Vegetation Feedbacks Research Articles

Global assessment of climatic responses to ozone–vegetation interactions

Abstract. The coupling between surface ozone (O3) and vegetation significantly influences the regional to global climate. O3 uptake by plant stomata inhibits the photosynthetic rate and stomatal conductance, impacting evapotranspiration through land surface ecosystems. Using a climate–vegetation–chemistry coupled model (the NASA GISS ModelE2 coupled with the Yale Interactive terrestrial Biosphere, or ModelE2-YIBs), we assess the global climatic responses to O3–vegetation interactions during the boreal summer of the present day (2005–2014). High O3 pollution reduces stomatal conductance, resulting in warmer and drier conditions worldwide. The most significant responses are found in the eastern US and eastern China, where the surface air temperature increases by +0.33 ± 0.87 and +0.56 ± 0.38 °C, respectively. These temperature increases are accompanied by decreased latent heat and increased sensible heat in both regions. The O3–vegetation interaction also affects atmospheric pollutants. The surface maximum daily 8 h average O3 concentrations increase by +1.46 ± 3.02 ppbv in eastern China and +1.15 ± 1.77 ppbv in the eastern US due to the O3-induced inhibition of stomatal uptake. With reduced atmospheric stability following a warmer climate, increased cloud cover but decreased relative humidity jointly reduce aerosol optical depth by −0.06 ± 0.01 (−14.67 ± 12.15 %) over eastern China. This study suggests that vegetation feedback should be considered for a more accurate assessment of climatic perturbations caused by tropospheric O3.

Embedding a novel phenology model into the Common Land Model for improving the modeling of land-atmosphere fluxes

Land surface models (LSMs) are essential tools for simulating the energy and momentum exchange between the land surface and the atmosphere. The vegetation phenology module, a pivotal component of LSMs, reflects the feedback of vegetation to climate variations. However, the vegetation phenology module in several LSMs, such as the Common Land Model (CoLM), face challenges concerning its rationality. Currently, the original satellite phenology mode in CoLM, which uses satellite-based leaf area index (LAI) data directly and statically, constrains the model's ability to accurately represent complex and dynamic ecosystem processes. In this study, we embedded a dynamic vegetation phenology model into CoLM, serving as a novel phenology module. We conducted an extensive comparison of the effects of various phenology modules on CoLM, focusing on their performance in the modeling of gross primary productivity (GPP) and evapotranspiration (ET) at both site and global scales. Results demonstrate an improvement in CoLM for modeling GPP and ET following the integration of the novel phenology module. Specifically, the Pearson's correlation coefficient for GPP increased by 1.29 % to 33.74 %, and for ET by 0.32 % to 7.47 % on a site scale. Furthermore, on a global scale, when compared with global reference datasets, the CoLM embedded with the novel phenology module successfully captures the spatiotemporal distribution of GPP and ET, and its performance is closer to the reference data than that of the CoLM with the original satellite phenology mode. This study highlights the importance of vegetation phenology in LSMs and its potential to improve the modeling of dynamic interactions between vegetation processes and environmental changes within LSMs.

Mid-Holocene West African monsoon rainfall enhanced in EC-Earth simulation with dynamic vegetation feedback

Proxy records have shown that the Mid-Holocene was a period of humid conditions across West Africa, with an enhanced West African Monsoon (WAM) and vegetated conditions in areas currently characterized by desert, often referred to as the Green Sahara. However, General Circulation Models regularly struggle with recreating this strengthened Mid-Holocene monsoon in West Africa. Vegetation feedbacks has long been viewed as an essential process modulating the monsoon variability in West Africa, and simulations using prescribed vegetation to recreate a Green Sahara have shown a strengthened WAM and increased rainfall. However, simulations with prescribed vegetation in Sahara represent an idealized vegetation cover and do not take any environmental heterogeneity into account. Furthermore, this only represents a one-directional forcing by the vegetation on the climate rather than the full vegetation feedback. To address this, we have simulated the Mid-Holocene (~ 6 ka) climate using the Earth System Model EC-Earth3-Veg. The results show that coupled dynamic vegetation reproduces an apparent enhancement of the WAM, with the summer rainfall in the Sahel region increasing by 15% compared to simulations with a prescribed modern vegetation cover. Vegetation feedbacks enhance the warming of the Sahara region, deepens the Sahara Heat Low, results in increased rainfall and strengthens monsoonal flow across West Africa. However, the enhancement is still below what can be viewed in proxy reconstructions, highlighting the role of model limitation and biases and the importance of investigating other processes, such as the interactive aerosol-albedo feedback.

