Effects of forest management practices on carbon dynamics of China's boreal forests under changing climates

Climate change and forest management practices influence forest productivity and carbon budgets, and understanding their interactions is necessary to develop accurate predictions of carbon dynamics as many countries in the world strive towards carbon neutrality. Here, we developed a model-coupling framework to simulate the carbon dynamics of boreal forests in China. The expected dynamics of forest recovery and change following intense timber harvesting in the recent past and projected carbon dynamics into the future under different climate change scenarios and forest management practices (e.g., restoration, afforestation, tending, and fuel management). We predict that under current management strategies, climate change would lead to increased fire frequency and intensity, eventually shifting these forests from carbon sinks towards being carbon sources. This study suggests that future boreal forest management should be altered to reduce the probability of fire occurrence and carbon losses caused by catastrophic fires through planting deciduous species, mechanical removal, and prescribed fire.

Targeting of rainwater harvesting structures using geospatial tools and analytical hierarchy process (AHP) in the semi-arid region of Rajasthan (India)

Burgeoning population growth and subsequent demand for freshwater, besides competition among irrigation, domestic, and industrial sectors, coupled with a changing climate, have necessitated prudent and effective management of water resources. Rainwater harvesting (RWH) is considered one of the most effective strategies for water management. However, the location and design of RWH structures are essential for proper implementation, operation, and maintenance. An attempt has been made in this study to locate the most suitable site for RWH structure and design using one of the robust multi-criteria decision analysis techniques, viz. analytic hierarchy process, using geospatial tools in the Gambhir watershed, Rajasthan, India. High-resolution Sentinel-2A data and a digital elevation model of the Advanced Land Observation Satellite were used in this study. Five biophysical parameters, viz. land use and land cover, slope, soil texture, surface runoff, and drainage density, were considered to identify suitable locations for RWH structures. It was observed that runoff is the prime factor in determining the location of RWH structures compared to other parameters. It was revealed that 75.54 km² (13% of the total area) was very highly suited for the construction of RWH structures, while 114.56 km² (19%) was highly suitable. A total of 43.77 km² (7%) of land was determined to be unsuitable for the construction of any type of RWH structure. Farm ponds, check dams, and percolation ponds were suggested for the study area. Furthermore, Boolean logic was used to target a particular type of RWH structure. The study indicated that a total of 25 farm ponds, 14 check dams, and 16 percolation ponds can be constructed at identified locations in the watershed. Water resource development maps of the watershed generated using an analytical approach would be useful for policymakers and hydrologists for targeting and implementing RWH structures in the study watershed.

Root nitrogen uptake capacity of Chinese fir enhanced by warming and nitrogen addition

There is a knowledge gap in the effects of climate warming and nitrogen (N) deposition on root N absorption capacity, which limits our ability to predict how climate change alters the N cycling and its consequences for forest productivity especially in subtropical areas where soil N availability is already high. In order to explore the effects and mechanism of warming and the N deposition on root N absorption capacity of Chinese fir (Cunninghamia lanceolata), a subtropical arbuscular mycorrhizal conifer, the fine root 15NH4+ and 15NO3- uptake kinetics at a reference temperature of 20 °C were measured across different seasons in a factorial soil warming (ambient, +5 °C) × N addition (ambient, +40 kg N ha-1 yr-1) experiment. The results showed that (i) compared with the control, warming increased the maximal uptake rate of NH4+ (Vmax,20 °C-NH4+) in summer, while N addition enhanced it in spring and summer; compared with non-warming treatments, warming treatments increased the uptake rate of NO3- at a reference concentration of 100 μmol (V100,20 °C-NO3-) in spring. (ii) The analysis of covariance showed that Vmax,20 °C-NH4+ was positively correlated with root mycorrhizal colonization rate (MCR) and V100,20 °C-NO3- was positively correlated with specific root respiration rate (SRR), whereas no N uptake kinetic parameter was correlated with specific root length, root N and non-structural carbon concentrations. Thus, our results demonstrate that warming-increased root NH4+ uptake might be related to warming-increased MCR, whereas warming-increased root NO3- uptake might be related to warming-increased SRR. We conclude that root NH4+ and NO3- uptake capacity of subtropical Chinese fir can be elevated under warming and N deposition, which could improve plantation productivity and mitigate N leaching loss and soil acidification.

Climate change, fire return intervals and the growing risk of permanent forest loss in boreal Eurasia

Climate change has driven an increase in the frequency and severity of fires in Eurasian boreal forests. A growing number of field studies have linked the change in fire regime to post-fire recruitment failure and permanent forest loss. In this study we used four burned area and two forest loss datasets to calculate the landscape-scale fire return interval (FRI) and associated risk of permanent forest loss. We then used machine learning to predict how the FRI will change under a high emissions scenario (SSP3-7.0) by the end of the century. We found that there are currently 133,000 km² forest at high, or extreme, risk of fire-induced forest loss, with a further 3 M km² at risk by the end of the century. This has the potential to degrade or destroy some of the largest remaining intact forests in the world, negatively impact the health and economic wellbeing of people living in the region, as well as accelerate global climate change.

