Plants

2024

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14 pages, 3976 KiB

Open AccessArticle

Generic and Specific Models for Volume Estimation in Forest and Savanna Phytophysiognomies in Brazilian Cerrado

by Yanara Ferreira de Souza, Eder Pereira Miguel, Adriano José Nogueira Lima, Álvaro Nogueira de Souza, Eraldo Aparecido Trondoli Matricardi, Alba Valéria Rezende, Joberto Veloso de Freitas, Hallefy Junio de Souza, Kennedy Nunes Oliveira, Maria de Fátima de Brito Lima and Leonardo Job Biali

Plants 2024, 13(19), 2769; https://doi.org/10.3390/plants13192769 - 3 Oct 2024

Viewed by 1067

Abstract

The Cerrado has high plant and vertebrate diversity and is an important biome for conserving species and provisioning ecosystem services. Volume equations in this biome are scarce because of their size and physiognomic diversity. This study was conducted to develop specific volumetric models [...] Read more.

The Cerrado has high plant and vertebrate diversity and is an important biome for conserving species and provisioning ecosystem services. Volume equations in this biome are scarce because of their size and physiognomic diversity. This study was conducted to develop specific volumetric models for the phytophysiognomies Gallery Forest, Dry Forest, Forest Savannah, and Savannah Woodland, a generic model and a model for Cerrado forest formation. Twelve 10 m × 10 m (100 m²) (National Forest Inventory) plots were used for each phytophysiognomy at different sites (regions) of the Federal District (FD) where trees had a diameter at breast height (DBH; 1.30 m) ≥5 cm in forest formations and a diameter at base height (Db; 0.30 m) ≥5 cm in savanna formations. Their diameters and heights were measured, they were cut and cubed, and the volume of each tree was obtained according to the Smalian methodology. Linear and nonlinear models were adjusted. Criteria for the selection of models were determined using correlation coefficients, the standard error of the estimates, and a graphical analysis of the residues. They were later validated by the chi-square test. The resultant models indicated that fit by specific phytophysiognomy was ideal; however, the generic and forest formation models exhibited similar performance to specific models and could be used in extensive areas of the Cerrado, where they represent a high potential for generalization. To further increase our understanding, similar research is recommended for the development of specific and generic models of the total volume in Cerrado areas. Full article

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20 pages, 3424 KiB

Open AccessArticle

Relationship between Cumulative Temperature and Light Intensity and G93 Parameters of Isoprene Emission for the Tropical Tree Ficus septica

by Hirosuke Oku, Asif Iqbal, Shigeki Oogai, Masashi Inafuku and Ishmael Mutanda

Plants 2024, 13(2), 243; https://doi.org/10.3390/plants13020243 - 15 Jan 2024

Cited by 1 | Viewed by 1702

Abstract

The most widely used isoprene emission algorithm, G93 formula, estimates instantaneous leaf-level isoprene emission using the basal emission factor and light and temperature dependency parameters. The G93 parameters have been suggested to show variation depending on past weather conditions, but no study has [...] Read more.

The most widely used isoprene emission algorithm, G93 formula, estimates instantaneous leaf-level isoprene emission using the basal emission factor and light and temperature dependency parameters. The G93 parameters have been suggested to show variation depending on past weather conditions, but no study has closely examined the relationship between past meteorological data and the algorithm parameters. Here, to examine the influence of the past weather on these parameters, we monitored weather conditions, G93 parameters, isoprene synthase transcripts and protein levels, and MEP pathway metabolites in the tropical tree Ficus septica for 12 days and analyzed their relationship with cumulative temperature and light intensity. Plants were illuminated with varying (ascending and descending) light regimes, and our previously developed Ping-Pong optimization method was used to parameterize G93. The cumulative temperature of the past 5 and 7 days positively correlated with C_T₂ and α, respectively, while the cumulative light intensity of the past 10 days showed the highest negative correlation with α. Concentrations of MEP pathway metabolites and IspS gene expression increased with increasing cumulative temperature. At best, the cumulative temperature of the past 2 days positively correlated with the MEP pathway metabolites and IspS gene expression, while these factors showed a biphasic positive and negative correlation with cumulative light intensity. Optimized G93 captured well the temperature and light dependency of isoprene emission at the beginning of the experiment; however, its performance significantly decreased for the latter stages of the experimental duration, especially for the descending phase. This was successfully improved through separate optimization of the ascending and descending phases, emphasizing the importance of the optimization of formula parameters and model improvement. These results have important implications for the improvement of isoprene emission algorithms, particularly under the predicted increase in future global temperatures. Full article

