Forest Dynamics Research Articles

Beyond resilience: Responses to changing climate and disturbance regimes in temperate forest landscapes across the Northern Hemisphere.

Climate change has profound impacts on forest ecosystem dynamics and could lead to the emergence of novel ecosystems via changes in species composition, forest structure, and potentially a complete loss of tree cover. Disturbances fundamentally shape those dynamics: the prevailing disturbance regime of a region determines the inherent variability of a system, and its climate-mediated change could accelerate forest transformation. We used the individual-based forest landscape and disturbance model iLand to investigate the resilience of three protected temperate forest landscapes on three continents-selected to represent a gradient from low to high disturbance activity-to changing climate and disturbance regimes. In scenarios of sustained strong global warming, natural disturbances increased across all landscapes regardless of projected changes in precipitation (up to a sevenfold increase in disturbance rate over the 180-year simulation period). Forests in landscapes with historically high disturbance activity had a higher chance of remaining resilient in the future, retaining their structure and composition within the range of variability inherent to the system. However, the risk of regime shift and forest loss was also highest in these systems, suggesting forests may be vulnerable to abrupt change beyond a threshold of increasing disturbance activity. Resilience generally decreased with increasing severity of climate change. Novelty in tree species composition was more common than novelty in forest structure, especially under dry climate scenarios. Forests close to the upper tree line experienced high novelty in structure across all three study systems. Our results highlight common patterns and processes of forest change, while also underlining the diverse and context-specific responses of temperate forest landscapes to climate change. Understanding past and future disturbance regimes can anticipate the magnitude and direction of forest change. Yet, even across a broad gradient of disturbance activity, we conclude that climate change mitigation is the most effective means of maintaining forest resilience.

Trading off nature for nature‐based solutions: The bioeconomics of forest management for wildlife, timber, and carbon

AbstractNature‐based solutions are attracting interest for their potential to enlist ecological processes as cost‐effective and safe ways to capture and store carbon in forest ecosystems. Such solutions often need to be implemented in landscapes in which there are longer established values for other ecosystem services including wildlife and timber production. Here we develop an integrative model that illustrates the inherent trade‐offs that will arise among the competing values for landscape space and how to resolve them. The analysis characterizes boreal forest ecosystem dynamics involving interactions among the main trophic compartments of an intact boreal ecosystem, aka “nature.” The model accounts for carbon accumulation via biomass growth of forest trees (timber), carbon loss due to controls from moose herbivory that varies with moose population density (hunting), and soil carbon inputs and release, which together determine the carbon sink strength of the ecosystem. We link the ecological dynamics with an economic analysis by assigning a price to carbon stored within the intact boreal forest ecosystem. We then weigh these carbon impacts against the economic benefits of timber production and hunting across a range of moose population densities. Combined, this carbon‐bioeconomic program calculates the total ecosystem benefit of a modeled boreal forest system, providing a framework for examining how different forest harvest and moose densities influence the achievement of carbon storage targets, under different levels of carbon pricing. The analysis shows that promoting nature‐based solutions merely for carbon storage may result in loss of a key part of “nature” via loss of the trophic structure and key functional controls in the ecosystem.

Diversity-biomass relationships are shaped by tree mycorrhizal associations and stand structural diversity at different spatial scales

