Contrasting water-use strategies to climate warming in white birch and larch in a boreal permafrost region.

The effects of rising atmospheric CO2 concentrations (Ca) with climate warming on intrinsic water-use efficiency and radial growth in boreal forests are still poorly understood. We measured tree-ring cellulose δ13C, δ18O, and tree-ring width in Larix dahurica (larch) and Betula platyphylla (white birch), and analyzed their relationships with climate variables in a boreal permafrost region of northeast China over past 68 years covering a pre-warming period (1951-1984; base period) and a warm period (1985-2018; warm period). We found that white birch but not larch significantly increased their radial growth over the warm period. The increased intrinsic water-use efficiency in both species was mainly driven by elevated Ca but not climate warming. White birch but not larch showed significantly positive correlations between tree-ring δ13C, δ18O and summer maximum temperature as well as vapor pressure deficit in the warm period, suggesting a strong stomatal response in the broad-leaved birch to temperature changes. The climate warming-induced radial growth enhancement in white birch is primarily associated with a conservative water-use strategy. In contrast, larch exhibits a profligate water-use strategy. It implies an advantage for white birch over larch in the warming permafrost regions.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit.

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

Impacts of snow cover seasonality on spring land surface phenology of forests in Changbai mountains of Northeast China.

Snow cover phenology (SCP) strongly affects forest spring phenology (the start of growing season, SOS), but the underlying mechanism of the relationship varies. In this study, we aimed to analyze the relationship between forest SOS and SCP, and investigate the mechanisms about how changes of SCP affect forest SOS. To do so, we extracted forest SOS and SCP from multiple remote sensing datasets and analyzed the spatio-temporal patterns of both in Changbai Mountains (2001-2020). We assessed the relationships between SCP and forest SOS using partial least squares regression analysis and investigated the potential mechanism of SCP changes affecting on forest SOS using path analysis. We found earlier forest SOS (-0.5 days/year), prolonged snow cover duration (SCD, 0.43 day/year), and earlier snow cover end day (SCED, -0.1 days/year) in the region. The results indicated that SCD showed negative influence while SCED showed positive influence on forest SOS in most of the region. Results revealed that the influence of SCP on forest SOS was mainly through altering spring temperature and the dominant path of SCP influencing forest SOS followed hydrothermal gradients. Our study reveals new insights into the influence of changing SCP on forest SOS, which provides the theoretical basis for including SCP in the phenological models.

Private land management is more important than public land in sustaining oaks in temperate forests in the eastern U.S.

Preserving the abundance and stocking of oaks (Quercus spp.) has become increasingly challenging in temperate hardwood forests of the eastern US in recent decades due to a remarkable shift in dominance to mesophytic species (e.g., red maple Acer rubrum). Studies have shown that efforts to sustain oaks while restraining maples yield limited success. Given that a significant portion of forestlands in the eastern U.S. are privately owned, it is critical to assess whether current forest management on cross-ownership forests can achieve those objectives. However, such assessments are rare. In this study, we employed a landscape modeling approach to investigate the long-term outcomes (i.e., 150-year forest composition and structure) of business-as-usual management and alternative management in a large, temperate hardwood forest landscape in Ohio, US. The business-as-usual management continues the current existing management practices, whereas the alternative management increases the pace and scale of forest management on both private and public lands to favor oaks. We compared the basal area and relative dominance for oaks (including Q. alba, Q. coccinea, Q. prinus, Q. rubra, and Q. velutina) and maples (including A. rubrum, A. saccharinum, and A. saccharum). Our results demonstrate that the implementation of business-as-usual management practices on both private and public lands may not effectively ensure the long-term sustainability of oak populations, but instead promote the proliferation of maple species over time. By contrast, alternative management on both private and public lands can effectively sustain oaks across a range of diameter classes while mitigating the growth of large, dominant maples. Our study emphasizes the influential role of private lands in driving oak-maple dynamics at the regional scale, as they can generate significant regional effects even when public lands continue with their business-as-usual management practices. Starting conditions based on landownership are crucial considerations for understanding these dynamics over time.

Cotton cultivated area detection and yield monitoring combining remote sensing with field data in lower Indus River basin, Pakistan.

