scholarly journals Resolving temperature limitation on spring productivity in an evergreen conifer forest using a model-data fusion framework

2021 ◽  
Author(s):  
Stephanie G. Stettz ◽  
Nicholas C. Parazoo ◽  
A. Anthony Bloom ◽  
Peter D. Blanken ◽  
David R. Bowling ◽  
...  
Keyword(s):  
Climate Change ◽  
Data Fusion ◽  
Gross Primary Production ◽  
Growing Season ◽  
Cold Temperature ◽  
Evergreen Forest ◽  
Model Data ◽  
Environmental Controls ◽  
Climate Change Uncertainty ◽  
Temperature Limitation

Abstract. The flow of carbon through terrestrial ecosystems and the response to climate is a critical but highly uncertain process in the global carbon cycle. However, with a rapidly expanding array of in situ and satellite data, there is an opportunity to improve our mechanistic understanding of the carbon (C) cycle’s response to land use and climate change. Uncertainty in temperature limitation on productivity pose a significant challenge to predicting the response of ecosystem carbon fluxes to a changing climate. Here we diagnose and quantitatively resolve environmental limitations on growing season onset of gross primary production (GPP) using nearly two decades of meteorological and C flux data (2000–2018) at a subalpine evergreen forest in Colorado USA. We implement the CARDAMOM model-data fusion network to resolve the temperature sensitivity of spring GPP. To capture a GPP temperature limitation – a critical component of integrated sensitivity of GPP to temperature – we introduced a cold temperature scaling function in CARDAMOM to regulate photosynthetic productivity. We found that GPP was gradually inhibited at temperature below 6.0 °C (±2.6 °C) and completely inhibited below −7.1 °C (±1.1 °C). The addition of this scaling factor improved the model’s ability to replicate spring GPP at interannual and decadal time scales (r = 0.88), relative to the nominal CARDAMOM configuration (r = 0.47), and improved spring GPP model predictability outside of the data assimilation training period (r = 0.88) . While cold temperature limitation has an important influence on spring GPP, it does not have a significant impact on integrated growing season GPP, revealing that other environmental controls, such as precipitation, play a more important role in annual productivity. This study highlights growing season onset temperature as a key limiting factor for spring growth in winter-dormant evergreen forests, which is critical in understanding future responses to climate change.

scholarly journals Analyzing Daily Estimation of Forest Gross Primary Production Based on Harmonized Landsat-8 and Sentinel-2 Product Using SCOPE Process-Based Model

2020 ◽  
Vol 12 (22) ◽  
pp. 3773
Author(s):  
Rahul Raj ◽  
Bagher Bayat ◽  
Petr Lukeš ◽  
Ladislav Šigut ◽  
Lucie Homolová
Keyword(s):  
Time Series ◽  
Gross Primary Production ◽  
Growing Season ◽  
Temporal Variations ◽  
Forest Stand ◽  
Evergreen Forest ◽  
Landsat 8 ◽  
Data Set ◽  
Scope Model ◽  
Sentinel 2

Vegetation top-of-canopy reflectance contains valuable information for estimating vegetation biochemical and structural properties, and canopy photosynthesis (gross primary production (GPP)). Satellite images allow studying temporal variations in vegetation properties and photosynthesis. The National Aeronautics and Space Administration (NASA) has produced a harmonized Landsat-8 and Sentinel-2 (HLS) data set to improve temporal coverage. In this study, we aimed to explore the potential and investigate the information content of the HLS data set using the Soil Canopy Observation of Photosynthesis and Energy fluxes (SCOPE) model to retrieve the temporal variations in vegetation properties, followed by the GPP simulations during the 2016 growing season of an evergreen Norway spruce dominated forest stand. We optimized the optical radiative transfer routine of the SCOPE model to retrieve vegetation properties such as leaf area index and leaf chlorophyll, water, and dry matter contents. The results indicated percentage differences less than 30% between the retrieved and measured vegetation properties. Additionally, we compared the retrievals from HLS data with those from hyperspectral airborne data for the same site, showing that HLS data preserve a considerable amount of information about the vegetation properties. Time series of vegetation properties, retrieved from HLS data, served as the SCOPE inputs for the time series of GPP simulations. The SCOPE model reproduced the temporal cycle of local flux tower measurements of GPP, as indicated by the high Nash–Sutcliffe efficiency value (>0.5). However, GPP simulations did not significantly change when we ran the SCOPE model with constant vegetation properties during the growing season. This might be attributed to the low variability in the vegetation properties of the evergreen forest stand within a vegetation season. We further observed that the temporal variation in maximum carboxylation capacity had a pronounced effect on GPP simulations. We focused on an evergreen forest stand. Further studies should investigate the potential of HLS data across different forest types, such as deciduous stand.

