Biophysical Effects of Temperate Forests in Regulating Regional Temperature and Precipitation Pattern across Northeast China

Jiao, Yue; Bu, Kun; Yang, Jiuchun; Li, Guangshuai; Shen, Lidu; Liu, Tingxiang; Yu, Lingxue; Zhang, Shuwen; Heng-qing, Zhang

doi:10.3390/rs13234767

Cited by 13 publications

(6 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The research area of this study is the Northeast China (NEC), which includes the Heilongjiang, Jilin, and Liaoning provinces, is located from 118 • 50 E to 135 • 09 E and 38 • 42 N to 53 • 35 N (Figure 1) [42]. NEC has the considerable climatic and topographical gradients, and the main topography of NEC is mountains and plains, with mountains in the east, west and north, and plains in the middle and south [43]. Due to geographical location NEC belongs to a temperate continental monsoon climate [44], which is divided into a warm temperate zone, temperate zone, and cold temperate zone from south to north and has obvious differences in humidity from east to west [45].…”

Section: Study Areamentioning

confidence: 99%

Spatiotemporal Variations of Forest Vegetation Phenology and Its Response to Climate Change in Northeast China

et al. 2022

View full text Add to dashboard Cite

Vegetation phenology is an important indicator of vegetation dynamics. The boreal forest ecosystem is the main part of terrestrial ecosystem in the Northern Hemisphere and plays an important role in global carbon balance. In this study, the dynamic threshold method combined with the ground-based phenology observation data was applied to extract the forest phenological parameters from MODIS NDVI time-series. Then, the spatiotemporal variation of forest phenology is discussed and the relationship between phenological change and climatic factors was concluded in the northeast China from 2011 to 2020. The results indicated that the distribution of the optimal extraction threshold has spatial heterogeneity, and the changing rate was 3% and 2% with 1° increase in latitude for SOS (the start of the growing season) and EOS (the end of the growing season). This research also notes that the SOS had an advanced trend at a rate of 0.29 d/a while the EOS was delayed by 0.47 d/a. This variation of phenology varied from different forest types. We also found that the preseason temperature played a major role in effecting the forest phenology. The temperature in winter of the previous year had a significant effect on SOS in current year. Temperature in autumn of the current year had a significant effect on EOS.

show abstract

Section: Study Areamentioning

confidence: 99%

Spatiotemporal Variations of Forest Vegetation Phenology and Its Response to Climate Change in Northeast China

et al. 2022

View full text Add to dashboard Cite

show abstract

“…This implies that the impact of vegetation on precipitation is greater than the response of vegetation to precipitation changes. The results of previous studies have confirmed that temperate forests in Northeast China have the ability to regulate the regional water cycle [53]. This is achieved through high evapotranspiration, where forests transfer a significant amount of water to the atmosphere.…”

Section: ) Causal Links Between Vegetation and Meteorological Factors...mentioning

confidence: 67%

Assessing the Causal Effects of Climate Change on Vegetation Dynamics in Northeast China Using Convergence Cross-Mapping

Wu,

Zhou,

Wang

et al. 2023

IEEE Access

View full text Add to dashboard Cite

The patterns of interaction between terrestrial vegetation and the atmosphere are complex, and some are poorly understood. Linear or general linear methods have been widely used to explore the dynamics of vegetation and climate changes. However, linear thinking may hinder our understanding of complex nonlinear systems, and it is difficult to extract the underlying causality of linear correlations directly from observational data. In this study, we aimed to quantify the interactions between vegetation and climate, using nonlinear dynamical methods based on state-space reconstruction and datasets from Chinese meteorological stations and remote sensing data during 1982-2015 in Northeast China (NEC). Specifically, we identified the causal links between meteorological factors (temperature and precipitation) and the vegetation index (NDVI) by reconstructing the state space from historical records. During the study period, vegetation exhibited a strong bidirectional causal relationship with both temperature and precipitation across Northeast China. The NDVI can be accurately reconstructed from the state information of meteorological factors (temperature and precipitation). The results of the multivariate EDM scenarios reveal varying sensitivities of different vegetation types to meteorological factors. Overall, slight temperature changes have a stronger impact on vegetation compared to precipitation. Mixed forest and broad-leaved forest demonstrate lower sensitivity to precipitation changes compared to other vegetation types. This study on the causal relationship between vegetation and meteorological factors in Northeast China contributes to a deeper understanding of climate change and vegetation feedback in middle and high latitudes. Our work demonstrates that the EDM-based convergent cross-mapping nonlinear causal analysis method is valuable for comprehending the interactions within complex systems in earth science.

