Xylogenesis, the process through which wood cells are formed, results in the long-term storage of carbon in woody biomass, making it a key component of the global carbon cycle. Understanding how environmental drivers influence xylogenesis during the growing season is therefore of great interest. However, studying short-term drivers of wood production using xylogenetic data is complicated by the usual sampling scheme and the influence of eccentric growth, i.e., heterogeneous growth around the stem. In this study, we improve xylogenesis research by introducing a statistical approach that explicitly considers seasonal phenology, short-term growth rates, and growth eccentricity. To this end, we developed Bayesian models of xylogenesis and compared them with a conventional method based on the use of Gompertz functions. Our results show that eccentricity generated high temporal autocorrelation between successive samples, and that explicitly taking it into account improved both the representativeness of phenology and intra-ring variability. We observed consistent short-term patterns in the model residuals, suggesting the influence of an unaccounted-for environmental variable on cell production. The proposed models offer several advantages over traditional methods, including robust confidence intervals around predictions, consistency with phenology, and reduced sensitivity to extreme observations at the end of the growing season, often linked to eccentric growth. These models also provide a benchmark for mechanistic testing of short-term drivers of wood formation.
{"title":"Modeling eccentric growth explicitly to investigate intra-annual drivers of xylem cell production using xylogenetic data","authors":"Lucie Nina Barbier , Marc-André Lemay , Étienne Boucher , Sergio Rossi , Fabio Gennaretti","doi":"10.1016/j.fecs.2025.100413","DOIUrl":"10.1016/j.fecs.2025.100413","url":null,"abstract":"<div><div>Xylogenesis, the process through which wood cells are formed, results in the long-term storage of carbon in woody biomass, making it a key component of the global carbon cycle. Understanding how environmental drivers influence xylogenesis during the growing season is therefore of great interest. However, studying short-term drivers of wood production using xylogenetic data is complicated by the usual sampling scheme and the influence of eccentric growth, i.e., heterogeneous growth around the stem. In this study, we improve xylogenesis research by introducing a statistical approach that explicitly considers seasonal phenology, short-term growth rates, and growth eccentricity. To this end, we developed Bayesian models of xylogenesis and compared them with a conventional method based on the use of Gompertz functions. Our results show that eccentricity generated high temporal autocorrelation between successive samples, and that explicitly taking it into account improved both the representativeness of phenology and intra-ring variability. We observed consistent short-term patterns in the model residuals, suggesting the influence of an unaccounted-for environmental variable on cell production. The proposed models offer several advantages over traditional methods, including robust confidence intervals around predictions, consistency with phenology, and reduced sensitivity to extreme observations at the end of the growing season, often linked to eccentric growth. These models also provide a benchmark for mechanistic testing of short-term drivers of wood formation.</div></div>","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"15 ","pages":"Article 100413"},"PeriodicalIF":4.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145747358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2026-01-07DOI: 10.1016/j.fecs.2026.100425
Rudong Zhao , Yu Wu , Chang Liao , Yi li , Qiuxiang Tian , Qinghu Jiang , Xiaoxiang Zhao , Jing Fang , Canlan Jiang , Feng Liu
Nitrogen (N) deposition profoundly influences carbon (C) cycling in terrestrial ecosystems. However, integrated studies on dynamics of net ecosystem C stock (NEC) under N deposition in subtropical forests remain limited, creating uncertainty in assessing their C sequestration potential. We conducted a 6-year field experiment using a randomized block design to investigate the effects of N addition at three levels (0, 30, and 60 kg N·ha−1·year−1) on NEC and its components—aboveground C stock (AGC), belowground C stock (BGC), forest litter C stock (FLC), fine root C stock (FRC), and heterotrophic respiration C efflux (RhC). N addition significantly reduced AGC, BGC, FRC, and RhC, but increased FLC. As a result, NEC declined with N addition, with AGC contributing most to this reduction and FLC the least. The N-addition-induced reduction in soil water content appeared to be the primary driver of decreases in AGC and BGC and indirectly reduced FRC via suppressed fine root biomass. RhC dynamics were more strongly governed by fine root biomass than by microbial traits, thereby partially mitigating the NEC loss. While N addition rates had limited effects on NEC and most C stock components, RhC was significantly affected. These findings suggest that medium- to long-term N deposition may reduce the C sequestration capacity of subtropical forests. This study provides new insights for accurately assessing C sequestration potential under increasing N deposition.