Asian monsoon variations over the past 21 ka: An introduction

The Asian monsoon influences the lives of more than a third of the world's population, and understanding its spatial and temporal variability is fundamental to sustainable development. The complex dynamics of this climatic system are therefore of broad scientific and societal interest. In this virtual special issue (VSI), we present 19 papers dealing with the Asian monsoon since the Last Glacial Maximum (LGM, ∼21 kyr BP), with a focus on understanding variability and forcing mechanisms. Findings use recently developed quantitative reconstructions combined with numerical simulations, and present novel insights as follows: (1) analyses of comprehensive datasets of pollen, diatom, brGDGTs, oxygen and hydrogen isotopes and frequency magnetic susceptibility, as well as an innovative algorithm model for the lake energy-water balance, improve the reliability of quantitative reconstructions of Asian monsoon climate variations; (2) studies of quantitative climate parameters in central East Asia show that mean annual temperature (MAT) was ∼5 °C (or ∼ 7.9 °C using brGDGTs) lower during the LGM, ∼1.5 °C (±41% using brGDGTs) higher around the Holocene thermal optimum (HO) and mean annual precipitation (MAP) varied between 30 and 150% with marked seasonality during 8–5 ka; (3) dynamical downscaling palaeoclimatic simulations improve the accuracy of past monsoon variations, revealing strong variability in monsoon precipitation across the LGM and HO. The holistic study of Asian monsoon variations at orbital to centennial timescales in these VSI papers presents reliable observations of monsoon variability and its driving mechanisms, providing high-resolution quantitative paleoclimate reconstructions that fill existing gaps in spatial coverage, as well as offering an improved understanding, thorough numerical simulation, of coupled sea-level change and vegetation feedbacks.

Simulation of ozone–vegetation coupling and feedback in China using multiple ozone damage schemes

Abstract. As a phytotoxic pollutant, surface ozone (O3) not only affects plant physiology but also influences meteorological fields and air quality by altering leaf stomatal functions. Previous studies revealed strong feedbacks of O3–vegetation coupling in China but with large uncertainties due to the applications of varied O3 damage schemes and chemistry–vegetation models. In this study, we quantify the O3 vegetation damage and the consequent feedbacks to surface meteorology and air quality in China by coupling two O3 damage schemes (S2007 vs. L2013) into a fully coupled regional meteorology–chemistry model. With different schemes and damaging sensitivities, surface O3 is predicted to decrease summertime gross primary productivity by 5.5 %–21.4 % and transpiration by 5.4 %–23.2 % in China, in which the L2013 scheme yields 2.5–4 times of losses relative to the S2007 scheme. The damage to the photosynthesis of sunlit leaves is ∼ 2.6 times that of shaded leaves in the S2007 scheme but shows limited differences in the L2013 scheme. Though with large discrepancies in offline responses, the two schemes yield a similar magnitude of feedback to surface meteorology and O3 air quality. The O3-induced damage to transpiration increases national sensible heat by 3.2–6.0 W m−2 (8.9 % to 16.2 %), while reducing latent heat by 3.3–6.4 W m−2 (−5.6 % to −17.4 %), leading to a 0.2–0.51 °C increase in surface air temperature and a 2.2 %–3.9 % reduction in relative humidity. Meanwhile, surface O3 concentrations on average increase by 2.6–4.4 µg m−3, due to the inhibitions of stomatal uptake and the anomalous enhancement in isoprene emissions, the latter of which is attributed to the surface warming by O3–vegetation coupling. Our results highlight the importance of O3 control in China due to its adverse effects on ecosystem functions, global warming, and O3 pollution through O3–vegetation coupling.