As the Earth's population continuously increase with the passage of time, the demand for agricultural raw material for human need increases. It is critical to maintaining updated and accurate information about the dynamics and properties of the world agricultural systems. As cash crop, the updated information of the spatial distribution of cotton field is necessary to monitor the crop area and growth changes at regional level. We used 8-day enhanced vegetation index (EVI) time series to detect cotton crop area and binomial probabilistic approach to obtain the probability distribution of cotton crop occurrence. We used Gaussian kriging to derive cotton yield inside the detected cotton crop areas through crop reporting data. We also used field data from farmers to validate the cotton yield results. A strong correlation between the MODIS-derived cotton cultivated area and statistical data at the tehsil level were achieved (R2 = 0.84) for all study years (2004-2019). The total accuracy for the cotton crop area detection was 84.6% and yield prediction was 92.1%. Our study presents new approaches to map cotton area and yield, which are applicable to other regions through machine learning.

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.

What is the role of disturbance in catalyzing spatial shifts in forest composition and tree species biomass under climate change?

Mounting evidence suggests that climate change will cause shifts of tree species range and abundance (biomass). Abundance changes under climate change are likely to occur prior to a detectable range shift. Disturbances are expected to directly affect tree species abundance and composition, and could profoundly influence tree species spatial distribution within a geographical region. However, how multiple disturbance regimes will interact with changing climate to alter the spatial distribution of species abundance remains unclear. We simulated such forest demographic processes using a forest landscape succession and disturbance model (LANDIS-II) parameterized with forest inventory data in the northeastern United States. Our study incorporated climate change under a high-emission future and disturbance regimes varying with gradients of intensities and spatial extents. The results suggest that disturbances catalyze changes in tree species abundance and composition under a changing climate, but the effects of disturbances differ by intensity and extent. Moderate disturbances and large extent disturbances have limited effects, while high-intensity disturbances accelerate changes by removing cohorts of mid- and late-successional species, creating opportunities for early-successional species. High-intensity disturbances result in the northern movement of early-successional species and the southern movement of late-successional species abundances. Our study is among the first to systematically investigate how disturbance extent and intensity interact to determine the spatial distribution of changes in species abundance and forest composition.

Root Carbon Resources Determine Survival and Growth of Young Trees Under Long Drought in Combination With Fertilization.

Current increases in not only the intensity and frequency but also the duration of drought events could affect the growth, physiology, and mortality of trees. We experimentally studied the effects of drought duration in combination with fertilization on leaf water potential, gas exchange, growth, tissue levels of non-structural carbohydrates (NSCs), tissue NSC consumption over-winter, and recovery after drought release in oak (Quercus petraea) and beech (Fagus sylvatica) saplings. Long drought duration (>1 month) decreased leaf water potential, photosynthesis, and NSC concentrations in both oak and beech saplings. Nitrogen fertilization did not mitigate the negative drought effects on both species. The photosynthesis and relative height increment recovered in the following rewetting year. Height growth in the rewetting year was significantly positively correlated with both pre- and post-winter root NSC levels. Root carbon reserve is critical for tree growth and survival under long-lasting drought. Our results indicate that beech is more sensitive to drought and fertilization than oak. The present study, in a physiological perspective, experimentally confirmed the view that the European beech, compared to oak, may be more strongly affected by future environmental changes.

In situ 13CO2 labeling reveals that alpine treeline trees allocate less photoassimilates to roots compared with low-elevation trees.

Carbon (C) allocation plays a crucial role for survival and growth of alpine treeline trees, however it is still poorly understood. Using in situ 13CO2 labeling, we investigated the leaf photosynthesis and the allocation of 13C labeled photoassimilates in various tissues (leaves, twigs and fine roots) in treeline trees and low-elevation trees. Non-structural carbohydrate concentrations were also determined. The alpine treeline trees (2000 m. a.s.l.), compared with low-elevation trees (1700 m a.s.l.), did not show any disadvantage in photosynthesis, but the former allocated proportionally less newly assimilated C belowground than the latter. Carbon residence time in leaves was longer in treeline trees (19 days) than that in low-elevation ones (10 days). We found an overall lower density of newly assimilated C in treeline trees. The alpine treeline trees may have a photosynthetic compensatory mechanism to counteract the negative effects of the harsh treeline environment (e.g., lower temperature and shorter growing season) on C gain. Lower temperature at treeline may limit the sink activity and C downward transport via phloem, and shorter treeline growing season may result in early cessation of root growth, decreases sink strength, which all together lead to lower density of new C in the sink tissues and finally limit the growth of the alpine treeline trees.

Effects of winter chilling vs. spring forcing on the spring phenology of trees in a cold region and a warmer reference region.