氮沉降对陆地生态系统碳(C)循环有着深远的影响。然而，对亚热带森林净生态系统碳储量（NEC）在N沉降下动态的综合研究仍然有限，这给评估其碳固存潜力带来了不确定性。采用随机区组设计进行了为期6年的田间试验，研究了3个水平（0、30和60 kg N·ha−1·年−1）施氮对NEC及其组分（地上C库（AGC）、地下C库（BGC）、森林凋落物C库（FLC）、细根C库（FRC）和异养呼吸C外排（RhC））的影响。N的添加显著降低了AGC、BGC、FRC和RhC，但增加了FLC。结果表明，随着N的增加，NEC呈下降趋势，其中AGC对NEC的降低贡献最大，FLC的降低作用最小。n添加导致的土壤含水量降低是AGC和BGC降低的主要驱动因素，并通过抑制细根生物量间接降低FRC。与微生物性状相比，细根生物量对RhC动态的影响更大，从而在一定程度上减轻了NEC的损失。施氮量对NEC和大部分碳源组分的影响有限，但对RhC的影响显著。这些结果表明，中长期氮沉降可能会降低亚热带森林的碳固存能力。该研究为准确评估氮沉降增加下碳固存潜力提供了新的思路。
{"title":"Six years of nitrogen addition reduced ecosystem carbon sequestration capacity in a subtropical forest","authors":"Rudong Zhao , Yu Wu , Chang Liao , Yi li , Qiuxiang Tian , Qinghu Jiang , Xiaoxiang Zhao , Jing Fang , Canlan Jiang , Feng Liu","doi":"10.1016/j.fecs.2026.100425","DOIUrl":"10.1016/j.fecs.2026.100425","url":null,"abstract":"<div><div>Nitrogen (N) deposition profoundly influences carbon (C) cycling in terrestrial ecosystems. However, integrated studies on dynamics of net ecosystem C stock (NEC) under N deposition in subtropical forests remain limited, creating uncertainty in assessing their C sequestration potential. We conducted a 6-year field experiment using a randomized block design to investigate the effects of N addition at three levels (0, 30, and 60 kg N·ha<sup>−1</sup>·year<sup>−1</sup>) on NEC and its components—aboveground C stock (AGC), belowground C stock (BGC), forest litter C stock (FLC), fine root C stock (FRC), and heterotrophic respiration C efflux (RhC). N addition significantly reduced AGC, BGC, FRC, and RhC, but increased FLC. As a result, NEC declined with N addition, with AGC contributing most to this reduction and FLC the least. The N-addition-induced reduction in soil water content appeared to be the primary driver of decreases in AGC and BGC and indirectly reduced FRC via suppressed fine root biomass. RhC dynamics were more strongly governed by fine root biomass than by microbial traits, thereby partially mitigating the NEC loss. While N addition rates had limited effects on NEC and most C stock components, RhC was significantly affected. These findings suggest that medium- to long-term N deposition may reduce the C sequestration capacity of subtropical forests. This study provides new insights for accurately assessing C sequestration potential under increasing N deposition.</div></div>","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"15 ","pages":"Article 100425"},"PeriodicalIF":4.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-04-01Epub Date: 2025-10-26DOI: 10.1016/j.fecs.2025.100398
Yiping Hou , Xiaohua Wei , Zhipeng Xu , Sheena A. Spencer , Ming Qiu , Shixuan Lyu , Wenfei Liu
Extreme climate events (e.g., heatwaves and droughts) are becoming increasingly frequent due to global climate change, which inevitably affects tree growth and various other ecological processes. While the impacts of droughts on these processes have been widely evaluated, the effects of heatwaves on tree growth and soil water content (SWC) remain poorly understood, particularly those related to thinning treatment. In this study, we evaluated the impacts of the 2021 Pacific Northwest Heatwave and thinning on forest growth and SWC, as well as assessed how thinning might mitigate the heatwave's impacts in lodgepole pine forests in British Columbia, Canada. We measured meteorological data (air temperature, rainfall, solar radiation (SR), relative humidity (RH), and wind speed (Ws)), sap flow, SWC, soil temperature (Ts), and tree diameters at the breast height (DBH) during the growing season (June–September) in the control (27,000 stems·ha−1), lightly thinned (4,500 stems·ha−1), and heavily thinned (1,100 stems·ha−1) experimental plots from 2018 to 2024. We found that thinning persistently and significantly (p < 0.05) increased individual tree growth, with the most pronounced effects in the heavily thinned stands. The 2021 Pacific Northwest Heatwave led to an exceptionally hot growing season, significantly (p < 0.05) reducing forest growth and SWC across all plots. Forest growth recovered in 2022 in the thinned plots but remained suppressed in the unthinned plots, suggesting that thinning effectively mitigated the impact of the heatwave on forest growth, while the heatwave's impacts were persistent in the unthinned plots. Our study highlights that thinning is a practical management strategy for improving tree growth and supporting climate change adaptation to extreme climate events.