The role of dispersal limitation in the forest biome shifts of Europe in the last 18,000 years

AbstractAimHow the ability of plants to move towards newly favourable habitats (dispersal limitation) impacts the change of biome distribution and transition under fast climate warming is still debated. Analysing vegetation change in the past may help to clarify the relative importance of underlying ecological processes such as climate, biotic interactions, and dispersal. In this study, we investigated how dispersal limitation affected the distribution of European forests in the last 18,000 years.LocationSouthern and Central Europe.TaxonSpermatophyta.MethodsUsing the LPJ‐GM 2.0 model (an extension of LPJ‐GUESS), we simulated European vegetation from the end of the Last Glacial Maximum (18.5 ka) to the current time (0 ka). Using biome reconstructions from pollen data as reference, we compared the performance of two dispersal modes: with no migration constraints or seed limitation (free dispersal mode), and with plant establishment depending on seed dynamics and dispersal (dispersal limitation mode).ResultsThe model run, including migration processes, was better at capturing the post‐glacial expansion of European temperate forests (and the longer persistence of boreal forests) than the setting assuming free dispersal, especially during periods of rapid warming. This suggests that a number of (temperate) tree taxa experienced delayed occupancy of climatically suitable habitats due to a limited dispersal capacity, i.e., post‐glacial migration lags.Main ConclusionsOur results show that including migration processes in model simulations allows for more realistic reconstructions of forest patterns under rapid climate change, with consequences for future projections of carbon sequestration and climate reconstructions with vegetation feedback, assisted migration and forest conservation.

Glacial inception through rapid ice area increase driven by albedo and vegetation feedbacks

Abstract. We present transient simulations of the last glacial inception using the Earth system model CLIMBER-X with dynamic vegetation, interactive ice sheets, and visco-elastic solid Earth responses. The simulations are initialized at the middle of the Eemian interglacial (125 kiloyears before present, ka) and run until 100 ka, driven by prescribed changes in Earth's orbital parameters and greenhouse gas concentrations from ice core data. CLIMBER-X simulates a rapid increase in Northern Hemisphere ice sheet area through MIS5d, with ice sheets expanding over northern North America and Scandinavia, in broad agreement with proxy reconstructions. While most of the increase in ice sheet area occurs over a relatively short period between 119 and 117 ka, the larger part of the increase in ice volume occurs afterwards with an almost constant ice sheet extent. We show that the vegetation feedback plays a fundamental role in controlling the ice sheet expansion during the last glacial inception. In particular, with prescribed present-day vegetation the model simulates a global sea level drop of only ∼ 20 m, compared with the ∼ 35 m decrease in sea level with dynamic vegetation response. The ice sheet and carbon cycle feedbacks play only a minor role during the ice sheet expansion phase prior to ∼ 115 ka but are important in limiting the deglaciation during the following phase characterized by increasing summer insolation. The model results are sensitive to climate model biases and to the parameterization of snow albedo, while they show only a weak dependence on changes in the ice sheet model resolution and the acceleration factor used to speed up the climate component. Overall, our simulations confirm and refine previous results showing that climate–vegetation–cryosphere feedbacks play a fundamental role in the transition from interglacial to glacial states characterizing Quaternary glacial cycles.

Will large-scale forestation lead to a soil water deficit crisis in China's drylands?