Regions at high latitudes and high altitudes are undergoing a more pronounced winter warming than spring warming, and such asymmetric warming will affect chilling and forcing processes and thus the spring phenology of plants. We analyzed winter chilling and spring forcing accumulation in relation to the spring phenology of three tree species (Ulmus pumila, Populus simonii, and Syringa oblata) growing in a cold region (CR) compared with trees in a warmer reference region (WR), using the Dynamic Model and the Growing Degree Hour (GDH) model. We tested that forcing rather than chilling affects the spring phenology of trees in CR (hypothesis I), and that trees in CR have both lower mean chilling and forcing temperature and thus longer accumulation periods than trees in WR (hypothesis II). The modeling results confirmed that chilling and forcing occur simultaneously during the early spring when temperature gradually increases. In line with our hypotheses, forcing played a crucial role in spring phenology in CR, but chilling and forcing combined to determine spring phenology in WR. The temperature during the chilling and forcing periods was lower and the accumulation period started earlier and ended later in CR than in WR. Moreover, the chilling accumulation was broken into two periods by the low deep winter temperature in CR, and that interruption will be removed by future strong winter warming. Future asymmetric warming, with a stronger temperature increase in winter than in spring, could decrease the forcing accumulation effects and increase the chilling effects on the spring phenology of plants in CR. This change in the balance between chilling and forcing will lead to a shift in plant phenology, which will further have major impacts on biogeochemical cycles and on ecosystem functions and services.

Estimating burn severity and carbon emissions from a historic megafire in boreal forests of China.

Wildfires, especially those of large size, worsen air quality and alter the carbon cycle through combustion of large quantities of biomass and release of carbon into the atmosphere. The Black Dragon fire, which occurred in 1987 in the boreal forests of China is among the top five of such megafires ever recorded in the world. With over 30 years of accumulation of data and availability of new greenhouse gas emission accounting methods, carbon emissions from this megafire can now be estimated with improved precision and greater spatial resolution. To do this, we combined field and remote sensing data to map four burn severity classes and calculated combustion efficiency in terms of the biomass immediately consumed in the fire. Results of the study showed that 1.30 million hectares burned and 52% of that area burned with high severity. The emitted carbon dioxide equivalents (CO2e), accounted for approximately 10% of total fossil fuel emissions from China in 1987, along with CO (2%-3% of annual anthropogenic CO emissions from China) and non-methane hydrocarbons (NMHC) contributing to the atmospheric pollutants. Our study provides an important basis for carbon emission estimation and understanding the impacts of megafires.

Patterns and drivers of recent disturbances across the temperate forest biome.

Increasing evidence indicates that forest disturbances are changing in response to global change, yet local variability in disturbance remains high. We quantified this considerable variability and analyzed whether recent disturbance episodes around the globe were consistently driven by climate, and if human influence modulates patterns of forest disturbance. We combined remote sensing data on recent (2001-2014) disturbances with in-depth local information for 50 protected landscapes and their surroundings across the temperate biome. Disturbance patterns are highly variable, and shaped by variation in disturbance agents and traits of prevailing tree species. However, high disturbance activity is consistently linked to warmer and drier than average conditions across the globe. Disturbances in protected areas are smaller and more complex in shape compared to their surroundings affected by human land use. This signal disappears in areas with high recent natural disturbance activity, underlining the potential of climate-mediated disturbance to transform forest landscapes.

Distribution and Driving Factors of Forest Swamp Conversions in a Cold Temperate Region.

Forest swamps are widely distributed in cold temperate regions, with important landscape and ecological functions. They are prone to conversion caused by complex factors. Forest swamp conversions involve forest swamping, meadow swamping, water body swamping, and conversion to farmland. An understanding of the landscape characteristics and primary environmental factors driving forest swamp conversions is imperative for exploring the mechanism of forest swamp conversions. We investigated the landscape characteristics of forest swamp conversions and quantified the relative importance of environmental factors driving these conversions for the period from 1990 to 2015 in the Great Xing'an Mountains of China. We found that forest swamping displayed high patch numbers (34,916) and density (8.51/100 ha), commonly occurring at the edge of large areas of forests. Meadow swamping was localized with low patch numbers (3613) and density (0.88/100 ha) due to lack of water recharge from ground water. Water body swamping had complex shapes (perimeter area ratio mean = 348.32) because of water table fluctuations and helophyte growth during this conversion process. Conversions to farmland presented fairly regular (perimeter area ratio mean = 289.91) and aggregated (aggregation index = 67.82) characteristics affected by agricultural irrigation and management. We found that climatic and geomorphic factors were relatively important compared to topographic factors for forest swamp conversions. Negative geomorphic conditions provided the waterlogging environment as a precondition of swamp formation. Sufficient precipitation was an important source of water recharge due to the existence of permafrost regions and long-term low temperature reduced the evaporation of swamps water and the decomposition rate of organisms. These wet and cold climatic conditions promoted forest swamp development in cold temperate regions. Humans exerted a relatively important role in forest swamping and conversions to farmland. Fire disturbance and logging accelerated the conversion from forest to swamp. This study provides scientific information necessary for the management and conservation of forest swamp resources in cold temperate regions.