Diversity-biomass relationships (DBRs) in terrestrial ecosystems tend to vary across spatial scales, but, particularly in hyperdiverse forests, the mechanisms driving these trends remain uncertain. Until now, few have simultaneously investigated the connections between tree species diversity, stand structural diversity, mycorrhizal associations, and ecosystem functioning. In addition, DBRs have only been studied at limited spatial scales, with limited focus on the direct and indirect effects of environmental factors. We addressed these research gaps using a 30-ha forest dynamics plot located in Pu'er City, Southwest China. Through piecewise structural equation models, we quantified the direct effects of tree species diversity (α, β, γ), stand structural diversity, mycorrhizal associations (AM, EcM), and the environmental factors (soil fertility and topography), as well as the indirect effects of the environmental factors on aboveground tree biomass across spatial scales ranging from 400 to 230,400 ​m2. We hypothesized that complex interactions among these factors underpin the variation in DBRs in natural ecosystems across spatial scales. Our results showed that environmental conditions indirectly affected the tree biomass via changes in tree species diversity, and these effects became stronger as the spatial scale increased. At small to moderate spatial scales, environmental factors were more predictive of tree biomass than tree species diversity (or its components); the effects of stand structural diversity on biomass also gradually increased with spatial scale. Conversely, from the intermediate to the largest spatial scales, mycorrhizal associations gradually became the best predictors of DBR dynamics. Our research offers novel empirical evidence demonstrating the importance of environmental conditions, structural diversity, and mycorrhizal associations in shaping cross-scale DBRs. Future comprehensive studies should consider these factors to assess the mechanisms shaping scale-dependent DBRs in complex natural ecosystems.

Global increase of lianas in tropical forests.

Lianas profoundly affect tropical forests dynamics, reducing productivity and carbon storage, which underscores the importance of monitoring change in their abundance in projecting the future of the global terrestrial carbon store. While increasing liana populations are documented within the Neotropics, the global consistency of these patterns is questioned, and remains to be determined. To evaluate pantropical trends in liana abundance comprehensively and quantitatively, we conducted a systematic literature review and meta-analysis. This approach allowed us to synthesize data from published longitudinal studies examining liana trends across the tropics. We calculated standardized effect sizes and standard errors, and applied a Bayesian hierarchical meta-analytic model to adjust for publication bias. Our analysis reveals an overall pan-tropical increase in lianas abundance, occurring at an average rate of 1.7 ± 0.7 SE% per year (~10% to 24% per decade). This upward trend, confirmed to be robust against publication bias, extends beyond Neotropical regions, indicating a widespread phenomenon. Although a global trend of increasing liana abundance is evident, significant local variation exist, attributable to differences in life cycle stages, abundance metrics, forest successional stages, and biogeographical realms. Notably, increases in stem density of saplings and biomass of canopy lianas, especially in old-growth forests, point to global climatic drivers and heightened turnover rates in tropical forests as factors promoting sustained liana growth in the canopy and clonal colonization in the understory. These trends suggest that the rise in liana abundance may not only persist but could also intensify under climate change. Considering both previous and current research on lianas, our findings confirm growing concerns about lianas' expanding impact on pan-tropical carbon storage, highlighting their significant potential effect on global carbon dynamics.

The dynamics of deciduous dipterocarp forest in relation to climate variability in the Sakaerat Biosphere Reserve, Northeastern Thailand

Abstract. Yatar C, Thinkampheang S, Sungkaew S, Wachrinrat C, Asanok L, Kamyo T, Hermhuk S, Kachina P, Thongsawi J, Phumphuang W, Yarnvudhi A, Waengsothorn S, Cheysawat S, Marod D. 2024. The dynamics of deciduous dipterocarp forest in relation to climate variability in the Sakaerat Biosphere Reserve, Northeastern Thailand. Biodiversitas 25: 3088-3098. Climate change is a major environmental problem influencing forest dynamics. To clarify tropical seasonal forest dynamics under climate change, we conducted long-term monitoring of all trees with Diameter at Breast Height (DBH) ?4.5 cm within a 1-ha permanent plot established in 2004 in a deciduous dipterocarp forest in the Sakaerat Biosphere Reserve (SBR), Northeastern Thailand. Surveys of all trees within the plot with DBH ?2 cm were conducted in 2008, 2015, and 2019. Climate data were obtained from the SBR climate station during 2004-2019 and used to extract dates with drought and wet conditions. Forest dynamics varied among species and periods, with stem density exhibiting a decreasing trend. Despite prolonged drought conditions from 2004 to 2009, which usually leads to increased mortality rates, the recruitment rate was 7-fold higher than the mortality rate at a site protected from fire during 2004-2008, and most of the recruited species were pioneer species, shrubs, and small trees. A contrasting trend was observed during 2015-2019, with a mortality rate almost 10-fold higher than the recruitment rate, indicating a significant ecological disturbance, likely to have been driven by a severe El Niño event during 2015-2016. Thus, climate induced disturbances (i.e., drought and fire) appear to have inhibited tree regeneration in the deciduous dipterocarp forest, particularly when they occurred in combination and for specific timing and intensity levels. Addressing the challenges posed by drought and fire to tree regeneration requires holistic management approaches that consider both ecological and climatic factors. Monitoring and adaptive management are also essential to mitigate the impact of future disturbances and support the long-term viability of forest ecosystems.