Trading water for carbon has cautioned large-scale afforestation in global drylands. However, model simulations suggested that the consumption of soil water could be partially offset by increasing precipitation due to vegetation feedback. A systematic meta-analysis of long-term and large-scale field observations is urgently required to address the abovementioned limitations, and the implementation of large-scale afforestation since 1978 in northern China provides an ideal example. This study collected data comprising 1226 observations from 98 sites in northern China to assess the variation in soil water content (SWC) with stand age after afforestation and discuss the effects of tree species, precipitation and conversions of land use types on SWC. We found that the SWC has been decreased by coniferous forest and broadleaf forest at rates of 0.6 and 3.2 mm decade–1, respectively, since 1978. There is a significant declining trend of SWC with the stand age of plantations, and the optimum growth stage for plantation forest is 0–20 a in northern China. However, we found increases in SWC for the conversion from grassland to forest and in the low-precipitation region, both are corresponding to the increased SWC in coniferous forest. Our study implies that afforestation might lead to a soil water deficit crisis in northern China in the long term at the regional scale but depends on prior land use types, tree taxa and the mean annual precipitation regime, which sheds light on decision-making regarding ecological restoration policies and water resource management in drylands.

Impacts of Mid‐Pliocene Ice Sheets and Vegetation on Afro‐Asian Summer Monsoon Rainfall Revealed by EC‐Earth Simulations

AbstractThe impact of mid‐Pliocene boundary conditions on Afro‐Asian summer monsoon (AfroASM) rainfall is examined using the fully coupled Earth System Model EC‐Earth3‐LR. Our focus lies on the effects of varying CO2 concentration, diminished ice sheets and vegetation dynamics. We find that the enhanced AfroASM rainfall is predominantly caused by the “warmer‐gets‐wetter” mechanism due to elevated CO2 levels. Additionally, the ice sheet, similar in size to that of the mid‐Pliocene era, creates several indirect effects. These include sea ice‐albedo feedback and inter‐hemispheric atmosphere energy transport. Such influences result in the southward shift of Hadley circulation and formation of Pacific‐Japan pattern, leading to reduced rainfall in North African and South Asian monsoon regions but increased rainfall in East Asian monsoon region. Interestingly, while dynamic vegetation feedback has a minimal direct effect on AfroASM rainfall, it significantly influences rainfall in the mid‐high latitudes of the North Hemisphere by enhancing water vapor feedback.

Modeling and evaluating the effects of irrigation on land–atmosphere interaction in southwestern Europe with the regional climate model REMO2020–iMOVE using a newly developed parameterization

Abstract. Irrigation is a crucial land use practice to adapt agriculture to unsuitable climate and soil conditions. Aiming to improve the growth of plants, irrigation modifies the soil condition, which causes atmospheric effects and feedbacks through land–atmosphere interaction. These effects can be quantified with numerical climate models, as has been done in various studies. It could be shown that irrigation effects, such as air temperature reduction and humidity increase, are well understood and should not be neglected on local and regional scales. However, there is a lack of studies including the role of vegetation in the altered land–atmosphere interaction. With the increasing resolution of numerical climate models, these detailed processes have a chance to be better resolved and studied. This study aims to analyze the effects of irrigation on land–atmosphere interaction, including the effects and feedbacks of vegetation. We developed a new parameterization for irrigation, implemented it into the REgional climate MOdel (REMO2020), and coupled it with the interactive MOsaic-based VEgetation module (iMOVE). Following this new approach of a separate irrigated fraction, the parameterization is suitable as a subgrid parameterization for high-resolution studies and resolves irrigation effects on land, atmosphere, and vegetation. Further, the parameterization is designed with three different water application schemes in order to analyze different parameterization approaches and their influence on the representation of irrigation effects. We apply the irrigation parameterization for southwestern Europe including the Mediterranean region at a 0.11∘ horizontal resolution for hot extremes. The simulation results are evaluated in terms of the consistency of physical processes. We found direct effects of irrigation, like a changed surface energy balance with increased latent and decreased sensible heat fluxes, and a surface temperature reduction of more than −4 K as a mean during the growing season. Further, vegetation reacts to irrigation with direct effects, such as reduced water stress, but also with feedbacks, such as a delayed growing season caused by the reduction of the near-surface temperature. Furthermore, the results were compared to observational data, showing a significant bias reduction in the 2 m mean temperature when using the irrigation parameterization.