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2023

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18 pages, 3165 KiB

Open AccessArticle

AMMI and GGE Biplot Analyses for Mega-Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments

by Kibreab Yosefe Wodebo, Taye Tolemariam, Solomon Demeke, Weyessa Garedew, Tessema Tesfaye, Muluken Zeleke, Deribe Gemiyu, Worku Bedeke, Jane Wamatu and Mamta Sharma

Plants 2023, 12(17), 3064; https://doi.org/10.3390/plants12173064 - 25 Aug 2023

Cited by 17 | Viewed by 2636

Abstract

This paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated [...] Read more.

This paper reports an evaluation of eleven oat genotypes in four environments for two consecutive years to identify high-biomass-yielding, stable, and broadly adapted genotypes in selected parts of Ethiopia. Genotypes were planted and evaluated with a randomized complete block design, which was repeated three times. The additive main effect and multiplicative interaction analysis of variances revealed that the environment, genotype, and genotype–environment interaction had a significant (p ≤ 0.001) influence on the biomass yield in the dry matter base (t ha⁻¹). The interaction of the first and second principal component analysis accounted for 73.43% and 14.97% of the genotype according to the environment interaction sum of squares, respectively. G6 and G5 were the most stable and widely adapted genotypes and were selected as superior genotypes. The genotype-by-environment interaction showed a 49.46% contribution to the total treatment of sum-of-squares variation, while genotype and environment effects explained 34.94% and 15.60%, respectively. The highest mean yield was obtained from G6 (12.52 kg/ha), and the lowest mean yield was obtained from G7 (8.65 kg/ha). According to the additive main effect and multiplicative interaction biplot, G6 and G5 were high-yielding genotypes, whereas G7 was a low-yielding genotype. Furthermore, according to the genotype and genotype–environment interaction biplot, G6 was the winning genotype in all environments. However, G7 was a low-yielding genotype in all environments. Finally, G6 was an ideal genotype with a higher mean yield and relatively good stability. However, G7 was a poor-yielding and unstable genotype. The genotype, environment, and genotype x environment interaction had extremely important effects on the biomass yield of oats. The findings of the graphic stability methods (additive main effect and multiplicative interaction and the genotype and genotype–environment interaction) for identifying high-yielding and stable oat genotypes were very similar. Full article

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16 pages, 1557 KiB

Open AccessArticle

Theoretical Analyses of Turgor Pressure during Stress Relaxation and Water Uptake, and after Changes in Expansive Growth Rate When Water Uptake Is Normal and Reduced

by Joseph K. E. Ortega

Plants 2023, 12(9), 1891; https://doi.org/10.3390/plants12091891 - 5 May 2023

Cited by 3 | Viewed by 5846

Abstract

Turgor pressure provides the force needed to stress and deform the cell walls of plants, algae, and fungi during expansive growth. However, turgor pressure plays another subtle but equally important role in expansive growth of walled cells: it connects the two biophysical processes [...] Read more.

Turgor pressure provides the force needed to stress and deform the cell walls of plants, algae, and fungi during expansive growth. However, turgor pressure plays another subtle but equally important role in expansive growth of walled cells: it connects the two biophysical processes of water uptake and wall deformation to ensure that the volumetric rates of water uptake and enlargement of the cell wall chamber are equal. In this study, the role of turgor pressure as a ‘connector’ is investigated analytically by employing validated and established biophysical equations. The objective is to determine the effect of ‘wall loosening’ on the magnitude of turgor pressure. It is known that an increase or decrease in turgor pressure and/or wall loosening rate increases or decreases the expansive growth rate, respectively. Interestingly, it is shown that an increase in the wall loosening rate decreases the turgor pressure slightly, thus reducing the effect of wall loosening on increasing the expansive growth rate. Other analyses reveal that reducing the rate of water uptake results in a larger decrease in turgor pressure with the same increase in wall loosening rate, which further reduces the effect of wall loosening on increasing the expansive growth rate. Full article