Higher tree diversity is linked to higher tree mortality

Examining the relationship between tree diversity and ecosystem functioning has been a recent focus of forest ecology. Particular emphasis has been given to the impact of tree diversity on productivity and to its potential to mitigate negative global change effects; however, little attention has been paid to tree mortality. This is critical because both tree mortality and productivity underpin forest ecosystem dynamics and therefore forest carbon sequestration. Neglecting tree mortality leaves a large part of the picture undocumented. Here we show that increasingly diverse forest stands have increasingly high mortality probabilities. We found that the most species-rich stands in temperate biomes had mortality probabilities more than sevenfold higher than monospecific stands (∼0.6% year−1 in monospecific stands to 4.0% year−1 in the most species-rich stands) while in boreal stands increases were less pronounced but still significant (∼1.1% year−1 in monospecific stands to 1.8% year−1 in the most species-rich stands). Tree species richness was the third-most-important predictor of mortality in our models in temperate forests and the fifth-most-important predictor in boreal forests. Our results highlight that while the promotion of tree diversity undoubtedly has many positive effects on ecosystem functioning and the services that trees provide to humanity, it remains important to consider all aspects of forest dynamics in order to properly predict the implications of maintaining and promoting tree diversity.

Site index as a predictor of the effect of climate warming on boreal tree growth

The boreal forest represents the terrestrial biome most heavily affected by climate change. However, no consensus exists regarding the impacts of these changes on the growth of tree species therein. Moreover, assessments of young tree responses in metrics transposable to forest management remain scarce. Here, we assessed the impacts of climate change on black spruce (Picea mariana [Miller] BSP) and jack pine (Pinus banksiana Lambert) growth, two dominant tree species in boreal forests of North America. Starting with a retrospective analysis including data from 2591 black spruces and 890 jack pines, we forecasted trends in 30-year height growth at the transitions from closed to open boreal coniferous forests in Québec, Canada. We considered three variables: (1) height growth, rarely used, but better-reflecting site potential than other growth proxies, (2) climate normals corresponding to the growth period of each stem, and (3) site type (as a function of texture, stoniness, and drainage), which can modify the effects of climate on tree growth. We found a positive effect of vapor pressure deficit on the growth of both species, although the effect on black spruce leveled off. For black spruce, temperatures had a positive effect on the height at 30 years, which was attenuated when and where climatic conditions became drier. Conversely, drought had a positive effect on height under cold conditions and a negative effect under warm conditions. Spruce growth was also better on mesic than on rocky and sub-hydric sites. For portions of the study areas with projected future climate within the calibration range, median height-change varied from 10 to 31% for black spruce and from 5 to 31% for jack pine, depending on the period and climate scenario. As projected increases are relatively small, they may not be sufficient to compensate for potential increases in future disturbances like forest fires.

Use Remote Sensing and Machine Learning to Study the Changes of Broad-Leaved Forest Biomass and Their Climate Driving Forces in Nature Reserves of Northern Subtropics

Forest is the largest vegetation carbon pool in the global terrestrial ecosystem. The spatial distribution and change of forest biomass are of importance to reveal the surface spatial variation and driving factors, to analyze and evaluate forest productivity, and to evaluate ecological function of forest. In this study, broad-leaved forests located in a typical state nature reserve in northern subtropics were selected as the study area. Based on ground survey data and high-resolution remote sensing images, three machine learning models were used to identify the best remote sensing quantitative inversion model of forest biomass. The biomass of broad-leaved forest with 30-m resolution in the study area from 1998 to 2016 was estimated by using the best model about every two years. With the estimated biomass, multiple leading factors to cause biomass temporal change were then identified from dozens of remote sensing factors by investigating their nonlinear correlations. Our results showed that the artificial neural network (ANN) model was the best (R2 = 0.8742) among the three, and its accuracy was also much higher than that of the traditional linear or nonlinear models. The mean biomass of the broad-leaved forest in the study area from 1998 to 2016 ranged from 90 to 145 Mg ha−1, showing an obvious temporal variation. Instead of biomass, biomass change (BC) was studied further in this research. Significant correlations were found between BC in broad-leaved forest and three climate factors, including average daily maximum surface temperature, maximum precipitation, and maximum mean temperature. It was also found that BC has a strong correlation with the biomass at the previous time (i.e., two years ago). Those quantitative correlations were used to construct a linear model of BC with high accuracy (R2 = 0.8873), providing a new way to estimate the biomass change of two years later based on the observations of current biomass and the three climate factors.

