnal primates could greatly inform their long‐term conservation as it will provide information for better awareness of their ecological role and needs.Abstract in Malagasy is available with online material.

Impact of land use on shallow groundwater quality for domestic use in Mathira East Sub-County in Kenya

Shallow groundwater sources of boreholes and springs form major types of water resources used in rural areas of Kenya. Information on their status is inadequate, thus hindering their sustainable management. This study investigated the relationship between land-use types, groundwater sources and water quality. Thirty-six randomly selected groundwater sources were sampled in Mathira East Sub-County from four stratified land-use types of forest, tea, coffee, and urban, with 18 samples collected for either shallow boreholes or springs. The Principal Component Analyses (PCA) grouped groundwater resources into three groups according to groundwater sources and land-use types. Spearman rank correlation, one-way ANOVA and unpaired t-test found that land use types significantly influenced shallow groundwater quality along an increasing gradient of landscape disturbances from the less disturbed forest, then tea, coffee and lastly to the severely disturbed, the urban area. The most affected water parameters were turbidity, conductivity, NO3–N, phosphates and faecal coliforms and their variation was attributed to land-use changes, especially agricultural intensification and urbanisation. The significant variations in other water quality parameters (total hardness, total alkalinity, dissolved oxygen, pH, manganese and fluoride) were attributed to water–rock interactions, climatic factors and land use changes. Calculated Water Quality Index (WQI) with faecal coliforms parameter from groundwater sources were found unsuitable for domestic use, while the ones derived without faecal coliforms parameter were found safe for human use. Overall, shallow groundwater sources were contaminated and unsafe for human use. This study recommends regular monitoring of key water parameters affected by land use changes to support the sustainable management of shallow groundwater resources in Mathira East Sub-County and the larger region of South Sahara Africa.

The effect of mosses on the relocation of SOC and total N due to soil erosion and percolation in a disturbed temperate forest

Forests cover one-third of the global land and are important components of carbon and nitrogen cycling. Anthropogenic disturbances, such as forest road systems or skid trails for timber harvesting, can dramatically change the nutrient cycling in these ecosystems. Skid trails increase soil erosion and thus the displacement of soil organic carbon (SOC) and total nitrogen (Nt). Additionally, runoff transports high amounts of dissolved organic carbon (DOC), which can have a negative impact on aquatic ecosystems. One of the most important countermeasures against soil erosion is the quick recolonization of vegetation. To date, the extent to which natural vegetation succession influences the relocation of SOC and Nt, and in particular the role of mosses in this context, has not been well investigated. This study investigates the influence of natural vegetation succession and in particular of mosses on the displacement process of SOC and Nt as well as DOC caused by soil erosion. To this end, we combine the results of a field study using in-situ rainfall simulations with small-scale runoff plots in skid trails of the Schönbuch Nature Park in southwestern Germany with the results of ex-situ rainfall simulation experiments with infiltration boxes containing the substrate from the respective skid trails. The eroded sediments of skid trails were on average enriched in SOC by 16% and in Nt by 35% compared to the original soil, which lead to a decrease of the C/N ratio in sediments. As vegetation succession progressed, the displacement of SOC and Nt was reduced, confirmed by a negative correlation between the enrichment ratios of SOC (ERSOC), Nt and total vegetation cover. However, mosses tended to reduce ERSOC more than vascular plants. Additionally, mosses significantly decreased DOC concentration in surface runoff compared to bare soils, while no difference in DOC concentration in percolated water could be observed. Future research should explore the role of mosses in the storage of SOC and Nt in the soil and their impact on soil stability. Thus, utilizing mosses could potentially minimize environmental impacts from soil disturbances in forests.