{"title":"Impact of heatwave and thinning on tree growth and soil water content in young lodgepole pine forests","authors":"Yiping Hou , Xiaohua Wei , Zhipeng Xu , Sheena A. Spencer , Ming Qiu , Shixuan Lyu , Wenfei Liu","doi":"10.1016/j.fecs.2025.100398","DOIUrl":"10.1016/j.fecs.2025.100398","url":null,"abstract":"<div><div>Extreme climate events (e.g., heatwaves and droughts) are becoming increasingly frequent due to global climate change, which inevitably affects tree growth and various other ecological processes. While the impacts of droughts on these processes have been widely evaluated, the effects of heatwaves on tree growth and soil water content (SWC) remain poorly understood, particularly those related to thinning treatment. In this study, we evaluated the impacts of the 2021 Pacific Northwest Heatwave and thinning on forest growth and SWC, as well as assessed how thinning might mitigate the heatwave's impacts in lodgepole pine forests in British Columbia, Canada. We measured meteorological data (air temperature, rainfall, solar radiation (SR), relative humidity (RH), and wind speed (<em>W</em><sub>s</sub>)), sap flow, SWC, soil temperature (<em>T</em><sub>s</sub>), and tree diameters at the breast height (DBH) during the growing season (June–September) in the control (27,000 stems·ha<sup>−1</sup>), lightly thinned (4,500 stems·ha<sup>−1</sup>), and heavily thinned (1,100 stems·ha<sup>−1</sup>) experimental plots from 2018 to 2024. We found that thinning persistently and significantly (<em>p</em> < 0.05) increased individual tree growth, with the most pronounced effects in the heavily thinned stands. The 2021 Pacific Northwest Heatwave led to an exceptionally hot growing season, significantly (<em>p</em> < 0.05) reducing forest growth and SWC across all plots. Forest growth recovered in 2022 in the thinned plots but remained suppressed in the unthinned plots, suggesting that thinning effectively mitigated the impact of the heatwave on forest growth, while the heatwave's impacts were persistent in the unthinned plots. Our study highlights that thinning is a practical management strategy for improving tree growth and supporting climate change adaptation to extreme climate events.</div></div>","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"15 ","pages":"Article 100398"},"PeriodicalIF":4.4,"publicationDate":"2026-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145467424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-17DOI: 10.1016/j.fecs.2026.100459
Eneli Põldveer, Paavo Kaimre, Diana Laarmann, Andres Kiviste, Annika Tuum, Henn Korjus
Continuous cover forestry (CCF) is gaining increasing attention in Estonia, but its implementation is constrained by limited experience, insufficiently detailed forest inventory data, and regulatory frameworks developed primarily for even-aged forest management. In this study, we established a CCF experimental site on private forest land by setting up permanent sample plots following the design of the Estonian Network of Forest Research Plots. We also developed an algorithm-based approach for automatic tree selection in the selection cutting area using detailed tree-level data collected from the sample plots. The experimental site provides a potentially long-term empirical basis for testing selection cutting decisions, identifying the level of forest inventory detail required for CCF, and evaluating the applicability of current management rules to continuous cover forestry and their scope for development under Estonian conditions.