Aboveground biomass increments over 26 years (1993-2019) in an old-growth cool-temperate forest in northern Japan

Assessing long-term changes in the biomass of old-growth forests with consideration of climate effects is essential for understanding forest ecosystem functions under a changing climate. Long-term biomass changes are the result of accumulated short-term changes, which can be affected by endogenous processes such as gap filling in small-scale canopy openings. Here, we used 26 years (1993-2019) of repeated tree census data in an old-growth, cool-temperate, mixed deciduous forest that contains three topographic units (riparian, denuded slope, and terrace) in northern Japan to document decadal changes in aboveground biomass (AGB) and their processes in relation to endogenous processes and climatic factors. AGB increased steadily over the 26 years in all topographic units, but different tree species contributed to the increase among the topographic units. AGB gain within each topographic unit exceeded AGB loss via tree mortality in most of the measurement periods despite substantial temporal variation in AGB loss. At the local scale, variations in AGB gain were partially explained by compensating growth of trees around canopy gaps. Climate affected the local-scale AGB gain: the gain was larger in the measurement periods with higher mean air temperature during the current summer but smaller in those with higher mean air temperature during the previous autumn, synchronously in all topographic units. The influences of decadal summer and autumn warming on AGB growth appeared to be counteracting, suggesting that the observed steady AGB increase in KRRF is not fully explained by the warming. Future studies should consider global and regional environmental factors such as elevated CO₂ concentrations and nitrogen deposition, and include cool-temperate forests with a broader temperature range to improve our understanding on biomass accumulation in this type of forests under climate change.

Assessing Pathways of Climate Change Effects in SpaDES: An Application to Boreal Landbirds of Northwest Territories Canada

Distributions of landbirds in Canadian northern forests are expected to be affected by climate change, but it remains unclear which pathways are responsible for projected climate effects. Determining whether climate change acts indirectly through changing fire regimes and/or vegetation dynamics, or directly through changes in climatic suitability may allow land managers to address negative trajectories via forest management. We used SpaDES, a novel toolkit built in R that facilitates the implementation of simulation models from different areas of knowledge to develop a simulation experiment for a study area comprising 50 million ha in the Northwest Territories, Canada. Our factorial experiment was designed to contrast climate effects pathways on 64 landbird species using climate-sensitive and non-climate sensitive models for tree growth and mortality, wildfire, and landbirds. Climate-change effects were predicted to increase suitable habitat for 73% of species, resulting in average net gain of 7.49 million ha across species. We observed higher species turnover in the northeastern, south-central (species loss), and western regions (species gain). Importantly, we found that most of the predicted differences in net area of occupancy across models were attributed to direct climate effects rather than simulated vegetation change, despite a similar relative importance of vegetation and climate variables in landbird models. Even with close to a doubling of annual area burned by 2100, and a 600 kg/ha increase in aboveground tree biomass predicted in this region, differences in landbird net occupancy across models attributed to climate-driven forest growth were very small, likely resulting from differences in the pace of vegetation and climate changes, or vegetation lags. The effect of vegetation lags (i.e., differences from climatic equilibrium) varied across species, resulting in a wide range of changes in landbird distribution, and consequently predicted occupancy, due to climate effects. These findings suggest that hybrid approaches using statistical models and landscape simulation tools could improve wildlife forecasts when future uncoupling of vegetation and climate is anticipated. This study lays some of the methodological groundwork for ecological adaptive management using the new platform SpaDES, which allows for iterative forecasting, mixing of modeling paradigms, and tightening connections between data, parameterization, and simulation.

Understanding and Modeling Forest Disturbance Interactions at the Landscape Level

Disturbances, both natural and anthropogenic, affect the configuration, composition, and function of forested ecosystems. Complex system behaviors emerge from the interactions between disturbance regimes, the vegetation response to those disturbances, and their interplay with multiple drivers (climate, topography, land use, etc.) across spatial and temporal scales. Here, we summarize conceptual advances and empirical approaches to disturbance interaction investigation, and used those insights to evaluate and categorize 146 landscape modeling studies emerging from a systematic review of the literature published since 2010. Recent conceptual advances include formal disaggregation of disturbances into their constituent components, embedding disturbance processes into system dynamics, and clarifying terminology for interaction factors, types, and ecosystem responses. Empirical studies investigating disturbance interactions now span a wide range of approaches, including (most recently) advanced statistical methods applied to an expanding set of spatial and temporal datasets. Concurrent development in spatially-explicit landscape models, informed by these empirical insights, integrate the interactions among natural and anthropogenic disturbances by coupling these processes to account for disturbance stochasticity, disturbance within and across scales, and non-linear landscape responses to climate change. Still, trade-offs between model elegance and complexity remain. We developed an index for the degree of process integration (i.e., balance of static vs. dynamic components) within a given disturbance agent and applied it to the studies from our systematic review. Contemporary model applications in this line of research have applied a wide range process integration, depending on the specific question, but also limited in part by data and knowledge. Non-linear “threshold” behavior and cross-scaled interactions remain a frontier in temperate, boreal, and alpine regions of North America and Europe, while even simplistic studies are lacking from other regions of the globe (e.g., subtropical and tropical biomes). Understanding and planning for uncertainty in system behavior—including disturbance interactions—is paramount at a time of accelerated anthropogenic change. While progress in landscape modeling studies in this area is evident, work remains to increase model transparency and confidence, especially for understudied regions and processes. Moving forward, a multi-dimensional approach is recommended to address the uncertainties of complex human-ecological dynamics.