High-resolution quantitative vegetation reconstruction in the North China Plain during the early-to-middle Holocene using the REVEALS model

Understanding the process and pattern of vegetation succession during the early-to-middle Holocene can yield valuable information for better predicting future vegetation evolution. In this study, we investigated the humidity evolution pattern in the North China Plain (NCP) during the early-to-middle Holocene by employing principal component analysis on 93 fossil spectra. Furthermore, by integrating the Regional Estimates of Vegetation Abundance from Large Sites (REVEALS) model, we quantitatively reconstructed the process of vegetation succession and discussed vegetation response to climate change events. Our results indicate that the sample scores of the first principal component axis (PCA axis 1) exhibited a consistent negative bias, implying a gradual rise in regional humidity. The quantitatively reconstructed tree coverage was found to be lower than the uncorrected pollen proportions, while the coverage of herb plants showed a significant increase compared to their respective pollen percentages. In the early and middle Holocene, the vegetation of the NCP succeeded from meadow steppe (10,000 ∼ 8,100 cal yr B.P.) to meadow steppe with pine woodland patches (8,100 ∼ 7,100 cal yr B.P.), then to pine forest (7,100 ∼ 5,300 cal yr B.P.). The quantitatively reconstructed vegetation exhibited the most pronounced response to 8.2 ka climate event, with Asteraceae emerging as the dominant taxa. Furthermore, we conducted a comprehensive analysis of the impact of the 8.2 ka climate event on vegetation in northern China, identifying four distinct types of vegetation feedback: (1) negligible alterations in vegetation, (2) expansion of steppe or desert steppe, (3) proliferation of temperate tree species, and (4) augmentation of meadow steppe.

Possible impacts of vegetation cover increment on the relationship between winter snow cover anomalies over the Third Pole and summer precipitation in East Asia

Snow cover over the Tibetan Plateau (TP)–the Third Pole of the earth has been recognized as a reliable signal of summer floods or droughts in East Asia (EA). The distribution of snow cover can be influenced by vegetation, however, the impacts of changes in cover of non-growing season vegetation–withered grass stem over TP on the climatic effects of snow cover remains poorly understood. Here, we showed that the relationship between TP winter snow cover (TPWSC) and EA summer precipitation (EASP) strengthened starting in the early 1990s but weakened after the early 2000s. The weakening of the TPWSC–EASP relationship was linked to the effects of vegetation cover increment (VCI) on winter and spring snow cover over the TP. A possible mechanism behind this linkage is that VCI leads to a shortened persistence of TPWSC anomalies and weakened surface diabatic heating anomalies in spring. Consequently, the influences of TP thermal forcing on the downstream atmospheric circulation in summer were altered, resulting in a different pattern of EASP anomalies. These findings highlight the importance of snow—vegetation feedback and its potential to alter the effectiveness of snow cover in seasonal climate prediction.

Feedback and contribution of vegetation, air temperature and precipitation to land surface temperature in the Yangtze River Basin considering statistical analysis

ABSTRACT Land surface temperature (LST), especially day-night LST difference , is a key variable for the stability of terrestrial ecosystems, affected by vegetation and climate change. Quantifying the contribution and feedback of vegetation and climate to LST changes is critical to developing mitigation strategies. Based on LST, Normalized vegetation index (NDVI), land use (LU), air temperature (AT) and precipitation (Pre) from 2003 to 2021, partial correlation was used to analyze the response of LST to vegetation and climate. The feedback and contribution of both to LST were further quantified by using spatial linear relationships and partial derivatives analysis. The results showed that both interannual LST and responded negatively to vegetation, and vegetation had a negative feedback effect in areas with significantly altered. Vegetation was also a major contributor to the decline of With the advantage of positive partial correlation area of 94.99%, AT became the main driving factor and contributor to change trend. Pre contributed negatively to both and , with contributions of −0.004 °C/y and −0.022 °C/y, respectively. AT played a decisive role in LST warming of YRB, which was partially mitigated by vegetation and Pre. The present research contributed to the detection of LST changes and improved understanding of the driving mechanism.