{"title":"An algorithm-based approach for tree selection in continuous cover forestry","authors":"Eneli Põldveer, Paavo Kaimre, Diana Laarmann, Andres Kiviste, Annika Tuum, Henn Korjus","doi":"10.1016/j.fecs.2026.100459","DOIUrl":"https://doi.org/10.1016/j.fecs.2026.100459","url":null,"abstract":"Continuous cover forestry (CCF) is gaining increasing attention in Estonia, but its implementation is constrained by limited experience, insufficiently detailed forest inventory data, and regulatory frameworks developed primarily for even-aged forest management. In this study, we established a CCF experimental site on private forest land by setting up permanent sample plots following the design of the Estonian Network of Forest Research Plots. We also developed an algorithm-based approach for automatic tree selection in the selection cutting area using detailed tree-level data collected from the sample plots. The experimental site provides a potentially long-term empirical basis for testing selection cutting decisions, identifying the level of forest inventory detail required for CCF, and evaluating the applicability of current management rules to continuous cover forestry and their scope for development under Estonian conditions.","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"94 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-17DOI: 10.1016/j.fecs.2026.100458
Sheng-I Yang, Thomas J. Brandeis, Humfredo Marcano-Vega, Tamara Heartsill-Scalley
Mixed-effects models with species as a random effect have provided a practical solution to produce reliable predictions of tree growth. Applying them to new datasets can be challenging because species-specific adjustments are not automatically available for “new” species (i.e., species that are not “observed” in model training). In general, there are four strategies used for unobserved species when applying mixed models: (1) generating predictions using only the fixed-effects portion of the model, (2) computing species-specific adjustments post hoc when limited observations for the new species are available, (3) building two separate models with and without species as a random effect, and (4) combining data grouping with mixed modeling. To our knowledge, the relative efficacy of these strategies has not been explicitly examined for diverse species-rich forests in the Caribbean. Long-term data collected by the US Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program in Puerto Rico and the U.S. Virgin Islands over the past 20 years were used in this study.
{"title":"Examining strategies to project tree diameter for unobserved species in diverse tropical forests using mixed-effects models","authors":"Sheng-I Yang, Thomas J. Brandeis, Humfredo Marcano-Vega, Tamara Heartsill-Scalley","doi":"10.1016/j.fecs.2026.100458","DOIUrl":"https://doi.org/10.1016/j.fecs.2026.100458","url":null,"abstract":"Mixed-effects models with species as a random effect have provided a practical solution to produce reliable predictions of tree growth. Applying them to new datasets can be challenging because species-specific adjustments are not automatically available for “new” species (i.e., species that are not “observed” in model training). In general, there are four strategies used for unobserved species when applying mixed models: (1) generating predictions using only the fixed-effects portion of the model, (2) computing species-specific adjustments post hoc when limited observations for the new species are available, (3) building two separate models with and without species as a random effect, and (4) combining data grouping with mixed modeling. To our knowledge, the relative efficacy of these strategies has not been explicitly examined for diverse species-rich forests in the Caribbean. Long-term data collected by the US Department of Agriculture (USDA), Forest Service, Forest Inventory and Analysis (FIA) program in Puerto Rico and the U.S. Virgin Islands over the past 20 years were used in this study.","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"40 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-16DOI: 10.1016/j.fecs.2026.100455
Matthew B. Russell, Aaron R. Weiskittel
The peer review process in forestry journals has remained largely unchanged despite significant shifts in the academic publishing landscape over the past decade. Using data from 156 forestry journals and detailed metrics from 10 selected journals, we examine trends in peer-review capacity, associate editor roles, and publishing volume from 2000 through 2024. Over this period, the number of forestry articles published annually has increased more than fourfold, while the pool of available reviewers has contracted, creating unsustainable pressure on the review system. Open-access publishing now accounts for 45% of forestry articles, up from 20% in 2000, with implications for review timelines and quality assurance. We evaluate the potential of artificial intelligence tools to assist with peer review, while acknowledging associated risks to scientific integrity. Drawing on a comparison of reviews from human experts and large language models, we propose recommendations for experimenting with alternative review models, implementing version control, and integrating artificial intelligence (AI) responsibly into the peer review process.