Landscape-Scale Drivers of Resistance and Resilience to Bark Beetles: A Conceptual Susceptibility Model

Bark beetle (Dendroctonus spp.) outbreaks in the middle latitudes of western North America cause large amounts of tree mortality, outstripping wildfire by an order of magnitude. While temperatures play an important, and direct role in the population dynamics of ectothermic bark beetles, an equally important influence is the nature of the host substrate—the structure and composition of forested communities. For many of the dominant tree species in the western United States, “hazard” indices have been developed for specific bark beetles, which generally include three key variables—host tree size, absolute or relative density of the stand, and percentage of host composition. We provide a conceptual model to apply these three variables across forest ecosystems and bark beetles that shifts the thinking from a species–specific model to a model which focuses on the underlying ecological factors related to bark beetle outbreak susceptibility. We explored the use of our model across multiple scales using the Forest Inventory and Analysis database: Interior West, USA; the states of Colorado and Arizona; and specific national forests within Arizona that are implementing a large-scale restoration effort. We demonstrated that across the Interior West and Colorado, the vast majority of forests have moderate to high susceptibility to bark beetles. Our conceptual model maintains the simplicity of previous “hazard” models but acknowledges the need to consider scale when managing bark beetles. It also shifts the management approach from resistance thinking to the development of “associational resilience”, where the focus is not on any one individual stand or area but the longer-term perspective of forest persistence across the landscape.

Simulating the Effects of Intensifying Silviculture on Desired Species Yields across a Broad Environmental Gradient

In the past two decades, forest management has undergone major paradigm shifts that are challenging the current forest modelling architecture. New silvicultural systems, guidelines for natural disturbance emulation, a desire to enhance structural complexity, major advances in successional theory, and climate change have all highlighted the limitations of current empirical models in covering this range of conditions. Mechanistic models, which focus on modelling underlying ecological processes rather than specific forest conditions, have the potential to meet these new paradigm shifts in a consistent framework, thereby streamlining the planning process. Here we use the NEBIE (a silvicultural intervention scale that classifies management intensities as natural, extensive, basic, intensive, and elite) plot network, from across Ontario, Canada, to examine the applicability of a mechanistic model, ZELIG-CFS (a version of the ZELIG tree growth model developed by the Canadian Forest Service), to simulate yields and species compositions. As silvicultural intensity increased, overall yield generally increased. Species compositions met the desired outcomes when specific silvicultural treatments were implemented and otherwise generally moved from more shade-intolerant to more shade-tolerant species through time. Our results indicated that a mechanistic model can simulate complex stands across a range of forest types and silvicultural systems while accounting for climate change. Finally, we highlight the need to improve the modelling of regeneration processes in ZELIG-CFS to better represent regeneration dynamics in plantations. While fine-tuning is needed, mechanistic models present an option to incorporate adaptive complexity into modelling forest management outcomes.

Role of Mixed-Species Stands in Attenuating the Vulnerability of Boreal Forests to Climate Change and Insect Epidemics

We investigated whether stand species mixture can attenuate the vulnerability of eastern Canada's boreal forests to climate change and insect epidemics. For this, we focused on two dominant boreal species, black spruce [Picea mariana (Mill.) BSP] and trembling aspen (Populus tremuloides Michx.), in stands dominated by black spruce or trembling aspen ("pure stands"), and mixed stands (M) composed of both species within a 36 km² study area in the Nord-du-Québec region. For each species in each stand composition type, we tested climate-growth relations and assessed the impacts on growth by recorded insect epidemics of a black spruce defoliator, the spruce budworm (SBW) [Choristoneura fumiferana (Clem.)], and a trembling aspen defoliator, the forest tent caterpillar (FTC; Malacosoma disstria Hübn.). We implemented linear models in a Bayesian framework to explain baseline and long-term trends in tree growth for each species according to stand composition type and to differentiate the influences of climate and insect epidemics on tree growth. Overall, we found climate vulnerability was lower for black spruce in mixed stands than in pure stands, while trembling aspen was less sensitive to climate than spruce, and aspen did not present differences in responses based on stand mixture. We did not find any reduction of vulnerability for mixed stands to insect epidemics in the host species, but the non-host species in mixed stands could respond positively to epidemics affecting the host species, thus contributing to stabilize ecosystem-scale growth over time. Our findings partially support boreal forest management strategies including stand species mixture to foster forests that are resilient to climate change and insect epidemics.

Linkages between Climate, Radial Growth and Defoliation in Abies pinsapo Forests from Southern Spain

Systematic forest networks of health monitoring have been established to follow changes in tree vigor and mortality. These networks often lack long-term growth data, but they could be complemented with tree ring data, since both defoliation and radial growth are proxies of changes in tree vigor. For instance, a severe water shortage should reduce growth and increase tree defoliation in drought-prone areas. However, the effects of climatic stress and drought on growth and defoliation could also depend on tree age. To address these issues, we compared growth and defoliation data with recent climate variability and drought severity in Abies pinsapo old and young trees sampled in Southern Spain, where a systematic health network (Andalucía Permanent Plot Network) was established. Our aims were: (i) to assess the growth sensitivity of old and young A. pinsapo trees and (ii) to test if relative changes in radial growth were related with recent defoliation, for instance, after severe droughts. We also computed the resilience indices to quantify how old and young trees recovered growth after recent droughts. Wet-cool conditions during the prior autumn and the current early summer improved the growth of old trees, whereas late-spring wet conditions enhanced the growth of young trees. Old trees were more sensitive to wet and sunny conditions in the early summer than young trees. Old and young trees were more responsive to the Standardized Precipitation-Evapotranspiration Index drought index of June–July and July–August calculated at short (one–three months) and mid (three–six months) time scales, respectively. Old trees presented a higher resistance to a severe drought in 1995 than young trees. A positive association was found between stand defoliation and relative growth. Combining monitoring and tree ring networks is useful for the detection of early warning signals of dieback in similar drought-prone forests.