Assessment of spatio-temporal dynamics of mangrove forest in Teluk Pangpang, Banyuwangi, East Java, Indonesia

Abstract. Hidayah Z, Rachman HA, Wiyanto DB. 2024. Assessment of spatio-temporal dynamics of mangrove forest in Teluk Pangpang, Banyuwangi, East Java, Indonesia. Biodiversitas 25: 3138-3150. Mangrove forest in Teluk Pangpang, Banyuwangi District, East Java, Indonesia is located in a semi-enclosed bay area on the east coast of Java Island and bordering with Bali Strait. Since 2020, this location has been designated as an Essential Ecosystem Area (EEA) by the Indonesia Ministry of Environment and Forestry. Regardless of its designation as an EEA, information on vegetation stucture and spatio-temporal changes of Teluk Pangpang’s mangrove forest is limited. The availability of multi-temporal medium to high-resolution satellite imagery data enables researchers to monitor the condition of mangrove ecosystem using long-term data and reliable spatial continuity. The objective of this study is to investigate vegetation community structure of mangrove forest in Teluk Pangpang, as well as to determine the changes in extent and condition of mangrove forest measured as Mangrove Health Index (MHI) between 2015 and 2023 using remote sensing and GIS analysis. Spatio-temporal dynamics of MHI was determined using Sentinel-2 imagery data from 2015, 2018 and 2023. Meanwhile, a series of extensive survey in 15 transects with a total of 75 plots were conducted to obtain field data. The results showed that Rhizophora apiculata Blume and R. mucronata Lam. were the most important species with Important Value Index (IVI) of 140.91 and 148.24, respectively. Meanwhile, Sentinel-2 image processing results revealed a major increase in mangrove’s area, from 643.35 ha in 2015 to 737.51 ha in 2023. Furthermore, MHI analysis indicated improving conditions of mangrove ecosystem, as evidenced by the significant increased of mangroves area at the excellent MHI category (MHI>66.8) from 11.00 ha in 2015 to 175.86 ha in 2023. Based on Principal Component Analysis (PCA) several environmental parameters were strongly correlated to MHI including salinity, DO, TSS and mangrove’s diversity index. The findings of this study, primarily the application of MHI approach, may provide an alternative strategy for monitoring the dynamics of vegetation cover of mangrove forest in Teluk Pangpang and other mangrove areas in Indonesia.

Spatial distribution of the ethnomedicinal plant Aglaonema simplex at the Sakaerat Environmental Research Station, Northeastern Thailand

Abstract. O-thong N, Tasen W, Marod D, Thinkampheang S, Phumphuang W. 2024. Spatial distribution of the ethnomedicinal plant Aglaonema simplex at the Sakaerat Environmental Research Station, Northeastern Thailand. Biodiversitas 25: 3043-3050. Aglaonema simplex Blume (Araceae) is an evergreen herbaceous plant used ornamentally and in traditional medicine. Although the usefulness of this plant has been widely studied and reported, its ecology remains poorly understood. In this study, we examined the effects of various environmental factors on the spatial distribution of A. simplex in a Dry Evergreen Forest (DEF) at the Sakaerat Environmental Research Station (SERS) in Northeastern Thailand. All individual plants were counted; their positions were recorded within a 16-ha Forest Dynamics Plot (FDP), and their distribution pattern was analyzed using Ripley's K function. The spatial distribution of A. simplex was determined using a generalized linear model that incorporated plant density and topographic and edaphic variables within the 16-ha study plot. We found a total of 11,232 A. simplex individuals with a density of 702 individuals ha-1, with a clumped distribution pattern. The modeling results showed that the spatial distribution of A. simplex was positively influenced by soil clay content, soil pH, exchangeable magnesium, and adult tree density; it was negatively influenced by sapling density and rocky outcrops. These findings contribute to the broader understanding of the ecological niche of A. simplex. They can be used to design integrated land management approaches that balance ecological conservation with economic development goals.