{"title":"Improving peer review capacity and integrity in forestry journals","authors":"Matthew B. Russell, Aaron R. Weiskittel","doi":"10.1016/j.fecs.2026.100455","DOIUrl":"https://doi.org/10.1016/j.fecs.2026.100455","url":null,"abstract":"The peer review process in forestry journals has remained largely unchanged despite significant shifts in the academic publishing landscape over the past decade. Using data from 156 forestry journals and detailed metrics from 10 selected journals, we examine trends in peer-review capacity, associate editor roles, and publishing volume from 2000 through 2024. Over this period, the number of forestry articles published annually has increased more than fourfold, while the pool of available reviewers has contracted, creating unsustainable pressure on the review system. Open-access publishing now accounts for 45% of forestry articles, up from 20% in 2000, with implications for review timelines and quality assurance. We evaluate the potential of artificial intelligence tools to assist with peer review, while acknowledging associated risks to scientific integrity. Drawing on a comparison of reviews from human experts and large language models, we propose recommendations for experimenting with alternative review models, implementing version control, and integrating artificial intelligence (AI) responsibly into the peer review process.","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"54 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The long-term carbon (C) sequestration potential of plantations hinges on the dynamics and persistence of mature forest C sinks, yet how C storage and stability evolve with increasing forest age remains unclear. Here, we examined a chronosequence of mature Pinus massoniana reforestations (32-, 45-, and 60-year-old) to quantify ecosystem C storage across plant (tree, shrub, and herb), litter, and soil (0–100 cm) pools, and to assess soil organic carbon (SOC) stability via the ratio of mineral-associated organic carbon (MAOC) vs. particulate organic carbon (POC). Results showed that the total ecosystem C storage remained relatively constant across stand developmental stages, reflecting that plant C storage increased 53.4% from 32 to 45 years, then declined, while SOC storage decreased 53.9% from 32 to 45 years, then increased. In contrast, the 64.0% rise in the MAOC/POC ratio from 32 to 60 years may reflect a trend of enhanced SOC stability. Microbial necromass constituted 45.9%–64.8% of SOC, with fungal necromass dominating bacterial necromass, especially in the subsoils (20–100 cm). Additionally, SOC, POC, and MAOC showed strong positive correlations with microbial necromass but exhibited weak associations with plant and litter C pools. The MAOC/POC ratio correlated strongly with the ratio of fungal necromass carbon (FNC) vs. bacterial necromass carbon (BNC). These results reveal that microbial—especially fungal—necromass may underpin the soil C stability and ecosystem C persistence of mature pine reforestations. Therefore, accurately predicting the long-term C sequestration of mature reforestation requires a mechanistic understanding that integrates both SOC stability and microbial necromass dynamics.