Hundred year projected carbon loads and species compositions for four National Forests in the northwestern USA

BACKGROUND

Forests are an important component of the global carbon balance, and climate sensitive growth and yield models are an essential tool when predicting future forest conditions. In this study, we used the dynamic climate capability of the Forest Vegetation Simulator (FVS) to simulate future (100 year) forest conditions on four National Forests in the northwestern USA: Payette National Forest (NF), Ochoco NF, Gifford Pinchot NF, and Siuslaw NF. Using Forest Inventory and Analysis field plots, aboveground carbon estimates and species compositions were simulated with Climate-FVS for the period between 2016 and 2116 under a no climate change scenario and a future climate scenario. We included a sensitivity analysis that varied calculated disturbance probabilities and the dClim rule, which is one method used by Climate-FVS to introduce climate-related mortality. The dClim rule initiates mortality when the predicted climate change at a site is greater than the change in climate associated with a predetermined shift in elevation.

RESULTS

Results of the simulations indicated the dClim rule influenced future carbon projections more than estimates of disturbance probability. Future aboveground carbon estimates increased and species composition remained stable under the no climate change scenario. The future climate scenario we tested resulted in less carbon at the end of the projections compared to the no climate change scenarios for all cases except when the dClim rule was disengaged on the Payette NF. Under the climate change scenario, species compositions shifted to climatically adapted species or early successional species.

CONCLUSION

This research highlights the need to consider climate projections in long-term planning or future forest conditions may be unexpected. Forest managers and planners could perform similar simulations and use the results as a planning tool when analyzing climate change effects at the National Forest level.

Complementarity effects are strengthened by competition intensity and global environmental change in the central boreal forests of Canada

Increases in niche complementarity have been hypothesised to reduce the intensity of interspecific competition within natural forests. In regions currently experiencing potentially enhanced growth under global environmental change, niche complementarity may become even more beneficial. However, few studies have provided direct evidence of this mechanism. Here, we use data from 180 permanent sample plots in Manitoba, Canada, with a full spatial mapping of all stems, to show that complementarity effects on average increased with neighbourhood competition intensity and temporally rising CO₂ , warming and water availability. Importantly, complementarity effects increased with both shade tolerance and phylogenetic dissimilarity between the focal tree and its neighbours. Our results provide further evidence that increasing stand functional and phylogenetic diversity can improve individual tree productivity, especially for individuals experiencing intense competition and may offer an avenue to maintain productivity under global environmental change.

Taxonomy, together with ontogeny and growing conditions, drives needleleaf species' sensitivity to climate in boreal North America

Currently, there is no consensus regarding the way that changes in climate will affect boreal forest growth, where warming is occurring faster than in other biomes. Some studies suggest negative effects due to drought-induced stresses, while others provide evidence of increased growth rates due to a longer growing season. Studies focusing on the effects of environmental conditions on growth-climate relationships are usually limited to small sampling areas that do not encompass the full range of environmental conditions; therefore, they only provide a limited understanding of the processes at play. Here, we studied how environmental conditions and ontogeny modulated growth trends and growth-climate relationships of black spruce (Picea mariana) and jack pine (Pinus banksiana) using an extensive dataset from a forest inventory network. We quantified the long-term growth trends at the stand scale, based on analysis of the absolutely dated ring-width measurements of 2,266 trees. We assessed the relationship between annual growth rates and seasonal climate variables and evaluated the effects of various explanatory variables on long-term growth trends and growth-climate relationships. Both growth trends and growth-climate relationships were species-specific and spatially heterogeneous. While the growth of jack pine barely increased during the study period, we observed a growth decline for black spruce which was more pronounced for older stands. This decline was likely due to a negative balance between direct growth gains induced by improved photosynthesis during hotter-than-average growing conditions in early summers and the loss of growth occurring the following year due to the indirect effects of late-summer heat waves on accumulation of carbon reserves. For stands at the high end of our elevational gradient, frost damage during milder-than-average springs could act as an additional growth stressor. Competition and soil conditions also modified climate sensitivity, which suggests that effects of climate change will be highly heterogeneous across the boreal biome.