Effects of species biological traits and environmental heterogeneity on simulated tree species distribution shifts under climate change.

Demographic processes (fecundity, dispersal, colonization, growth, and mortality) and their interactions with environmental changes are not well represented in current climate-distribution models (e.g., niche and biophysical process models) and constitute a large uncertainty in projections of future tree species distribution shifts. We investigate how species biological traits and environmental heterogeneity affect species distribution shifts. We used a species-specific, spatially explicit forest dynamic model LANDIS PRO, which incorporates site-scale tree species demography and competition, landscape-scale dispersal and disturbances, and regional-scale abiotic controls, to simulate the distribution shifts of four representative tree species with distinct biological traits in the central hardwood forest region of United States. Our results suggested that biological traits (e.g., dispersal capacity, maturation age) were important for determining tree species distribution shifts. Environmental heterogeneity, on average, reduced shift rates by 8% compared to perfect environmental conditions. The average distribution shift rates ranged from 24 to 200myear-1 under climate change scenarios, implying that many tree species may not able to keep up with climate change because of limited dispersal capacity, long generation time, and environmental heterogeneity. We suggest that climate-distribution models should include species demographic processes (e.g., fecundity, dispersal, colonization), biological traits (e.g., dispersal capacity, maturation age), and environmental heterogeneity (e.g., habitat fragmentation) to improve future predictions of species distribution shifts in response to changing climates.

An integrated modeling approach for estimating hydrologic responses to future urbanization and climate changes in a mixed-use midwestern watershed.

Future urban development and climatic changes are likely to affect hydrologic regimes in many watersheds. Quantifying potential water regime changes caused by these stressors is therefore crucial for enabling decision makers to develop viable environmental management strategies. This study presents an approach that integrates mid-21st century impervious surface growth estimates derived from the Imperviousness Change Analysis Tool with downscaled climate model projections and a hydrologic model Soil and Water Assessment Tool to characterize potential water regime changes in a mixed-use watershed in central Missouri, USA. Results for the climate change only scenario showed annual streamflow and runoff decreases (-10.7% and -9.2%) and evapotranspiration increases (+6.8%), while results from the urbanization only scenario showed streamflow and runoff increases (+3.8% and +9.3%) and evapotranspiration decreases (-2.4%). Results for the combined impacts scenario suggested that climatic changes could have a larger impact than urbanization on annual streamflow, (overall decrease of -6.1%), and could largely negate surface runoff increases caused by urbanization. For the same scenario, climatic changes exerted a stronger influence on annual evapotranspiration than urbanization (+3.9%). Seasonal results indicated that the relative influences of urbanization and climatic changes vary seasonally. Climatic changes most greatly influenced streamflow and runoff during winter and summer, and evapotranspiration during summer. During some seasons the directional change for hydrologic processes matched for both stressors. This work presented a practicable approach for investigating the relative influences of mid-21st century urbanization and climatic changes on the hydrology of a representative mixed-use watershed, adding to a limited body of research on this topic. This was done using a transferrable approach that can be adapted for watersheds in other regions.

Warming-induced upward migration of the alpine treeline in the Changbai Mountains, northeast China.

Treeline responses to environmental changes describe an important phenomenon in global change research. Often conflicting results and generally too short observations are, however, still challenging our understanding of climate-induced treeline dynamics. Here, we use a state-of-the-art dendroecological approach to reconstruct long-term changes in the position of the alpine treeline in relation to air temperature at two sides in the Changbai Mountains in northeast China. Over the past 160 years, the treeline increased by around 80 m, a process that can be divided into three phases of different rates and drives. The first phase was mainly influenced by vegetation recovery after an eruption of the Tianchi volcano in 1702. The slowly upward shift in the second phase was consistent with the slowly increasing temperature. The last phase coincided with rapid warming since 1985, and shows with 33 m per 1°C, the most intense upward shift. The spatial distribution and age structure of trees beyond the current treeline confirm the latest, warming-induced upward shift. Our results suggest that the alpine treeline will continue to rise, and that the alpine tundra may disappear if temperatures will increase further. This study not only enhances mechanistic understanding of long-term treeline dynamics, but also highlights the effects of rising temperatures on high-elevation vegetation dynamics.