Influence of the Periodicity of Ground Fires in Middle-Аged Pine Forests on the Combustible Materials Stocks

Significant areas of forest are annually exposed to fires in the Krasnoyarsk Territory. Fires transform forest areas and change the stocks and structure of combustible materials. Information on the dynamics of forest fuel accumulation can serve as a basis for managing the pyrogenic resistance of forest areas. The purpose of the research is to assess the impact of early spring ground fires of different frequencies on the structure and stocks of combustible materials in forests. Experimental fires were carried out in middle-aged mixed-grass-green-moss pine forests in the forest-steppe zone of the Krasnoyarsk Territory. Experimental fires were simulated with different periodicities (annual, with an interval of 2–3 years and a singular one). Regardless of periodicity, the experimental fires led to an increase of combustible materials stocks in 2–3 years after fires. Repeated burnings reduced the stocks of combustible materials close to pre-fire values. The structure of combustible materials has changed, which has led to a decrease in potential flammability of pine forests. The proportion of needles and bark in litter has decreased, and the proportion of cones has increased. Fires led to a redistribution of deadwood classes towards larger diameters. During the research period (2014–2018), the largest reserve of forest fuel loads was noted on the plot with triennial fires (68.2 t ha–1).

Long‐term assessment of macro‐ and micronutrients in foliage of European beech (Fagus sylvatica L.) in thinned versus unmanaged old‐growth stands

AbstractBackgroundScience‐based decisions regarding forest management require the knowledge of the impact of thinning regimens on the forests’ vitality and resilience. There is no systematic study analysing the role of forest management approaches on the nutritional status of forests, serving as a surrogate for their health and growth.AimsWe assessed the impact of ‘heavy thinning from above’ versus ‘no management’ on the foliar chemistry of old‐growth European beech stands on a calcareous site with cambisol/chromic luvisol soil in Thuringia, Germany.MethodsMacro‐ and micronutrients were analysed by serial foliar analysis of six trees per experimental plot over 13 years (2009–2021). To assess potential differences of foliar chemistry between the two plots and over time, a linear mixed‐effects model was applied.ResultsFoliar concentrations of all macro‐ and micronutrients were not significantly different between the two plots (p &gt; 0.05), demonstrating that the management approach had no relevant impact on the nutritional status of beech trees growing at the calcareous site. Furthermore, all foliar concentrations were dynamic over the 13‐year evaluation period. Hence, long‐term forest monitoring is crucial to capture the complex interplay between the trees and environmental conditions.ConclusionsSerial foliar analysis allows for a reliable evaluation of a forest's nutritional status. The results indicate that either regimen, that is, ‘heavy thinning from above’ or ‘no management’, shall not pose any risk in terms of growth and stability. Our results add to the understanding of beech forest dynamics and may provide a further piece for science‐based strategies of sustainable forest management.

An Improved LandTrendr Algorithm for Forest Disturbance Detection Using Optimized Temporal Trajectories of the Spectrum: A Case Study in Yunnan Province, China

Forest disturbance mapping plays an important role in furthering our understanding of forest dynamics. The Landsat-based detection of Trends in Disturbance and Recovery (LandTrendr) algorithm is widely used in forest disturbance mapping. However, it neglects the quality of the temporal trajectory and its change trends for forest disturbance mapping. Therefore, the aim of this paper is to improve LandTrendr (iLandTrendr) for forest disturbance mapping by optimizing its temporal trajectories and the post-processing of detection results. Specifically, the temporal trajectory of complex forest disturbance types was optimized using the Savitzky–Golay (SG) filter with constraints. That is, the smooth value generated from the SG filter for the disturbance year was replaced by the satellite observations when the nonlinear abrupt signals were included in the multi-temporal data. The forest disturbance detected by LandTrendr was further modified using the consistency of spectral variation trends. A case study using iLandTrendr to detect forest disturbance in Yunnan Province was conducted. Compared to the LandTrendr method, which has an overall accuracy (OA) of 35.88%, iLandTrendr generated forest disturbance mapping with an OA of 89.32%, which was significantly higher. The total mapped area of disturbance was 1,985,820.9 km2, accounting for 49.69% of the total area. The disturbances were predominately caused by natural factors, such as wildfires, pests and diseases, and forest degradation, accounting for 85.31% of the total disturbed area. iLandTrendr can quickly and accurately detect the occurrence year of complex forest disturbance types and can be extended for the forest disturbance mapping of a large area.