Computational assessment of Amazon forest plots regrowth capacity under strong spatial variability for simulating logging scenarios

In this paper, we assess the regrowth capacity of tropical forest plots by developing an original computational procedure based on statistical model checking methods. We calibrate a new mathematical model of forest dynamics with respect to post-logging data, produced in the Amazon basin. Our mathematical model is determined by a mechanistic system of ordinary differential equations and integrates a new nonlinear aging term, which is necessary to reproduce the complex post-logging dynamics of the tropical forest plots. Our method is based on an efficient algorithmic procedure that explores the parameter space of the model and computes a score for each parameter value, depending on the distance between the trajectory of the model and the data. We distinguish a group of four reference plots, for which the logging was the most intense, from another group of five non-reference plots, which are fitted a posteriori. Our results provide a set trajectories of the new model, which successfully fit the non-monotone post-logging data on each forest plot, in spite of the high level of biological variability identified in the study site. Rather than a unique set of parameters, we return a small cell of parameters, extracted from the parameter space, which contains in its close vicinity several relevant sets of parameters that are equally able to reproduce the regrowth dynamics of distinct tropical forest plots. The size of the cells that should be extracted from the parameter space increases with the level of biological variability. Finally, we show how to use the calibrated mathematical model for simulating logging scenarios, so as to better understand the temporal dynamics of forest regrowth.

Innovative educational and research center for monitoring forest resources of Siberia based on laser and microwave aerospace imaging

The possibilities of creating an innovative educational and scientific center for monitoring forest resources in Siberia on the basis of the Department of Space Facilities and Technologies of the Siberian State University of Science and Technology named after Mikhail Fedorovich Reshetnev are discussed, with the aim of training highly qualified engineering personnel and conducting promising scientific research in the field of monitoring, modeling, forecasting and management of forest resources. Methodological solutions and algorithms for three-dimensional modeling of forest structure and dynamics based on laser scanning data, digital aerial and space photography are proposed. These methods contribute to operational monitoring and can significantly reduce the cost of monitoring the condition and use of forest resources over the vast territory of Siberia. Remote sensing data is presented in the form of a geotransformed database and digital photo map, compatible in formats with computer-aided design systems and with the main geographic information systems – ArcView, ArcINFO, MapINFO. The innovative monitoring center will be used for operational state control and monitoring of forest management, the state of forest lands, forest management and forest inventory, solving problems of ecology and environmental management, geoecology, formation of a forest resource inventory, aerospace methods for studying natural resources and territories, information technology. Solving these problems will allow for the training of highly qualified specialists. The center's specialists plan to create information technologies for remote sensing of natural objects with the aim of import substitution of foreign software products. The main scientific directions of the created center: development and research of methods for system analysis of large-scale multidimensional remote sensing data based on nonparametric decision-making algorithms and parallel computing technologies; testing hypotheses about the distributions of large-volume remote sensing data based on nonparametric nuclear-type pattern recognition algorithms; detection of compact groups of large-volume remote sensing data corresponding to unimodal fragments of the joint probability density of multivariate random variables.