Models ignoring spatial heterogeneities of forest age will significantly overestimate the climate effects on litterfall in China

Litterfall is an important process that links vegetation and soil pools and plays an important role in the maintenance of soil fertility. Although studies indicated that climate will significantly affect forest litterfall, the role of biotic factors such as the spatial heterogeneity of forest age, remains unclear. In this study, we built an updated dataset of litterfall in China and explored the key drivers affecting forest litterfall by establishing optimal linear mixed models (OLMMs). The potential bias of models and their spatial patterns were then evaluated based on the OLMMs and remotely sensed and China's forest inventory data. The results showed the mean annual temperature (MAT) and forest age were the key drivers affecting forest litterfall. Abiotic factors and forest age and height together accounted for 77.5% of the variation in observed litterfall. Although forest age and height did not apparently enhance the coefficient of determination (R²), these factors significantly decreased spatial errors. Therefore, if the model contains only climate factors and the spatial patterns of biotic factors are ignored, it will produce high spatial errors (-52% to 92%). In addition, when forest age and height were not considered, variation of litterfall explained by forest age was inappropriately attributed to MAT, which significantly overestimated the importance of climate factors on forest litterfall. Specifically, litterfall was overestimated for young forests and underestimated for old forests if the model did not contain forest age in China. Models that ignored forest age significantly overestimated the contribution of climatic factors on forest litterfall and produced high spatially specific errors. The comparison of the litterfall modeled by OLMMs and the remote sensing-based net primary production (NPP) indicated that litterfall and NPP are strongly dependent, and the ratio of litterfall to NPP linearly increased with forest age.

Tree rings provide no evidence of a CO2 fertilization effect in old-growth subalpine forests of western Canada

Atmospheric CO₂ concentrations are now 1.7 times higher than the preindustrial values. Although photosynthetic rates are hypothesized to increase in response to rising atmospheric CO₂ concentrations, results from in situ experiments are inconsistent in supporting a CO₂ fertilization effect of tree growth. Tree-ring data provide a historical record of tree-level productivity that can be used to evaluate long-term responses of tree growth. We use tree-ring data from old-growth, subalpine forests of western Canada that have not had a stand-replacing disturbance for hundreds of years to determine if growth has increased over 19th and 20th centuries. Our sample consisted of 5,858 trees belonging to five species distributed over two sites in the coastal zone and two in the continental climate of the interior. We calculated annual increments in tree basal area, adjusted these increments for tree size and age, and tested whether there was a detectable temporal trend in tree growth over the 19th and 20th centuries. We found a similar pattern in 20th century growth trends among all species at all sites. Growth during the 19th century was mostly stable or increasing, with the exception of one of the coastal sites, where tree growth was slightly decreasing; whereas growth during the 20th century consistently decreased. The unexpected decrease in growth during the 20th century indicates that there was no CO₂ fertilization effect on photosynthesis. We compared the growth trends from our four sites to the trends simulated by seven Earth System Models, and saw that most of the models did not predict these growth declines. Overall, our results indicate that these old-growth forests are unlikely to increase their carbon storage capacity in response to rising atmospheric CO₂ , and thus are unlikely to contribute substantially to offsetting future carbon emissions.

Drivers of tree carbon storage in subtropical forests

Tropical and subtropical forest ecosystems play an important role in the global carbon regulation. Despite increasing evidence for effects of biodiversity (species diversity, functional diversity and functional dominance), stand structural attributes, stand age and environmental conditions (climate and topography) on tree carbon storage, the relative importance of these drivers at large scale is poorly understood. It is also still unclear whether biodiversity effects on tree carbon storage work through niche complementarity (i.e. increased tree carbon storage due to interspecific resource partitioning) or through the mass-ratio effect (tree carbon storage regulated by dominant traits within communities). Here we analyze tree carbon storage and its drivers using data of 480 plots sampled across subtropical forests in China. We use multiple regression models to test the relative effects of biodiversity, stand structural attributes, stand age and environmental conditions on tree carbon storage, and use a partial least squares path model to test how these variables directly and/or indirectly affect tree carbon storage. Our results show that tree carbon storage is most strongly affected by stand age, followed by climate, biodiversity and stand structural attributes. Stand age and climate had both direct and indirect (through species diversity, functional dominance and stand structural attributes) effects. We find that tree carbon storage correlates with both species diversity and functional dominance after stand age and environmental drivers are accounted for. Our results suggest that niche complementarity and the mass-ratio effect, not necessarily mutually exclusive, both play a role in maintaining ecosystem functioning. Our results further indicate that biodiversity conservation might be an effective way for enhancing tree carbon storage in natural, species-rich forest ecosystems.

Future biomass carbon sequestration capacity of Chinese forests

Chinese forests, characterized by relatively young stand age, represent a significant biomass carbon (C) sink over the past several decades. Nevertheless, it is unclear how forest biomass C sequestration capacity in China will evolve as forest age, climate and atmospheric CO₂ concentration change continuously. Here, we present a semi-empirical model that incorporates forest age and climatic factors for each forest type to estimate the effects of forest age and climate change on total forest biomass, under three different scenarios based on the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We estimate that age-related forest biomass C sequestration to be 6.69 Pg C (∼0.17 Pg C a^-1) from the 2000s to the 2040s. Climate change induces a rather weak increase in total forest biomass C sequestration (0.52-0.60 Pg C by the 2040s). We show that rising CO₂ concentrations could further increase the total forest biomass C sequestration by 1.68-3.12 Pg C in the 2040s across all three scenarios. Overall, the total forest biomass in China would increase by 8.89-10.37 Pg C by the end of 2040s. Our findings highlight the benefits of Chinese afforestation programs, continued climate change and increasing CO₂ concentration in sustaining the forest biomass C sink in the near future, and could therefore be useful for designing more realistic climate change mitigation policies such as continuous forestation programs and careful choice of tree species.