An improved assessment of forest disturbance using a novel approach of combining a Gaussian mixture model with an EM algorithm

Forests have experienced unprecedented decline and mortality beyond their historical range in past decades, which is attributed to disturbances like drought, fire, insects and disease. Traditional disturbance detection methods that typically employ a time series perspective to identify discrete disturbance events within continuous tree growth signals and were mainly designed for gap-scale often fail to identify disturbances across populations. To more accurately identify growth suppression and release clusters based on the perspective of forest population dynamics, here we applied a novel method of detecting forest disturbances using a Gaussian mixture model with an expectation maximisation algorithm (DGE), to fit annual distributions of growth indicators, i.e., tree-ring index. We further compared our novel approach of DGE with five traditional methods based on two sets of real tree-ring data and simulated tree-ring data. The results show an improvement of accuracy (35.5 %–48.1 %), sensitivity (36.6 %–58.1 %), precision (21.2 %–51.5 %) and specificity (11.1 %–20.6 %) for the average of two real radial growth datasets and an improvement of accuracy (7.6 %–13.9 %), sensitivity (70 %), precision (100 %) and specificity (9.1 %–9.7 %) for the simulation radial growth dataset, indicating that our DGE approach performs much better than the traditional methods. This study contributes to an improved strategy and understanding for sustainable forest management in the context of climate warming, demonstrating that our DGE approach can be better applied to global forest disturbance detection under global change.

Tracking Forest Disturbance in Northeast China’s Cold-Temperate Forests Using a Temporal Sequence of Landsat Data

Cold-temperate forests (CTFs) are not only an important source of wood but also provide significant carbon storage in China. However, under the increasing pressure of human activities and climate change, CTFs are experiencing severe disturbances, such as logging, fires, and pest infestations, leading to evident degradation trends. Though these disturbances impact both regional and global carbon budgets and their assessments, the disturbance patterns in CTFs in northern China remain poorly understood. In this paper, the Genhe forest area, which is a typical CTF region located in the Inner Mongolia Autonomous Region, Northeast China (with an area of about 2.001 × 104 km2), was selected as the study area. Based on Landsat historical archived data on the Google Earth Engine (GEE) platform, we used the continuous change detection and classification (CCDC) algorithm and considered seasonal features to detect forest disturbances over nearly 30 years. First, we created six inter-annual time series seasonal vegetation index datasets to map forest coverage using the maximum between-class variance algorithm (OTSU). Second, we used the CCDC algorithm to extract disturbance information. Finally, by using the ECMWF climate reanalysis dataset, MODIS C6, the snow phenology dataset, and forestry department records, we evaluated how disturbances relate to climate and human activities. The results showed that the disturbance map generated using summer (June–August) imagery and the enhanced vegetation index (EVI) had the highest overall accuracy (88%). Forests have been disturbed to the extent of 12.65% (2137.31 km2) over the last 30 years, and the disturbed area generally showed a trend toward reduction, especially after commercial logging activities were banned in 2015. However, there was an unusual increase in the number of disturbed areas in 2002 and 2003 due to large fires. The monitoring of potential widespread forest disturbance due to extreme drought and fire events in the context of climate change should be strengthened in the future, and preventive and salvage measures should be taken in a timely manner. Our results demonstrate that CTF disturbance can be robustly mapped by using the CCDC algorithm based on Landsat time series seasonal imagery in areas with complex meteorological conditions and spatial heterogeneity, which is essential for understanding forest change processes.

Behavioral and economic traits reflect distinct resource acquisition strategies in tendril vines and stem twining vines.

Climbing plants are important components of tropical and many temperate forest ecosystems. Current studies regard climbing plants as a single ecological plant type and ignore the ecological differences resulting from their climbing mechanisms, which may lead to a misrepresentation of the role of climbing plants in forest dynamics. Based on behavioral traits and economic traits of climbing plants, we test the hypothesis that tendril climbers and stem twiners are characterized by different resource acquisition strategies. We quantified and compared 4 behavioral traits and 7 economic traits of four stem twining vines and four tendril vines in a temperate oak forest and further tested their differences in resource acquisition strategy. Our study found that tendril vines were scattered in a group distinct from stem twining vines along the first axes of the principal component analysis using four behavioral traits and seven economic traits, being located at the more acquisitive end with more hosts, a larger distance to length ratio of stem, higher leaf and root nitrogen concentrations, and lower leaf carbon content, while stem twining vines showed the opposite trends. These results indicate that tendril vines have a more acquisitive strategy than stem twining vines. The findings suggest a functional variability among the different climbing mechanisms, and which should be accounted for in future studies.

Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.