Frass deposition from pest outbreaks affects soil organic carbon and its relationship with environmental factors in a deciduous broad-leaved forest

Forest defoliators are one of the major biological disturbances to forest ecosystems. As one of the abnormal nutrient input paths into forest ecosystems, frass deposition from the pest outbreak plays a critical role in regulating soil organic carbon (SOC) in forest ecosystems. However, how frass deposition affects SOC and its fractions in forests remains unclear. Based on a severe outbreak of defoliator in an oak-sweetgum mixed forest in Jigong Mountain in 2014, we compared the difference in SOC between plots with and without frass deposition for 4 consecutive years. The results showed that frass deposition led to a significant increase of 25.1 % in soil microbial biomass C (MBC) and 32.0 % in dissolved organic C (DOC) in 2014, which further escalated to 50.4 % and 50.6 % in the subsequent year (2015), respectively. The response of SOC to frass deposition lagged behind MBC and DOC. Specifically, there was no change in SOC in 2014, but a significant increase (50.9 %) was observed in the subsequent 2–3 years. The positive dependences of MBC and DOC upon fine root biomass were negated under frass deposition, while the relationship between SOC and fine root biomass remained unaffected. Soil organic carbon and DOC showed non-linear responses to frass amount and the changed soil nitrogen content. Our finding that the response of SOC to frass deposition lagged behind soil labile C indicates that SOC exhibits a certain resilience towards forest disturbance. The findings also imply that investigating the long-term impacts of frass deposition on SOC in forests would contribute to the scientific assessment of forest C cycling under disturbance.

How important is Forest Age in explaining the species composition of Near-natural Spruce Forests?

Multiple ecological drivers, along with forest age, determine the species composition of boreal forest ecosystems. However, the role of age in successional changes in forests cannot be understood without taking site conditions, the disturbance regime and forest structure into account. In this study, we ask two research questions: 1. What is the relationship between forest age and overall species composition in older near-natural spruce forests, i.e. forests of age beyond harvest maturity? 2. Do species associated with different forest habitats respond similarly to variation in forest age? Data were collected in 257 Norway spruce dominated 0.25 ha plots from three study areas in Southeastern and Central Norway. Species inventories were conducted for lichens and bryophytes on trees and rocks, vascular plants on the forest floor, and for deadwood-associated bryophytes and polypore fungi. Although NMDS ordination analyses of the total species composition identified a main axis related to the age of the oldest trees in two of the study areas, variation partitioning analyses showed that age explained a small fraction of variation of the species composition compared to site conditions, logging history, forest structure, and differences between the sites in all habitats. The unique variation explained by forest age species was, however, significant for all habitats. The fraction of variation in species composition explained by forest age was the largest for lichens and bryophytes on trees, and for deadwood-associated bryophytes and polypore fungi. Our results suggest that practical mapping of near-natural forests for management purposes inventories should include site conditions, forest structure and between site differences in addition to forest age.

Phloem-feeding insects create parasitoid-free space for caterpillars

Seemingly small ecological changes can have large, ramifying effects that defy expectations. Such are keystone effects in ecosystems. Phloem-feeding insect herbivores can act as keystone species by altering community structure and species interactions via plant-mediated or ant-mediated mechanisms. Plant responses triggered by phloem feeders can disrupt tri-trophic interactions induced by leaf-chewing herbivores, while ants that tend phloem feeders can deter or prey on other arthropods. Here, we investigate how phloem-feeding herbivores change caterpillar-parasitoid interactions on Quercus alba (white oak) trees in natural forests. We factorially manipulated the presence of phloem-feeding insects as well as ant access on Q.alba branches over multiple years and sites and measured parasitism rates of co-occurring caterpillars. While 19.3% of caterpillars were parasitized when phloem feeders were removed, the presence of phloem feeders completely suppressed parasitism of caterpillars (0%). This stark pattern was consistent across the diverse community of phloem feeders and caterpillars. Our manipulation of ant access had no effect on parasitism of caterpillars, implicating a plant-mediated mechanism. We further assessed the mechanistic hypothesis that phloem feeders suppress plant emission of caterpillar-induced volatile compounds, which could disrupt host-location behavior by parasitoids of caterpillars. Phloem feeders indeed reduced concentrations of four volatile compounds, consistent with the putative plant volatile-mediated mechanism. Given the important role of parasitoids in controlling herbivore populations, this keystone effect of phloem feeders offers novel insight into community dynamics in forests and potentially other terrestrial ecosystems.

Inter-generational consistency of the ectomycorrhizal fungal community in a mixed pine-cedar post-fire stand.