Annual and Seasonal Trends of Vegetation Responses and Feedback to Temperature on the Tibetan Plateau since the 1980s

The vegetation–temperature relationship is crucial in understanding land–atmosphere interactions on the Tibetan Plateau. Although many studies have investigated the connections between vegetation and climate variables in this region using remote sensing technology, there remain notable gaps in our understanding of vegetation–temperature interactions over different timescales. Here, we combined site-level air temperature observations, information from the global inventory modeling and mapping studies (GIMMS) dataset, and moderate-resolution imaging spectroradiometer (MODIS) products to analyze the spatial and temporal patterns of air temperature, vegetation, and land surface temperature (LST) on the Tibetan Plateau at annual and seasonal scales. We achieved these spatiotemporal patterns by using Sen’s slope, sequential Mann–Kendall tests, and partial correlation analysis. The timescale differences of vegetation-induced LST were subsequently discussed. Our results demonstrate that a breakpoint of air temperature change occurred on the Tibetan Plateau during 1994–1998, dividing the study period (1982–2013) into two phases. A more significant greening response of NDVI occurred in the spring and autumn with earlier breakpoints and a more sensitive NDVI response occurred in recent warming phase. Both MODIS and GIMMS data showed a common increase in the normalized difference vegetation index (NDVI) on the Tibetan Plateau for all timescales, while the former had a larger greening area since 2000. The most prominent trends in NDVI and LST were identified in spring and autumn, respectively, and the largest areas of significant variation in NDVI and LST mostly occurred in winter and autumn, respectively. The partial correlation analysis revealed a significant negative impact of NDVI on LST during the annual scale and autumn, and it had a significant positive impact during spring. Our findings improve the general understanding of vegetation–climate relationships at annual and seasonal scales.

Quantifying the Impact of Land Use and Land Cover Change on Moisture Recycling With Convection‐Permitting WRF‐Tagging Modeling in the Agro‐Pastoral Ecotone of Northern China

AbstractLand use and land cover change (LUCC) can influence the regional atmospheric water budget. In this study, the Weather Research and Forecasting model embedded with evapotranspiration (ET)‐tagging (WRF‐tagging) is used to investigate the atmospheric pathways of ET as well as where and to what extent ET returns as precipitation (P) in the agro‐pastoral ecotone of northern China (APENC). First, we updated the default land use and vegetation indices in the WRF‐tagging with high‐resolution and real‐time datasets. WRF‐tagging modeling reproduces the spatial distribution of P and ET reasonably after updating surface characteristics. Second, we analyzed and quantified the contribution of ET to atmospheric moisture and regional P in the APENC. The water vapor originating as ET is advected in the atmosphere below 600 hPa to hundreds of kilometers by the prevailing winds. Moisture recycling shows that 5.83% of P comes from local ET during the growing season in the core region of the APENC. Furthermore, to quantify the impact of LUCC on moisture recycling, we designed two different vegetation scenarios (Afforestation and Degradation) by changing land use and vegetation indices in the model. Results show that the precipitation recycling ratio increased to 6.31% in the Afforestation scenario, and decreased to 5.19% in the Degradation scenario, demonstrating the non‐neglectable positive feedback of vegetation on P. An analysis of land surface‐precipitation feedback processes indicates that the LUCC‐induced change in precipitation efficiency dominates P changes. Our findings highlight the importance of LUCC on local and regional moisture recycling in the APENC.

Burning trees in frozen soil: Simulating fire, vegetation, soil, and hydrology in the boreal forests of Alaska