{"title":"Microbial necromass underpins long-term soil carbon stability and ecosystem carbon persistence in pine reforestations","authors":"Shiyang Wu, Liehua Tie, Jordi Sardans, Xingliang Xu, Ji Chen, Peilei Hu, Lei Deng, Yixian Kong, Shengnan Ouyang, Congde Huang, Josep Peñuelas, Guijie Ding","doi":"10.1016/j.fecs.2026.100457","DOIUrl":"https://doi.org/10.1016/j.fecs.2026.100457","url":null,"abstract":"The long-term carbon (C) sequestration potential of plantations hinges on the dynamics and persistence of mature forest C sinks, yet how C storage and stability evolve with increasing forest age remains unclear. Here, we examined a chronosequence of mature <ce:italic>Pinus massoniana</ce:italic> reforestations (32-, 45-, and 60-year-old) to quantify ecosystem C storage across plant (tree, shrub, and herb), litter, and soil (0–100 cm) pools, and to assess soil organic carbon (SOC) stability via the ratio of mineral-associated organic carbon (MAOC) vs. particulate organic carbon (POC). Results showed that the total ecosystem C storage remained relatively constant across stand developmental stages, reflecting that plant C storage increased 53.4% from 32 to 45 years, then declined, while SOC storage decreased 53.9% from 32 to 45 years, then increased. In contrast, the 64.0% rise in the MAOC/POC ratio from 32 to 60 years may reflect a trend of enhanced SOC stability. Microbial necromass constituted 45.9%–64.8% of SOC, with fungal necromass dominating bacterial necromass, especially in the subsoils (20–100 cm). Additionally, SOC, POC, and MAOC showed strong positive correlations with microbial necromass but exhibited weak associations with plant and litter C pools. The MAOC/POC ratio correlated strongly with the ratio of fungal necromass carbon (FNC) vs. bacterial necromass carbon (BNC). These results reveal that microbial—especially fungal—necromass may underpin the soil C stability and ecosystem C persistence of mature pine reforestations. Therefore, accurately predicting the long-term C sequestration of mature reforestation requires a mechanistic understanding that integrates both SOC stability and microbial necromass dynamics.","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"189 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-03-12DOI: 10.1016/j.fecs.2026.100454
Tzeng Yih Lam
Modeling height–diameter (H–D) relationships is fundamental to forest management. Copula could be used to simulate H–D distributions that mirror the underlying dependence structures of an observed relationship. Tail dependence measures the co-movements of extreme events. It is an intrinsic property of a copula, but it has rarely been examined in forestry studies that applied a copula. The overall goal of this paper was to introduce tail dependence in H–D modeling using a small dataset of two species groups and the elliptical copulas (Normal and t copula). The H–D observations were first transformed into pseudo-observations by ranking, which were used to compute tail dependence. Elliptical copulas were fitted and used to simulate distributions of pseudo-observations. The simulated pseudo-observations were transformed into simulated H–D distributions by the fitted marginals. Results showed that the empirical tail dependence of the two species groups was asymmetrical, more variable in the lower tail, but more similar in the upper tail. The elliptical copulas failed to capture the asymmetric empirical tail dependence because of the symmetry imposed by the copulas. This led to inadequate representation of the simulated H–D distributions to the observed ones by producing extreme outliers that were not biologically meaningful. For example, the Normal copula simulated H–D pairs with D ≤ 2 cm but H up to 18 m for one species group. Our assessments of the lack of fit of the elliptical copulas are made possible by studying the distributions of pseudo-observations and computing tail dependence. They unravel dependence structures that are not immediately apparent in the corresponding H–D relationships. Lastly, we recommend future studies to consider reporting pseudo-observations and tail dependence and to explore alternative copulas that accommodate asymmetric tail dependence.