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14 pages, 2748 KiB

Open AccessArticle

Modeling for Predicting the Potential Geographical Distribution of Three Ephedra Herbs in China

by Longfei Guo, Yu Gao, Ping He, Yuan He and Fanyun Meng

Plants 2023, 12(4), 787; https://doi.org/10.3390/plants12040787 - 9 Feb 2023

Cited by 12 | Viewed by 2474

Abstract

Ephedra species are beneficial for environmental protection in desert and grassland ecosystems. They have high ecological, medicinal, and economic value. To strengthen the protection of the sustainable development of Ephedra, we used occurrence records of Ephedra sinica Stapf., Ephedra intermedia Schrenk et [...] Read more.

Ephedra species are beneficial for environmental protection in desert and grassland ecosystems. They have high ecological, medicinal, and economic value. To strengthen the protection of the sustainable development of Ephedra, we used occurrence records of Ephedra sinica Stapf., Ephedra intermedia Schrenk et C.A. Mey., and Ephedra equisetina Bge., combined with climate, soil, and topographic factors to simulate the suitable habitat of three Ephedra based on ensemble models on the Biomod2 platform. The results of the models were tested using AUC, TSS, and kappa coefficients. The results demonstrated that the ensemble model was able to accurately predict the potential distributions of E. sinica, E. intermedia, and E. equisetina. Eastern and central Inner Mongolia, middle and eastern Gansu, and northeastern Xinjiang were the optimum regions for the growth of E. sinica, E. intermedia, and E. equisetina, respectively. Additionally, several key environmental factors had a significant influence on the suitable habitats of the three Ephedra. The key factors affecting the distribution of E. sinica, E. intermedia, and E. equisetina were annual average precipitation, altitude, and vapor pressure, respectively. In conclusion, the results showed that the suitable ranges of the three Ephedra were mainly in Northwest China and that topography and climate were the primary influencing factors. Full article

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2022

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24 pages, 5231 KiB

Open AccessArticle

Crop Model Parameterisation of Three Important Pearl Millet Varieties for Improved Water Use and Yield Estimation

by Petrus A. Ausiku, John G. Annandale, Joachim Martin Steyn and Andrew J. Sanewe

Plants 2022, 11(6), 806; https://doi.org/10.3390/plants11060806 - 18 Mar 2022

Cited by 3 | Viewed by 3881

Abstract

Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast [...] Read more.

Pearl millet is an important crop for food security in Asia and Africa’s arid and semi-arid regions. It is widely grown as a staple cereal grain for human consumption and livestock fodder. Mechanistic crop growth and water balance models are useful to forecast crop production and water use. However, very few studies have been devoted to the development of the model parameters needed for such simulations for pearl millet. The objectives of the study were to determine crop-specific model parameters for each of three pearl millet varieties (landrace, hybrid, and improved), as well as to calibrate and validate the Soil Water Balance (SWB) model for predicting pearl millet production and water use based on weather data. The SWB was chosen because it is widely used in southern Africa; however, the developed parameters should benefit other models as well. The presented crop-specific parameter values were derived from field observations and literature. Varieties with different phenology, maturity dates and tillering habits were grown under well-watered and well-fertilised conditions for calibration purposes. The calibrated model was used to predict biomass production, grain yield and crop water use. The hybrid’s water use efficiency was higher than that of the landrace and improved variety. Full article

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56 pages, 6122 KiB

Open AccessArticle

Towards a Stochastic Model to Simulate Grapevine Architecture: A Case Study on Digitized Riesling Vines Considering Effects of Elevated CO₂

by Dominik Schmidt, Katrin Kahlen, Christopher Bahr and Matthias Friedel

Plants 2022, 11(6), 801; https://doi.org/10.3390/plants11060801 - 17 Mar 2022

Cited by 3 | Viewed by 2579

Abstract

Modeling plant growth, in particular with functional-structural plant models, can provide tools to study impacts of changing environments in silico. Simulation studies can be used as pilot studies for reducing the on-field experimental effort when predictive capabilities are given. Robust model calibration leads [...] Read more.