Climate Change Uncertainty and the Classification of 226 Local Entities in Korea

2020 ◽  
Vol 11 (222) ◽  
pp. 507-520
Author(s):  
Jaewan Kim ◽  
Tae Yong Jung ◽  
Chan Park ◽  
Jongwoo Moon ◽  
Dahyun Kang
Keyword(s):  
Climate Change ◽  
Climate Change Uncertainty

scholarly journals Comparison of the Radial Growth Response of Picea crassifolia to Climate Change in Different Regions of the Central and Eastern Qilian Mountains

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1015
Author(s):  
Xuan Wu ◽  
Liang Jiao ◽  
Dashi Du ◽  
Changliang Qi ◽  
Ruhong Xue
Keyword(s):  
Climate Change ◽  
Tree Growth ◽  
Central Region ◽  
Radial Growth ◽  
Growing Season ◽  
Qilian Mountains ◽  
Growth Patterns ◽  
Total Precipitation ◽  
Picea Crassifolia ◽  
The Qilian Mountains

It is important to explore the responses of radial tree growth in different regions to understand growth patterns and to enhance forest management and protection with climate change. We constructed tree ring width chronologies of Picea crassifolia from different regions of the Qilian Mountains of northwest China. We used Pearson correlation and moving correlation to analyze the main climate factors limiting radial growth of trees and the temporal stability of the growth–climate relationship, while spatial correlation is the result of further testing the first two terms in space. The conclusions were as follows: (1) Radial growth had different trends, showing an increasing followed by a decreasing trend in the central region, a continuously increasing trend in the eastern region, and a gradually decreasing trend in the isolated mountain. (2) Radial tree growth in the central region and isolated mountains was constrained by drought stress, and tree growth in the central region was significantly negatively correlated with growing season temperature. Isolated mountains showed a significant negative correlation with mean minimum of growing season and a significant positive correlation with total precipitation. (3) Temporal dynamic responses of radial growth in the central region to the temperatures and SPEI (the standardized precipitation evapotranspiration index) in the growing season were unstable, the isolated mountains to total precipitation was unstable, and that to SPEI was stable. The results of this study suggest that scientific management and maintenance plans of the forest ecosystem should be developed according to the response and growth patterns of the Qinghai spruce to climate change in different regions of the Qilian Mountains.

scholarly journals Characterizing Growing Season Length of Subtropical Coniferous Forests with a Phenological Model

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 95
Author(s):  
Yuan Gong ◽  
Christina L. Staudhammer ◽  
Susanne Wiesner ◽  
Gregory Starr ◽  
Yinlong Zhang
Keyword(s):  
Climate Change ◽  
Soil Water ◽  
Prescribed Fire ◽  
Water Availability ◽  
Longleaf Pine ◽  
Growing Season ◽  
Soil Water Availability ◽  
Future Climate Change ◽  
Short Term ◽  
Phenological Model

Understanding plant phenological change is of great concern in the context of global climate change. Phenological models can aid in understanding and predicting growing season changes and can be parameterized with gross primary production (GPP) estimated using the eddy covariance (EC) technique. This study used nine years of EC-derived GPP data from three mature subtropical longleaf pine forests in the southeastern United States with differing soil water holding capacity in combination with site-specific micrometeorological data to parameterize a photosynthesis-based phenological model. We evaluated how weather conditions and prescribed fire led to variation in the ecosystem phenological processes. The results suggest that soil water availability had an effect on phenology, and greater soil water availability was associated with a longer growing season (LOS). We also observed that prescribed fire, a common forest management activity in the region, had a limited impact on phenological processes. Dormant season fire had no significant effect on phenological processes by site, but we observed differences in the start of the growing season (SOS) between fire and non-fire years. Fire delayed SOS by 10 d ± 5 d (SE), and this effect was greater with higher soil water availability, extending SOS by 18 d on average. Fire was also associated with increased sensitivity of spring phenology to radiation and air temperature. We found that interannual climate change and periodic weather anomalies (flood, short-term drought, and long-term drought), controlled annual ecosystem phenological processes more than prescribed fire. When water availability increased following short-term summer drought, the growing season was extended. With future climate change, subtropical areas of the Southeastern US are expected to experience more frequent short-term droughts, which could shorten the region’s growing season and lead to a reduction in the longleaf pine ecosystem’s carbon sequestration capacity.