Future forest aboveground carbon dynamics in the central United States: the importance of forest demographic processes.

The Central Hardwood Forest (CHF) in the United States is currently a major carbon sink, there are uncertainties in how long the current carbon sink will persist and if the CHF will eventually become a carbon source. We used a multi-model ensemble to investigate aboveground carbon density of the CHF from 2010 to 2300 under current climate. Simulations were done using one representative model for each of the simple, intermediate, and complex demographic approaches (ED2, LANDIS PRO, and LINKAGES, respectively). All approaches agreed that the current carbon sink would persist at least to 2100. However, carbon dynamics after current carbon sink diminishes to zero differ for different demographic modelling approaches. Both the simple and the complex demographic approaches predicted prolonged periods of relatively stable carbon densities after 2100, with minor declines, until the end of simulations in 2300. In contrast, the intermediate demographic approach predicted the CHF would become a carbon source between 2110 and 2260, followed by another carbon sink period. The disagreement between these patterns can be partly explained by differences in the capacity of models to simulate gross growth (both birth and subsequent growth) and mortality of short-lived, relatively shade-intolerant tree species.

Defining fire environment zones in the boreal forests of northeastern China.

Fire activity in boreal forests will substantially increase with prolonged growing seasons under a warming climate. This trend poses challenges to managing fires in boreal forest landscapes. A fire environment zone map offers a basis for evaluating these fire-related problems and designing more effective fire management plans to improve the allocation of management resources across a landscape. Toward that goal, we identified three fire environment zones across boreal forest landscapes in northeastern China using analytical methods to identify spatial clustering of the environmental variables of climate, vegetation, topography, and human activity. The three fire environment zones were found to be in strong agreement with the spatial distributions of the historical fire data (occurrence, size, and frequency) for 1966-2005. This paper discusses how the resulting fire environment zone map can be used to guide forest fire management and fire regime prediction.

Relative effects of climatic and local factors on fire occurrence in boreal forest landscapes of northeastern China.

Fire significantly affects species composition, structure, and ecosystem processes in boreal forests. Our study objective was to identify the relative effects of climate, vegetation, topography, and human activity on fire occurrence in Chinese boreal forest landscapes. We used historical fire ignition for 1966-2005 and the statistical method of Kernel Density Estimation to derive fire-occurrence density (number of fires/km(2)). The Random Forest models were used to quantify the relative effects of climate, vegetation, topography, and human activity on fire-occurrence density. Our results showed that fire-occurrence density tended to be spatially clustered. Human-caused fire occurrence was highly clustered at the southern part of the region, where human population density is high (comprising about 75% of the area's population). In the north-central areas where elevations are the highest in the region and less densely populated, lightning-caused fires were clustered. Climate factors (e.g., fine fuel and duff moisture content) were important at both regional and landscape scales. Human activity factors (e.g., distance to nearest settlement and road) were secondary to climate as the primary fire occurrence factors. Predictions of fire regimes often assume a strong linkage between climate and fire but usually with less emphasis placed on the effects of local factors such as human activity. We therefore suggest that accurate forecasting of fire regime should include human influences such as those measured by forest proximity to roads and human settlements.

Development of standard fuel models in boreal forests of Northeast China through calibration and validation.

Understanding the fire prediction capabilities of fuel models is vital to forest fire management. Various fuel models have been developed in the Great Xing'an Mountains in Northeast China. However, the performances of these fuel models have not been tested for historical occurrences of wildfires. Consequently, the applicability of these models requires further investigation. Thus, this paper aims to develop standard fuel models. Seven vegetation types were combined into three fuel models according to potential fire behaviors which were clustered using Euclidean distance algorithms. Fuel model parameter sensitivity was analyzed by the Morris screening method. Results showed that the fuel model parameters 1-hour time-lag loading, dead heat content, live heat content, 1-hour time-lag SAV(Surface Area-to-Volume), live shrub SAV, and fuel bed depth have high sensitivity. Two main sensitive fuel parameters: 1-hour time-lag loading and fuel bed depth, were determined as adjustment parameters because of their high spatio-temporal variability. The FARSITE model was then used to test the fire prediction capabilities of the combined fuel models (uncalibrated fuel models). FARSITE was shown to yield an unrealistic prediction of the historical fire. However, the calibrated fuel models significantly improved the capabilities of the fuel models to predict the actual fire with an accuracy of 89%. Validation results also showed that the model can estimate the actual fires with an accuracy exceeding 56% by using the calibrated fuel models. Therefore, these fuel models can be efficiently used to calculate fire behaviors, which can be helpful in forest fire management.