The mutualistic interaction between trees and ectomycorrhizal fungi (EMF) can have a major effect on forest dynamics and specifically on seedling establishment. Here, we compared the EMF community composition associated with the roots of young saplings and mature trees of two co-habiting Pinaceae: Pinus halepensis and Cedrus deodara growing together in a post-fire forest plot, using fungal ITS metabarcoding. We found that the differences in the EMF community between the two sapling groups were mostly attributed to changes in the relative abundance of specific fungal species with little species turnover. Specifically, Tomentella showed high abundance on pine roots while Tuber, Russula and Sebacina were more common on the roots of cedars. The physical proximity to a specific host species was correlated with the EMF community composition of young saplings. Specifically, regardless of the sapling's own identity, the roots of saplings growing next to mature cedars had higher abundance of Tuber species while Tomentella coerulea, Russula densifolia and Tuber nitidum dominated saplings next to mature pines. Cedar saplings' shoot structure was correlated with a specific EMF species. Overall, these results suggest that when germinating next to mature trees, the EMF community of saplings could be determined by extrinsic factors such as the small-scale distribution of mature trees in the forest.

Spatial Pattern of Forest Age in China Estimated by the Fusion of Multiscale Information

Forest age is one of most important biological factors that determines the magnitude of vegetation carbon sequestration. A spatially explicit forest age dataset is crucial for forest carbon dynamics modeling at the regional scale. However, owing to the high spatial heterogeneity in forest age, accurate high-resolution forest age data are still lacking, which causes uncertainty in carbon sink potential prediction. In this study, we obtained a 1 km resolution forest map based on the fusion of multiscale age information, i.e., the ninth (2014–2018) forest inventory statistics of China, with high accuracy at the province scale, and a field-observed dataset covering 6779 sites, with high accuracy at the site scale. Specifically, we first constructed a random forest (RF) model based on field-observed data. Utilizing this model, we then generated a spatially explicit forest age map with a 1 km resolution (random forest age map, RF map) using remotely sensed data such as tree height, elevation, meteorology, and forest distribution. This was then used as the basis for downscaling the provincial-scale forest inventory statistics of the forest ages and retrieving constrained maps of forest age (forest inventory constrained age maps, FIC map), which exhibit high statistical accuracy at both the province scale and site scale. The main results included the following: (1) RF can be used to estimate the site-scale forest age accurately (R2 = 0.89) and has the potential to predict the spatial pattern of forest age. However, (2) owing to the impacts of sampling error (e.g., field-observed sites are usually located in areas exhibiting relatively favorable environmental conditions) and the spatial mismatch among different datasets, the regional-scale forest age predicted by the RF model could be overestimated by 71.6%. (3) The results of the downscaling of the inventory statistics indicate that the average age of forests in China is 35.1 years (standard deviation of 21.9 years), with high spatial heterogeneity. Specifically, forests are older in mountainous and hilly areas, such as northeast, southwest, and northwest China, than in southern China. The spatially explicit dataset of the forest age retrieved in this study encompasses synthesized multiscale forest age information and is valuable for the research community in assessing the carbon sink potential and modeling carbon dynamics.

Exploring how community context informs variations in local perceptions of forest disturbance and land management in Colorado over time

Place-based socio-economic and biophysical context has been viewed as an essential driver in shaping perceptions of forest risks and land management. Growing evidence of the importance of diverse community context in forested landscapes sets the stage to further consider how people's understandings of their local environment influence natural resource management preferences. However, research to date largely lacks considerations of how community context informs social responses to long-term environmental change over time. Using the mountain pine beetle (MPB) outbreak in Colorado, we analyze and compare longitudinal interview and survey data collected from nine north-central Colorado communities to understand the relationships between community context and changing perceptions of forest disturbance and engagement with land management. Both qualitative and quantitative findings show that community context framed and continues to inform variations in local perceptions of the MPB outbreak and forest management. Interviews with key informants provided rich narratives on different context-based trajectories in local residents' perceptional responses, while survey data allowed for general patterns of evolving community variations (e.g., stable or clearer community clustering, reduced community differences) to be uncovered. We explore methodological implications for community indication and future directions for understanding differing community responses to slow-moving environmental change. Incorporating knowledge of changing local contexts and variations can also help practitioners advance toward more dynamic and effective management strategies.