Boreal ecosystems account for 29% of the world's total forested area and contain more carbon than any other terrestrial biome. Over the past 60 years, Alaska has warmed twice as rapidly as the contiguous U.S. and wildfire activity has increased, including the number of fires, area burned, and frequency of large wildfire seasons. These recent and rapid changes in climate and wildfire have implications for future vegetation composition, structure, and biomass in interior Alaska, given that the vegetation is highly dependent on active layer thickness, soil moisture, organic layer depth, and plant-available nutrients. Here we developed a new succession extension (DGS) of the LANDIS-II forest landscape model which integrates a vegetation dynamics model (NECN) with a soil carbon model (DAMM-McNiP), a hydrologic model (SHAW), and a deep soil profile permafrost model (GIPL) in a spatially-explicit framework. DGS Succession uses the algorithms in the NECN Succession extension of LANDIS-II to simulate growth, mortality and reproduction of vegetation but has three major improvements. First, the simple bucket model in NECN was replaced with a physically-based model (SHAW) that simulates energy and water fluxes (e.g. snow depth, evapotranspiration, soil moisture) at multiple levels in the canopy and soil. Second, the active, slow, and passive soil pools in NECN were replaced by seven soil pools that are measurable in the field, with carbon and nitrogen dynamics dictated by DAMM-McNiP. Finally, soil temperature and soil moisture are simulated only at one depth in NECN, but in DGS, soil temperature (and hence permafrost dynamics) are simulated at as many as 50 user-defined depths down to 4 m with SHAW and 75 m with GIPL. During the initial calibration phase, DGS was applied at three inventory sites at the Bonanza Creek Long Term Ecological Research area in Interior Alaska where climate forcings, species biomass, soil temperature, and/or soil moisture were available. For the landscape-scale simulations, DGS was run with the SCRPPLE fire extension of LANDIS-II under two scenarios of climate using a ∼400,000 ha landscape that included the inventory sites. Across all three sites, DGS generally captured the variation in soil moisture and temperature across depths, seasons, and years reasonably well, though there were some discrepancies at each site. DGS had better agreement with field measurements of soil moisture and temperature than its predecessor NECN which produced unrealistically low soil moisture and unrealistically high seasonal fluctuations in soil temperature. At the landscape scale, ignitions, area burned, and soil temperature increased under climate change, as expected, while soil moisture was relatively unchanged across climate scenarios. Biomass tended to decline under climate change, which differs from other modeling studies in this region but is consistent with the browning trends observed from remote sensing data. Simulating climate, vegetation succession, hydrology, permafrost, carbon and nutrient cycling, and wildfire in an integrated, spatially-explicit framework like LANDIS-II will allow us to disentangle the drivers and ecosystem responses in this rapidly changing ecosystem, as well as other forested systems with complex hydrologic, biochemical, cryospheric, and vegetation feedbacks.

Dynamic relationships between gross primary production and energy partitioning in three different ecosystems based on eddy covariance time series analysis

Ecosystems are responsible for strong feedback processes that affect climate. The mechanisms and consequences of this feedback are uncertain and must be studied to evaluate their influence on global climate change. The main objective of this study is to assess the gross primary production (GPP) dynamics and the energy partitioning patterns in three different European forest ecosystems through time series analysis. The forest types are an Evergreen Needleleaf Forest in Finland (ENF_FI), a Deciduous Broadleaf Forest in Denmark (DBF_DK), and a Mediterranean Savanna Forest in Spain (SAV_SP). Buys-Ballot tables were used to study the intra-annual variability of meteorological data, energy fluxes, and GPP, whereas the autocorrelation function was used to assess the inter-annual dynamics. Finally, the causality of GPP and energy fluxes was studied with Granger causality tests. The autocorrelation function of the GPP, meteorological variables, and energy fluxes revealed that the Mediterranean ecosystem is more irregular and shows lower memory in the long term than in the short term. On the other hand, the Granger causality tests showed that the vegetation feedback to the atmosphere was more noticeable in the ENF_FI and the DBF_DK in the short term, influencing latent and sensible heat fluxes. In conclusion, the impact of the vegetation on the atmosphere influences the energy partitioning in a different way depending on the vegetation type, which makes the study of the vegetation dynamics essential at the local scale to parameterize these processes with more detail and build improved global models.