Spatial variability of tree species diversity in a mixed tropical forest in Southern Brazil

Floristic surveys and diversity indices are often applied to measure tree species diversity in mixed tropical forest remnants. However, these analyses are frequently limited to the overall results and do not allow to evaluate the spatial variability distributions of tree diversity, leading to develop additional tools. This study aimed to estimate the spatial variability of tree diversity and map their spatial patterns in a Brazilian mixed tropical forest conservation area. We used indices to measure the tree species diversity (dbh ≥ 10 cm) in 400 sampling units (25 m x 25 m) from a continuous forest inventory. Semivariograms were fitted to estimate spatial dependences and punctual kriging was applied to compose maps. Mean diversity values were constant in the continuous inventories, indicating a forest remnant in an advanced stage of ecological succession. On the other hand, tree diversity presented spatial patterns identified by geostatistics, in which the dynamics were composed of heterogeneous mosaics spatially influenced by tree species with different ecological features and densities, gap dynamics, advancement of forest succession, mortality, and Araucaria angustilofia's cohorts.

Interspecific variation in growth responses to tree size, competition and climate of western Canadian boreal mixed forests

Tree growth of boreal forest plays an important role on global carbon (C) cycle, while tree growth in the western Canadian boreal mixed forests has been predicted to be negatively affected by regional drought. Individual tree growth can be controlled by many factors, such as competition, climate, tree size and age. However, information about contributions of different factors to tree growth is still limited in this region. In order to address this uncertainty, tree rings of two dominant tree species, trembling aspen (Populus tremuloides Michx.) and white spruce (Picea glauca (Moench.) Voss), were sampled from boreal mixed forest stands distributed across Alberta, Canada. Tree growth rates over different time intervals (10years interval, 1998-2007; 20years interval, 1988-2007; 30years interval, 1978-2007) were calculated to study the effects of different factors (tree size, competition, climate, and age) on tree growth. Results indicated that tree growth of two species were both primarily affected by competition or tree size, while climatic indices showed less effects on tree growth. Growth of trembling aspen was significantly affected by inter- and intraspecific competition, while growth of white spruce was primarily influenced by tree size, followed by competition. Positive relationship was found between growth of white spruce and competition index of coniferous group, suggesting an intraspecific mutualism mechanism within coniferous group. Our results further suggested that competition driven succession was the primary process of forest composition shift in the western Canadian boreal mixed forest. Although drought stress increased tree mortality, decline of stem density under climate change released competition stress of surviving trees, which in turn sustained growth of surviving trees. Therefore, climatic indices showed fewer effects on growth of dominant tree species compared to other factors in our study.

Global effects of plant litter alterations on soil CO2 to the atmosphere

Soil respiration (Rs) is the largest terrestrial carbon (C) efflux to the atmosphere and is predicted to increase drastically through global warming. However, the responses of Rs to global warming are complicated by the fact that terrestrial plant growth and the subsequent input of plant litter to soil are also altered by ongoing climate change and human activities. Despite a number of experiments established in various ecosystems around the world, it remains a challenge to predict the magnitude and direction of changes in Rs and its temperature sensitivity (Q₁₀ ) due to litter alteration. We present a meta-analysis of 100 published studies to examine the responses of Rs and Q₁₀ to manipulated aboveground and belowground litter alterations. We found that 100% aboveground litter addition (double litter) increased Rs by 26.1% (95% confident intervals, 18.4%-33.7%), whereas 100% aboveground litter removal, root removal and litter + root removal reduced Rs by 22.8% (18.5%-27.1%), 34.1% (27.2%-40.9%) and 43.4% (36.6%-50.2%) respectively. Moreover, the effects of aboveground double litter and litter removal on Rs increased with experimental duration, but not those of root removal. Aboveground litter removal marginally increased Q₁₀ by 6.2% (0.2%-12.3%) because of the higher temperature sensitivity of stable C substrate than fresh litter. Estimated from the studies that simultaneously tested the responses of Rs to aboveground litter addition and removal and assuming negligible changes in root-derived Rs, "priming effect" on average accounted for 7.3% (0.6%-14.0%) of Rs and increased over time. Across the global variation in terrestrial ecosystems, the effects of aboveground litter removal, root removal, litter + root removal on Rs as well as the positive effect of litter removal on Q₁₀ increased with water availability. Our meta-analysis indicates that priming effects should be considered in predicting Rs to climate change-induced increases in litterfall. Our analysis also highlights the need to incorporate spatial climate gradient in projecting long-term Rs responses to litter alterations.