Modeling plant growth, in particular with functional-structural plant models, can provide tools to study impacts of changing environments in silico. Simulation studies can be used as pilot studies for reducing the on-field experimental effort when predictive capabilities are given. Robust model calibration leads to less fragile predictions, while introducing uncertainties in predictions allows accounting for natural variability, resulting in stochastic plant growth models. In this study, stochastic model components that can be implemented into the functional-structural plant model Virtual Riesling are developed relying on Bayesian model calibration with the goal to enhance the model towards a fully stochastic model. In this first step, model development targeting phenology, in particular budburst variability, phytomer development rate and internode growth are presented in detail. Multi-objective optimization is applied to estimate a single set of cardinal temperatures, which is used in phenology and growth modeling based on a development days approach. Measurements from two seasons of grapevines grown in a vineyard with free-air carbon dioxide enrichment (FACE) are used; thus, model building and selection are coupled with an investigation as to whether including effects of elevated CO

_{2}

conditions to be expected in 2050 would improve the models. The results show how natural variability complicates the detection of possible treatment effects, but demonstrate that Bayesian calibration in combination with mixed models can realistically recover natural shoot growth variability in predictions. We expect these and further stochastic model extensions to result in more realistic virtual plant simulations to study effects, which are used to conduct in silico studies of canopy microclimate and its effects on grape health and quality. Full article

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23 pages, 4954 KiB

Open AccessArticle

Predicting the Potential Suitable Climate for Coconut (Cocos nucifera L.) Cultivation in India under Climate Change Scenarios Using the MaxEnt Model

by Kukkehalli Balachandra Hebbar, Pulloott Sukumar Abhin, Veliyathukudy Sanjo Jose, Poonchalikundil Neethu, Arya Santhosh, Sandip Shil and P. V. Vara Prasad

Plants 2022, 11(6), 731; https://doi.org/10.3390/plants11060731 - 9 Mar 2022

Cited by 32 | Viewed by 8038

Abstract

Climate change and climate variability are projected to alter the geographic suitability of lands for crop cultivation. Early awareness of the future climate of the current cultivation areas for a perennial tree crop like coconut is needed for its adaptation and sustainable cultivation [...] Read more.

Climate change and climate variability are projected to alter the geographic suitability of lands for crop cultivation. Early awareness of the future climate of the current cultivation areas for a perennial tree crop like coconut is needed for its adaptation and sustainable cultivation in vulnerable areas. We analyzed coconut’s vulnerability to climate change in India, based on climate projections for the 2050s and the 2070s under two Representative Concentration Pathways (RCPs): 4.5 and 8.5. Based on the current cultivation regions and climate change predictions from seven ensembles of Global Circulation Models, we predict changes in relative climatic suitability for coconut cultivation using the MaxEnt model. Bioclimatic variables Bio 4 (temperature seasonality, 34.4%) and Bio 7 (temperature annual range, 28.7%) together contribute 63.1%, which along with Bio 15 (precipitation seasonality, 8.6%) determined 71.7% of the climate suitability for coconuts in India. The model projected that some current coconut cultivation producing areas will become unsuitable (plains of South interior Karnataka and Tamil Nadu) requiring crop change, while other areas will require adaptations in genotypic or agronomic management (east coast and the south interior plains), and yet in others, the climatic suitability for growing coconut will increase (west coast). The findings suggest the need for adaptation strategies so as to ensure sustainable cultivation of coconut at least in presently cultivated areas. Full article

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25 pages, 882 KiB

Open AccessArticle

Biophysical Equations and Pressure Probe Experiments to Determine Altered Growth Processes after Changes in Environment, Development, and Mutations

by Joseph K. E. Ortega

Plants 2022, 11(3), 302; https://doi.org/10.3390/plants11030302 - 24 Jan 2022

Cited by 3 | Viewed by 2480

Abstract

Expansive growth is a culmination of many biological processes. It is fundamental to volume growth, development, morphogenesis, sensory responses, and environmental responses of plants, fungi, and algae. Expansive growth of walled cells and plant tissue can be accurately described by a set of [...] Read more.