{"title":"The tale of tail dependence: Modeling height–diameter relationships with elliptical copulas","authors":"Tzeng Yih Lam","doi":"10.1016/j.fecs.2026.100454","DOIUrl":"https://doi.org/10.1016/j.fecs.2026.100454","url":null,"abstract":"Modeling height–diameter (<ce:italic>H</ce:italic>–<ce:italic>D</ce:italic>) relationships is fundamental to forest management. Copula could be used to simulate <ce:italic>H</ce:italic>–<ce:italic>D</ce:italic> distributions that mirror the underlying dependence structures of an observed relationship. Tail dependence measures the co-movements of extreme events. It is an intrinsic property of a copula, but it has rarely been examined in forestry studies that applied a copula. The overall goal of this paper was to introduce tail dependence in <ce:italic>H</ce:italic>–<ce:italic>D</ce:italic> modeling using a small dataset of two species groups and the elliptical copulas (Normal and <ce:italic>t</ce:italic> copula). The <ce:italic>H</ce:italic>–<ce:italic>D</ce:italic> observations were first transformed into pseudo-observations by ranking, which were used to compute tail dependence. Elliptical copulas were fitted and used to simulate distributions of pseudo-observations. The simulated pseudo-observations were transformed into simulated <ce:italic>H</ce:italic>–<ce:italic>D</ce:italic> distributions by the fitted marginals. Results showed that the empirical tail dependence of the two species groups was asymmetrical, more variable in the lower tail, but more similar in the upper tail. The elliptical copulas failed to capture the asymmetric empirical tail dependence because of the symmetry imposed by the copulas. This led to inadequate representation of the simulated <ce:italic>H</ce:italic>–<ce:italic>D</ce:italic> distributions to the observed ones by producing extreme outliers that were not biologically meaningful. For example, the Normal copula simulated <ce:italic>H</ce:italic>–<ce:italic>D</ce:italic> pairs with <ce:italic>D</ce:italic> ≤ 2 cm but <ce:italic>H</ce:italic> up to 18 m for one species group. Our assessments of the lack of fit of the elliptical copulas are made possible by studying the distributions of pseudo-observations and computing tail dependence. They unravel dependence structures that are not immediately apparent in the corresponding <ce:italic>H</ce:italic>–<ce:italic>D</ce:italic> relationships. Lastly, we recommend future studies to consider reporting pseudo-observations and tail dependence and to explore alternative copulas that accommodate asymmetric tail dependence.","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"58 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ecological impacts of aerosols on vegetation remain highly uncertain due to their capacity for both modifying radiation and causing phytotoxic damage. China has experienced the most rapid air quality improvement globally since 2013, yet the ecosystem consequences of this governance are poorly quantified. Here, we analyzed satellite observations and reanalysis data from multiple sources covering a long period to investigate the spatiotemporal patterns of aerosols and vegetation across China. By employing generalized linear mixed models (GLMM), we isolated the independent and relative contributions of aerosol optical depth (AOD) to vegetation dynamics. Our results reveal a pronounced divergence between the north and south: AOD suppresses vegetation growth in southern China with limited radiation, while in regions limited by water availability, it likely enhances water use efficiency and productivity by reducing surface radiation and vapor pressure deficit (VPD), thereby curtailing transpiration water loss. The impacts exhibited patterns that were distinctly specific to species: needleleaf forests, meadows, wetlands, and shrublands demonstrated heightened vulnerability to aerosol suppression, whereas needleleaf and broadleaf mixed forests uniquely benefited from increased diffuse radiation. Notably, the gross primary productivity (GPP) of steppe ecosystems underwent a fundamental shift from a negative to a positive response to aerosols after 2013, highlighting the dynamic interactions between aerosols and ecosystems that were specific to the environment. Crucially, the GLMM quantified a significant weakening of the aerosol suppression effect after the implementation of clean air policies, with its standardized negative coefficient on GPP declining from −0.16 to −0.10. This study provides observational evidence on a large scale that improving air quality not only alleviates environmental stress but also directly promotes ecosystem function, offering critical insights for assessing carbon neutrality policies.