Control of "blue carbon" storage by mangrove ageing: Evidence from a 66-year chronosequence in French Guiana

The role of mangroves in the blue carbon stock is critical and requires special focus. Mangroves are carbon-rich forests that are not in steady-state equilibrium at the decadal time scale. Over the last decades, the structure and zonation of mangroves have been largely disturbed by coastal changes and land use conversions. The amount of time since the last disturbance is a key parameter determining forest structure, but it has so far been overlooked in mangrove carbon stock projections. In particular, the carbon sequestration rates among mangrove successional ages after (re)establishment are poorly quantified and not used in large-scale estimations of the blue carbon stock. Here, it is hypothesized that ecosystem age structure significantly modulates mangrove carbon stocks. We analysed a 66-year chronosequence of the aboveground and belowground biomass and soil carbon stock of mangroves in French Guiana, and we found that in the year after forest establishment on newly formed mud banks, the aboveground, belowground and soil carbon stocks averaged 23.56 ± 7.71, 13.04 ± 3.37 and 84.26 ± 64.14 (to a depth of 1 m) Mg C/ha, respectively. The mean annual increment (MAI) in the aboveground and belowground reservoirs was 23.56 × Age^-0.52 and 13.20 × Age^-0.64  Mg C ha^-1  year^-1 , respectively, and the MAI in the soil carbon reservoir was 3.00 ± 1.80 Mg C ha^-1  year^-1 . Our results show that the plant carbon sink capacity declines with ecosystem age, while the soil carbon sequestration rate remains constant over many years. We suggest that global projections of the above- and belowground reservoirs of the carbon stock need to account for mangrove age structures, which result from historical changes in coastal morphology. Our work anticipates joint international efforts to globally quantify the multidecadal mangrove carbon balance based on the combined use of age-based parametric equations and time series of mangrove age maps at regional scales.

Detecting early warning signals of tree mortality in boreal North America using multiscale satellite data

Increasing tree mortality from global change drivers such as drought and biotic infestations is a widespread phenomenon, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and improve mortality forecasts: repeat forest inventories and satellite remote sensing. Time series of tree-level growth patterns indicate that productivity declines and related temporal dynamics often precede mortality years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized difference vegetation index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 24 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range of forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although the utility of coarse-scale imagery in the heterogeneous aspen parkland was limited. Longer-term NDVI data and annually remeasured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites remeasured at a typical 5 year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.

Temporal changes in soil C-N-P stoichiometry over the past 60 years across subtropical China

Controlled experiments have shown that global changes decouple the biogeochemical cycles of carbon (C), nitrogen (N), and phosphorus (P), resulting in shifting stoichiometry that lies at the core of ecosystem functioning. However, the response of soil stoichiometry to global changes in natural ecosystems with different soil depths, vegetation types, and climate gradients remains poorly understood. Based on 2,736 observations along soil profiles of 0-150 cm depth from 1955 to 2016, we evaluated the temporal changes in soil C-N-P stoichiometry across subtropical China, where soils are P-impoverished, with diverse vegetation, soil, and parent material types and a wide range of climate gradients. We found a significant overall increase in soil total C concentration and a decrease in soil total P concentration, resulting in increasing soil C:P and N:P ratios during the past 60 years across all soil depths. Although average soil N concentration did not change, soil C:N increased in topsoil while decreasing in deeper soil. The temporal trends in soil C-N-P stoichiometry differed among vegetation, soil, parent material types, and spatial climate variations, with significantly increased C:P and N:P ratios for evergreen broadleaf forest and highly weathered Ultisols, and more pronounced temporal changes in soil C:N, N:P, and C:P ratios at low elevations. Our sensitivity analysis suggests that the temporal changes in soil stoichiometry resulted from elevated N deposition, rising atmospheric CO₂ concentration and regional warming. Our findings revealed that the responses of soil C-N-P and stoichiometry to long-term global changes have occurred across the whole soil depth in subtropical China and the magnitudes of the changes in soil stoichiometry are dependent on vegetation types, soil types, and spatial climate variations.

Genetic Diversity among Age Classes of a Pinus sylvestris (L.) Population from the Białowieża Primeval Forest, Poland

The Białowieża Primeval Forest (BPF) is Europe’s last primeval forest and an irreplaceable area for biodiversity conservation due to its size, protection status, and substantially undisturbed nature. There is no other forest in Europe with such a large surface representing highly-advanced natural succession. This article reports on the first analysis of the genetic variability and demographic structure of a self-renewed Pinus sylvestris population located in BPF, using both chloroplast and mitochondrial DNA markers. The analysis of molecular variance (AMOVA) for chloroplast simple sequence repeats (cpSSRs) revealed a significant genetic differentiation among age classes that accounted for about 2% of the total variance, comparable to those reported among different populations of Scots pine. None of the 117 detected chloroplast haplotypes were common to all age classes. Haplotype diversity ranged from 0.370 to 0.415 for cpSSRs and from 0.320 to 0.455 for mitochondrial markers. The genetic variation of the studied age classes—represented by mitochondrial markers—strongly depicts the maternal genetic structure, indicating limited seed dispersal. Temporal genetic substructuring is maintained within a self-renewed population of Scots pine from the BPF.