scholarly journals The Water Needs of Grapevines in Central Poland

Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 416
Author(s):  
Barbara Jagosz ◽  
Stanisław Rolbiecki ◽  
Roman Rolbiecki ◽  
Ariel Łangowski ◽  
Hicran A. Sadan ◽  
...  
Keyword(s):  
Climate Change ◽  
Temporal Variability ◽  
Time Trend ◽  
Reference Evapotranspiration ◽  
Growing Season ◽  
Water Requirements ◽  
Climate Conditions ◽  
Central Poland ◽  
Crop Coefficients ◽  
Near Future

Climate warming increases the water needs of plants. The aim of this study was to estimate the water needs of grapevines in central Poland. Water needs were calculated using the crop coefficients method. Reference evapotranspiration was assessed by the Blaney–Criddle’s equation, modified for climate conditions in Poland. Crop coefficients were assumed according to the Doorenbos and Pruitt method. Water needs were calculated using the data from four meteorological stations. Rainfall deficit with the probability occurrence of normal years, medium dry years, and very dry years was determined by the Ostromęcki’s method. Water needs of grapevines during the average growing season were estimated at 438 mm. Upward time trend in the water needs both in the period of May–October and June–August was estimated. Temporal variability in the water needs was significant for all of the provinces. These changes were mainly impacted by a significant increasing tendency in mean air temperature and less by precipitation totals that did not show a clear changing tendency. Due to climate change, vineyards will require irrigation in the near future. The use of resource-efficient irrigation requires a precise estimate of the grapevines’ water needs. The study identified the water requirements for grapevines in central Poland.

scholarly journals Spatial and Temporal Differences in Alpine Meadow, Alpine Steppe and All Vegetation of the Qinghai-Tibetan Plateau and Their Responses to Climate Change

2021 ◽  
Vol 13 (4) ◽  
pp. 669
Author(s):  
Hanchen Duan ◽  
Xian Xue ◽  
Tao Wang ◽  
Wenping Kang ◽  
Jie Liao ◽  
...  
Keyword(s):  
Climate Change ◽  
Alpine Meadow ◽  
Global Climate ◽  
Growing Season ◽  
Tibet Plateau ◽  
Vegetation Types ◽  
Analysis Method ◽  
Alpine Steppe ◽  
Qinghai Tibet Plateau ◽  
Variation Trends

Alpine meadow and alpine steppe are the two most widely distributed nonzonal vegetation types in the Qinghai-Tibet Plateau. In the context of global climate change, the differences in spatial-temporal variation trends and their responses to climate change are discussed. It is of great significance to reveal the response of the Qinghai-Tibet Plateau to global climate change and the construction of ecological security barriers. This study takes alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau as the research objects. The normalized difference vegetation index (NDVI) data and meteorological data were used as the data sources between 2000 and 2018. By using the mean value method, threshold method, trend analysis method and correlation analysis method, the spatial and temporal variation trends in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau were compared and analyzed, and their differences in the responses to climate change were discussed. The results showed the following: (1) The growing season length of alpine meadow was 145~289 d, while that of alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau was 161~273 d, and their growing season lengths were significantly shorter than that of alpine meadow. (2) The annual variation trends of the growing season NDVI for the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau increased obviously, but their fluctuation range and change rate were significantly different. (3) The overall vegetation improvement in the Qinghai-Tibet Plateau was primarily dominated by alpine steppe and alpine meadow, while the degradation was primarily dominated by alpine meadow. (4) The responses between the growing season NDVI and climatic factors in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau had great spatial heterogeneity in the Qinghai-Tibet Plateau. These findings provide evidence towards understanding the characteristics of the different vegetation types in the Qinghai-Tibet Plateau and their spatial differences in response to climate change.

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