Tree-ring based forest model calibrations with a deep learning algorithm

Process-based forest growth models are important tools for forest management and studies for forest growth, carbon sequestration, and forest dynamics. However, their reliable simulations rely not only on the quality of model construction but also on accurate parameters to appropriately depict various physiological and biophysical processes in the models. While explicit physiological measurements are excellent sources for model parameterization, they are not always readily available. It would be ideal to use easy-to-measure tree-ring data as a benchmark for parametrization, but such applications have been rare. Here we present a new approach to reasonably parameterize a stand growth model based on tree-ring data using deep learning algorithms. We integrated a stable carbon isotope (δ13C) version of a simple process-based stand growth model, 3-PG, into a recurrent neural network (RNN). The new 3PG-RNN model trained the RNN network and calibrated 3-PG parameters to minimize the mean squared error between the 3-PG outputs and targeted values. We then tested 3PG-RNN based on two Abies grandis stands located in Northern Idaho, USA. The results showed that the 3PG-RNN model was efficient in calibrating key parameters related to gas-exchange processes, including specifically quantum yield, maximum canopy conductance, and the slope function for stomatal responses to vapor pressure deficit. These calibrated parameters provided reasonable simulations for gas-exchanges similar to those constrained by explicit physiological observations. This was particularly true when both long-term diameter growth (estimated from tree-ring width) and tree-ring δ13C were used for model training. The RNN tool made it possible to use tree ring data as the key benchmark to calibrate the forest model and provide unbiased simulations for gas exchanges and forest growth with the RNN approach, which would greatly facilitate forest studies and management.

The unidirectional relationship between forest disturbance and armed conflict in the Andean Paramo

The armed conflict in Colombia has profoundly transformed rural landscapes, significantly impacting local communities. Sumapaz, the world's largest paramo, is a crucial water source for over 15 million people in the central Andean region of Colombia. Historically, the paramo functioned as a strategic corridor for the leftist guerrilla Fuerzas Armadas Revolucionarias de Colombia (FARC) to gain access to Bogotá for a potential armed takeover of political power. The specific impact of the conflict between the FARC and the Colombian army in the paramo, as well as the effects of conflict de-escalation, remain understudied. By analyzing forest disturbances and records on victims and conflict events, we identified a unidirectional relationship between the intensity of armed conflict and landscape transformation. Forest disturbances were significantly higher during the armed conflict (2001-2012). In contrast, forest disturbances have markedly decreased since the beginning of peace negotiations in 2012 and the subsequent peace agreement period 2016-2020. These findings contrast with documented trends in other regions of the country, such as the Andean and Amazonian areas. Our results demonstrate that the legacy of armed confrontation between the Colombian army and FARC in the paramo negatively impacted the landscape. Importantly, these findings provide valuable insights into conservation policies and environmental management during the post-peace agreement era, offering an opportunity to develop future preservation actions and shape the future of the Andean Paramo.

Understanding hurricane effects on forestlands: Land cover changes and salvage logging

Hurricanes can cause catastrophic damage to forestlands, prompting forest owners to engage in salvage logging to mitigate losses and resulting in a sudden and pronounced impact on the timber supply. At the same time, salvaging efforts have profound ecological repercussions, reshaping forest dynamics and affecting vital ecosystem processes. Given the relevant impact of salvage logging to the timber market and its potential ecological effects, evaluating the main factors motivating or limiting its occurrence and the common spatial patterns of salvage sites could offer valuable support for post-storm management efforts following future hurricane events.This study evaluates the land cover change (LCC) of forested areas following hurricanes, recognizing that the change to land cover classification could be derived from storm damage or additional modifications, such as salvage logging activities. We used a set of predictive machine learning models to investigate the primary factors influencing these modifications and determining a possible connection to salvage operations. To serve this purpose, we selected variables that relate to both forest’s vulnerability to hurricane disturbance and salvage site selection criteria. This research was centered primarily on the category-five Hurricane Michael, using three additional hurricanes of different intensities to compare results. Random Forest was the bestperforming model for predicting LCC in all cases, having wind speed and distance to nearest wood-consuming mills as the most important features when trained on Hurricane Michael data, emphasizing the relevance of market- and operation-related variables alongside weather disturbance aspects. The findings of our study lead us to infer that the observed modifications in land cover following hurricanes likely represent an additional transformation induced by the removal of damaged timber material, potentially serving as a proxy for salvage logging activities.