Expansive growth is a culmination of many biological processes. It is fundamental to volume growth, development, morphogenesis, sensory responses, and environmental responses of plants, fungi, and algae. Expansive growth of walled cells and plant tissue can be accurately described by a set of three global biophysical equations that model the biophysical processes of water uptake, wall deformation, and turgor pressure. Importantly, these biophysical equations have been validated with the results of pressure probe experiments. Here, a systematic method (scheme) is presented that iterates between analyses with the biophysical equations and experiments conducted with the pressure probe. This iterative scheme is used to determine altered growth processes for four cases; two after changes in the environment, one after a change in development, and another after changes by mutation. It is shown that this iterative scheme can identify which biophysical processes are changed, the magnitude of the changes, and their contribution to the change in expansive growth rate. Dimensionless numbers are employed to determine the magnitude of the changes in the biophysical processes. The biological meaning and implication of the biophysical variables in the biophysical equations are discussed. Further, additional sets of global biophysical equations are presented and discussed. Full article

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2021

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14 pages, 1006 KiB

Open AccessArticle

Validating a Simple Mechanistic Model That Describes Weather Impact on Pasture Growth

by Edward B. Rayburn

Plants 2021, 10(9), 1754; https://doi.org/10.3390/plants10091754 - 24 Aug 2021

Cited by 2 | Viewed by 2094

Abstract

Mathematical models have many uses. When input data is limited, simple models are required. This occurs in pasture agriculture when managers typically only have access to temperature and rainfall values. A simple pasture growth model was developed that requires only latitude and daily [...] Read more.

Mathematical models have many uses. When input data is limited, simple models are required. This occurs in pasture agriculture when managers typically only have access to temperature and rainfall values. A simple pasture growth model was developed that requires only latitude and daily maximum and minimum temperature and rainfall. The accuracy of the model was validated using ten site-years of measured pasture growth at a site under continuous stocking where management controlled the height of grazing (HOG) and a site under rotational stocking at a West Virginia University farm (WVU). Relative forage growth, expressed as a fraction of maximum growth observed at the sites, was reasonably accurate. At the HOG site constant bias in relative growth was not different from zero. There was a year effect due to the weather station used for predicting growth at HOG being 1.8 km from the pasture. However, the error was only about 10-percent. At the WVU site constant bias for relative growth was not different from zero and year effect was eliminated when adjusted for nitrogen status of the treatments. This simple model described relative pasture growth within 10-percent of average for a given site, environment, and management using only daily weather inputs that are readily available. Using predictions of climate change impact on temperature and rainfall frequency and intensity this model can be used to predict the impact on pasture growth. Full article

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16 pages, 2090 KiB

Open AccessArticle

The Potential of Deep Roots to Mitigate Impacts of Heatwaves and Declining Rainfall on Pastures in Southeast Australia

by Rachelle Meyer, Alexandria Sinnett, Ruchika Perera, Brendan Cullen, Bill Malcolm and Richard J. Eckard

Plants 2021, 10(8), 1641; https://doi.org/10.3390/plants10081641 - 10 Aug 2021

Cited by 4 | Viewed by 2792

Abstract

Declines in growing-season rainfall and increases in the frequency of heatwaves in southern Australia necessitate effective adaptation. The Sustainable Grazing Systems Pasture Model (SGS) was used to model the growth of three pasture species differing in root depth and root distribution under three [...] Read more.

Declines in growing-season rainfall and increases in the frequency of heatwaves in southern Australia necessitate effective adaptation. The Sustainable Grazing Systems Pasture Model (SGS) was used to model the growth of three pasture species differing in root depth and root distribution under three different climate scenarios at two sites. The modelled metabolisable energy intake (in MJ) was used in a partial discounted net cash flow budget. Both the biophysical and economic modelling suggest that deep roots were advantageous in all climate scenarios at the long growing season site but provided no to little advantage at the short growing season site, likely due to the deep-rooted species drying out the soil profile earlier. In scenarios including climate change, the DM production of the deep-rooted species at the long growing season site averaged 386 kg/ha/year more than the more shallow-rooted species, while at the site with a shorter growing season it averaged 205 kg/ha/year less than the shallower-rooted species. The timing of the extra growth and pasture persistence strongly influenced the extent of the benefit. At the short growing season site other adaptation options such as summer dormancy will likely be necessary. Full article

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14 pages, 2127 KiB

Open AccessArticle

Probabilistic Provenance Detection and Management Pathways for Pseudotsuga menziesii (Mirb.) Franco in Italy Using Climatic Analogues

by Maurizio Marchi and Claudia Cocozza

Plants 2021, 10(2), 215; https://doi.org/10.3390/plants10020215 - 23 Jan 2021

Cited by 7 | Viewed by 2574

Abstract

The introduction of Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco] in Europe has been one of the most important and extensive silvicultural experiments since the 1850s. This success was mainly supported by the species’ wide genome and phenotypic plasticity even if the genetic origin [...] Read more.