Modeling Historical and Future Forest Fires in South Korea: The FLAM Optimization Approach

Climate change-induced heat waves increase the global risk of forest fires, intensifying biomass burning and accelerating climate change in a vicious cycle. This presents a challenge to the response system in heavily forested South Korea, increasing the risk of more frequent and large-scale fire outbreaks. This study aims to optimize IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM)—a processed-based model integrating biophysical and human impacts—to South Korea for projecting the pattern and scale of future forest fires. The developments performed in this study include: (1) the optimization of probability algorithms in FLAM based on the national GIS data downscaled to 1 km2 with additional factors introduced for national specific modeling; (2) the improvement of soil moisture computation by adjusting the Fine Fuel Moisture Code (FFMC) to represent vegetation feedbacks by fitting soil moisture to daily remote sensing data; and (3) projection of future forest fire frequency and burned area. Our results show that optimization has considerably improved the modeling of seasonal patterns of forest fire frequency. Pearson’s correlation coefficient between monthly predictions and observations from national statistics over 2016–2022 was improved from 0.171 in the non-optimized to 0.893 in the optimized FLAM. These findings imply that FLAM’s main algorithms for interpreting biophysical and human impacts on forest fire at a global scale are only applicable to South Korea after the optimization of all modules, and climate change is the main driver of the recent increases in forest fires. Projections for forest fire were produced for four periods until 2100 based on the forest management plan, which included three management scenarios (current, ideal, and overprotection). Ideal management led to a reduction of 60–70% of both fire frequency and burned area compared to the overprotection scenario. This study should be followed by research for developing adaptation strategies corresponding to the projected risks of future forest fires.

Three‐Dimensional Differentiation of the Contribution of Climatic Factors to Vegetation Change in the Pan‐Tibetan Plateau

AbstractDue to the heterogeneous terrains and unique alpine climate environment, the three‐dimensional differentiation of climatic impacts on vegetation change and its possible mechanism in the Pan‐Tibetan Plateau (PTP) are complex and lack adequate research. Hence, we here quantify the three‐dimensional differentiation of the contribution of climatic factors to vegetation change using the analysis of variance (ANOVA) method. Results indicate that the overall PTP has been warmer and wetter but partially drier, with a remarkable fractional vegetation coverage (FVC) increase since 2000. Moreover, the total areas with FVC changes accounting for approximately 49.3% of PTP are significantly driven by climate factors. Precipitation and potential evaporation predominate the vegetation change at relatively high altitudes and latitudes, while temperature affects the vegetation change at relatively low latitudes and parts of low elevations. Meanwhile, relative humidity dominates the vegetation change at middle altitudes and latitudes. Furthermore, the hydrothermal conditions and climate change magnitudes modulate the three‐dimensional differentiation. On the one hand, the effects of heat conditions on FVC change overwhelm the moisture conditions in alpine areas or warm and wet regions, in sharp contrast with the dominant role of water conditions in most dry areas. On the other hand, the spatial heterogeneity in climate change magnitudes influences the contribution of climatic factors in most hydrothermal conditions. Additionally, interventions challenging to quantify, such as climatic and mountainous hazards, anthropogenic activities, and vegetation feedback, will lead to the differentiation’s uncertainties. Our research hopefully provides theoretical support for national ecosystem management and major construction projects across PTP.

Monitoring Land Degradation through Vegetation Dynamics Mathematical Modeling: Case of Jornada Basin (in the U.S.)

Arid ecosystems are known to be sensitive to climate change. The Jornada Basin in the USA, as one representative of arid land, has suffered from land degradation in recent decades. In order to disentangle the climate–vegetation feedback, we analyzed the vegetation dynamics under the effects of climate change via a mathematical model based on the reaction–diffusion mechanism. Using this model, we conducted a sensitive analysis of climate factors and concluded that the ecosystem might experience a catastrophic shift with the climatic deterioration. We considered the non-local interaction term to explain the competition among plants. Additionally, the PLR (power law range) metric was used to quantify the extent of the degradation and to compare the results of the vegetation patterns from the remote sensing data and the simulations. From the results, this model could simulate the trends of land degradation in this area. We found that the land degradation could be mainly attributed to climate changes in recent years. This approach suggests that vegetation patterns can provide hints as to whether the ecosystem is approaching desertification. These results can help with mapping vulnerable arid areas around the world through model simulation and satellite images.