Tracking shifts in forest structural complexity through space and time in human‐modified tropical landscapes

Habitat structural complexity is an emergent property of ecosystems that directly shapes their biodiversity, functioning and resilience to disturbance. Yet despite its importance, we continue to lack consensus on how best to define structural complexity, nor do we have a generalised approach to measure habitat complexity across ecosystems. To bridge this gap, here we adapt a geometric framework developed to quantify the surface complexity of coral reefs and apply it to the canopies of tropical rainforests. Using high‐resolution, repeat‐acquisition airborne laser scanning data collected over 450 km2 of human‐modified tropical landscapes in Borneo, we generated 3D canopy height models of forests at varying stages of recovery from logging. We then tested whether the geometric framework of habitat complexity – which characterises 3D surfaces according to their height range, rugosity and fractal dimension – was able to detect how both human and natural disturbances drive variation in canopy structure through space and time across these landscapes. We found that together, these three metrics of surface complexity captured major differences in canopy 3D structure between highly degraded, selectively logged and old‐growth forests. Moreover, the three metrics were able to track distinct temporal patterns of structural recovery following logging and wind disturbance. However, in the process we also uncovered several important conceptual and methodological limitations with the geometric framework of habitat complexity. We found that fractal dimension was highly sensitive to small variations in data inputs and was ecologically counteractive (e.g. higher fractal dimension in oil palm plantations than old‐growth forests), while rugosity and height range were tightly correlated (r = 0.75) due to their strong dependency on maximum tree height. Our results suggest that forest structural complexity cannot be summarised using these three descriptors alone, as they overlook key features of canopy vertical and horizontal structure that arise from the way trees fill 3D space.Keywords: Forest disturbance, LiDAR, logging, recovery, remote sensing, structural complexity

Demographic and net primary productivity dynamics of primary and secondary tropical forests in Southwest China under a changing climate

AbstractTropical forests are major carbon sinks on the Earth's land surface. However, our understanding of how the demographic rate and carbon sink capacities of tropical forests respond to climate change remains limited. In this study, we investigated the impacts of environmental drivers on forest growth, mortality, recruitment, and stem net primary productivity (NPPstem) over 16 years at five tropical forest plots in Xishuangbanna, Southwest China. These plots are along a successional gradient spanning three tropical secondary forests (tropical secondary forest‐1 [TSF‐1], tropical secondary forest‐2 [TSF‐2], and tropical secondary forest‐3 [TSF‐3]) and two primary forests (tropical rainforest [TRF] and tropical karst forest [TKF]). Our results showed that early successional secondary forests (TSF‐2 and TSF‐3) had higher diameter growth rates and relative mortality rates. An extreme drought event during 2009–2010 reduced the growth rate, relative recruitment rate, and NPPstem for most plots while increasing mortality in early successional forest plots. We observed significant negative effects of maximum temperature (Tmax) on NPPstem and diameter growth rate across all plots. Additionally, we found that precipitation had significant positive effects on diameter growth rate across all plots. Furthermore, tree mortality increased with rising Tmax, whereas precipitation significantly enhanced tree recruitment. Our findings highlight the vulnerability of tree growth, mortality, recruitment, and productivity in tropical forests to extreme drought events in Southwest China. Continued climate warming and more frequent droughts will induce higher mortality rates and impede growth, thus reducing the carbon sink capacity of tropical forests, especially in early successional stage tropical secondary forests.