show abstract

“…Further, forests change the Earth's surface albedo (Thompson et al 2009, Stephens et al 2015. Therefore, while forests in temperate and boreal regions generally warm the atmosphere during winter due to their low albedo, they predominantly cool it during the growing season, due to evapotranspiration (Chalita and Le Treut 1994, Ma et al 2017, Jiao et al 2021.…”

Section: General Introductionmentioning

confidence: 99%

Climate change-induced shifts in leaf phenology of trees: past and future trends

Meier

2024

Preprint

View full text Add to dashboard Cite

Forests and atmosphere interact, for example when trees assimilate and respire CO2 during photosynthesis. Depending on their productivity and net assimilation, forests may function as a carbon sink or source. Further, the amounts of synthesized sugars assigned to growth, reproduction, and defense affect the fitness of the trees and eventually the distribution of species. Climate strongly impacts such forest-atmosphere interactions, which affect forests and in turn feed back to the climate. For deciduous trees, the beginning and end of the photosynthetically active period (i.e., the ‘growing season’) relate to spring and autumn leaf phenology (i.e., leaf unfolding and leaf senescence), respectively. The climatic conditions during the growing season (i.e., the ‘bioclimate’) are directly and indirectly influenced by climate change, as climate change alters the timing and length of the growing season through shifts in leaf unfolding and leaf senescence. While past changes in leaf unfolding and leaf senescence can be analyzed by in-situ observations, the underlying drivers and particularly possible future changes are often studied with process-oriented models. However, these models may suffer from a bias towards the mean (BTM), which causes the simulated values to be closer to the average than the observations and could result in overly flat simulated trends. Here I discuss (1) changes in the growing season and bioclimate in Switzerland during recent decades, (2) impacts of the calibration approach on the performance of 21 leaf senescence models tested with observations from Central Europe, and (3) effects of the BTM in these models on their performance and projections. Growing seasons have predominately lengthened at elevation-specific rates, which was primarily caused by changes in leaf senescence and increased the number of days with a negative atmospheric water balance at low elevations. Calibrations with the Generalized Simulated Annealing algorithm and with systematically balanced or stratified samples yielded the best performing leaf senescence models, while their performance was most influenced by their structure. The BTM caused the performance of current leaf senescence models to be only slightly better than the performance of a null model that constantly simulates the average of the calibration sample. Standard model comparisons favored models with stronger BTM, while models with weaker BTM projected smaller backward shifts in future leaf senescence. The latter is counter-intuitive, since smaller shifts result from flatter trends and are therefore associated with stronger rather than weaker BTM. I conclude that (1) the effects of phenological changes on the bioclimate should be considered when studying past and future forest productivity and species composition, (2) inference from process-oriented models to the underlying processes and drivers of leaf senescence is valid, and (3) current leaf senescence projections are highly uncertain and thus unreliable. While it is likely that current projections of future biosphere behavior under global change are distorted by erroneous state-of-the-art leaf senescence models, there is ample need and potential for the development of more accurate process-oriented models.

show abstract

Biophysical Effects of Temperate Forests in Regulating Regional Temperature and Precipitation Pattern across Northeast China

Cited by 13 publications

References 40 publications

Spatiotemporal Variations of Forest Vegetation Phenology and Its Response to Climate Change in Northeast China

Spatiotemporal Variations of Forest Vegetation Phenology and Its Response to Climate Change in Northeast China

Assessing the Causal Effects of Climate Change on Vegetation Dynamics in Northeast China Using Convergence Cross-Mapping

Climate change-induced shifts in leaf phenology of trees: past and future trends

Contact Info

Product

Resources

About