{"title":"Heterogeneous effects of aerosols on terrestrial ecosystems in China","authors":"Xiuting Lai, Hao Fan, Yanhong Jia, Shiyu Zhang, Jiayun Qi, Xu Wang","doi":"10.1016/j.fecs.2026.100452","DOIUrl":"https://doi.org/10.1016/j.fecs.2026.100452","url":null,"abstract":"Ecological impacts of aerosols on vegetation remain highly uncertain due to their capacity for both modifying radiation and causing phytotoxic damage. China has experienced the most rapid air quality improvement globally since 2013, yet the ecosystem consequences of this governance are poorly quantified. Here, we analyzed satellite observations and reanalysis data from multiple sources covering a long period to investigate the spatiotemporal patterns of aerosols and vegetation across China. By employing generalized linear mixed models (GLMM), we isolated the independent and relative contributions of aerosol optical depth (AOD) to vegetation dynamics. Our results reveal a pronounced divergence between the north and south: AOD suppresses vegetation growth in southern China with limited radiation, while in regions limited by water availability, it likely enhances water use efficiency and productivity by reducing surface radiation and vapor pressure deficit (VPD), thereby curtailing transpiration water loss. The impacts exhibited patterns that were distinctly specific to species: needleleaf forests, meadows, wetlands, and shrublands demonstrated heightened vulnerability to aerosol suppression, whereas needleleaf and broadleaf mixed forests uniquely benefited from increased diffuse radiation. Notably, the gross primary productivity (GPP) of steppe ecosystems underwent a fundamental shift from a negative to a positive response to aerosols after 2013, highlighting the dynamic interactions between aerosols and ecosystems that were specific to the environment. Crucially, the GLMM quantified a significant weakening of the aerosol suppression effect after the implementation of clean air policies, with its standardized negative coefficient on GPP declining from −0.16 to −0.10. This study provides observational evidence on a large scale that improving air quality not only alleviates environmental stress but also directly promotes ecosystem function, offering critical insights for assessing carbon neutrality policies.","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"10 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nutrient resorption is a key process through which plants optimize resource use in nutrient-limited environments. Global nutrient addition experiments and meta-analyses have revealed high variability in nutrient resorption efficiency (NuRE) and its influencing factors. However, most existing ecosystem models utilize static constants for NuRE, which fail to capture this variability and limit the model’s ability to accurately describe nutrient cycling. Here, we introduce two innovations: (i) a multifactor allometric model that extends conventional single-factor formulations alongside a hybrid framework that couples the allometric core with random forest (RF) residual correction to capture nonlinearities and interactions; and (ii) utilization of the resorbed nutrient amount (ReNu), rather than the ratio-based NuRE, as a more robust modeling target to reduce uncertainty and improve predictability. Using independent datasets from China and a global meta-analysis, nutrient resorption exhibited substantial variability. Allometric modeling predicted ReNu with R2 > 0.7, outperforming NuRE (R2 < 0.3), and hybrid modeling further reduced prediction error. NuRE is less robust and relies more on RF residual correction. By combining the interpretability of parametric allometry with the flexibility of data-driven learning, our framework provides a more accurate and dynamic representation of nutrient resorption for modeling forest nutrient cycling under global environmental change.
{"title":"Dynamic parameterization of the nutrient resorption process in forest ecosystems with a hybrid model","authors":"Langqin Hua, Josep Peñuelas, Guoyi Zhou, Lei Liu, Zhen Yu, Wenjing Chen, Xuemeng Wang, Xianzheng Zeng","doi":"10.1016/j.fecs.2026.100453","DOIUrl":"https://doi.org/10.1016/j.fecs.2026.100453","url":null,"abstract":"Nutrient resorption is a key process through which plants optimize resource use in nutrient-limited environments. Global nutrient addition experiments and meta-analyses have revealed high variability in nutrient resorption efficiency (NuRE) and its influencing factors. However, most existing ecosystem models utilize static constants for NuRE, which fail to capture this variability and limit the model’s ability to accurately describe nutrient cycling. Here, we introduce two innovations: (i) a multifactor allometric model that extends conventional single-factor formulations alongside a hybrid framework that couples the allometric core with random forest (RF) residual correction to capture nonlinearities and interactions; and (ii) utilization of the resorbed nutrient amount (ReNu), rather than the ratio-based NuRE, as a more robust modeling target to reduce uncertainty and improve predictability. Using independent datasets from China and a global meta-analysis, nutrient resorption exhibited substantial variability. Allometric modeling predicted ReNu with <ce:italic>R</ce:italic><ce:sup loc=\"post\">2</ce:sup> > 0.7, outperforming NuRE (<ce:italic>R</ce:italic><ce:sup loc=\"post\">2</ce:sup> < 0.3), and hybrid modeling further reduced prediction error. NuRE is less robust and relies more on RF residual correction. By combining the interpretability of parametric allometry with the flexibility of data-driven learning, our framework provides a more accurate and dynamic representation of nutrient resorption for modeling forest nutrient cycling under global environmental change.","PeriodicalId":54270,"journal":{"name":"Forest Ecosystems","volume":"62 1","pages":""},"PeriodicalIF":4.1,"publicationDate":"2026-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464859","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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