The introduction of Douglas-fir [Pseudotsuga menziesii (Mirb.) Franco] in Europe has been one of the most important and extensive silvicultural experiments since the 1850s. This success was mainly supported by the species’ wide genome and phenotypic plasticity even if the genetic origin of seeds used for plantations is nowadays often unknown. This is especially true for all the stands planted before the IUFRO experimentation in the 1960s. In this paper, a methodology to estimate the Douglas-fir provenances currently growing in Italy is proposed. The raw data from the last Italian National Forest Inventory were combined with literature information to obtain the current spatial distribution of the species in the country representing its successful introduction. Afterwards, a random forest classification model was run using downscaled climatic data as predictors and the classification scheme adopted in previous research studies in the Pacific North West of America. The analysis highlighted good matching between the native and the introduction range in Italy. Coastal provenances from British Columbia and the dry coast of Washington were detected as the most likely seed sources, covering 63.4% and 33.8% of the current distribution of the species in the country, respectively. Interior provenances and those from the dry coast of Oregon were also represented but limited to very few cases. The extension of the model on future scenarios predicted a gradual shift in suitable provenances with the dry coast of Oregon in the mid-term (2050s) and afterwards California (2080s) being highlighted as possible new seed sources. However, only further analysis with genetic markers and molecular methods will be able to confirm the proposed scenarios. A validation of the genotypes currently available in Italy will be mandatory as well as their regeneration processes (i.e., adaptation), which may also diverge from those occurring in the native range due to a different environmental pressure. This new information will also add important knowledge, allowing a refinement of the proposed modeling framework for a better support for forest managers. Full article

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2020

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11 pages, 592 KiB

Open AccessArticle

Growth Indicators of Main Species Predict Aboveground Biomass of Population and Community on a Typical Steppe

by Xiaojuan Huang, Yongjie Liu, Niya Wang, Lan Li, An Hu, Zhen Wang, Shenghua Chang, Xianjiang Chen and Fujiang Hou

Plants 2020, 9(10), 1314; https://doi.org/10.3390/plants9101314 - 5 Oct 2020

Cited by 1 | Viewed by 2489

Abstract

The objective was to explore a fast, accurate, non-destructive, and less disturbance method for predicting the aboveground biomass (AGB) of the typical steppe, by using plant height and canopy diameter of the dominant species, Stipa bungeana, Artemisia capillaris, and Lespedeza davurica [...] Read more.

The objective was to explore a fast, accurate, non-destructive, and less disturbance method for predicting the aboveground biomass (AGB) of the typical steppe, by using plant height and canopy diameter of the dominant species, Stipa bungeana, Artemisia capillaris, and Lespedeza davurica, data were observed from 165 quadrats during the peak plant growing season, and the product of plant height (PH) and canopy diameter (PC) were calculated for each species. AGB of population were predicted for the same species and other species through using 2/3 of the measured data, and the optimal predictive equation was linear in terms of determination coefficient. The other 1/3 of the data, which was measured from no grazing paddocks or rotational grazing paddocks, was substituted into the predictive equations for validation. Results showed that PC of one dominant species could be used to predict AGB of the same species or other species well. The predicted and measured values were significantly correlative, and most of the predictive accuracy was above 80%, and not affected by managements of grassland, including rotational grazing or no grazing. A combination of 3 to 6 representative species was used to predict AGB of the community, and the predictive equations with PC of six species as an independent variable were the most optimal because explaining 83.5% variation of AGB. The predictive methods cost 1/15, 1/9, and 1/51 of time, labor, and capital as much as the destructive sample method (quadrat sampling method), respectively, and thus improved the efficiency of field study and protecting the fragile study areas, especially the long-term study sites in grassland. Full article

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Modeling Impacts of Changing Environmental Conditions on Plant Growth

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2024

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2023

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