Beta effect of eCO2 can cause as much rainfall decrease as large-scale deforestation in the Amazon

2021 ◽  
Author(s):  
David Lapola ◽  
Gilvan Sampaio ◽  
Marília Shimizu ◽  
Carlos Guimarães-Júnior ◽  
Felipe Alexandre ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Strong Dependence ◽  
Physiological Effect ◽  
Heat Fluxes ◽  
Vegetation Coverage ◽  
Annual Rainfall ◽  
Area Index ◽  
Canopy Transpiration ◽  
Amazon Rainfall

<p>Amazon region’s climate is particularly sensitive to surface processes and properties such as heat fluxes and vegetation coverage. Rainfall is a key expression of such land surface-atmosphere interactions in the region due to its strong dependence on forest transpiration. While a large number of past studies have shown the impacts of large-scale deforestation on annual rainfall, studies on the isolated effects of elevated atmospheric CO<sub>2</sub> concentration (eCO<sub>2</sub>) on plant physiology (i.e. the β effect), for example on canopy transpiration and rainfall, are scarcer. Here we make a systematic comparison of the plant physiological effects of eCO<sub>2</sub> and deforestation on Amazon rainfall. We use the CPTEC-Brazilian Atmospheric Model (BAM) with dynamic vegetation under a 1.5xCO<sub>2</sub> and a 100% substitution of the forest by pasture grassland, with all other conditions held similar between the two scenarios. We find that both scenarios result in equivalent average annual rainfall reductions (Physiology: -252 mm,-12%; Deforestation: -292 mm, -13%) that are well above observed Amazon rainfall interannual variability of 5.1%. Rainfall decrease in the two scenarios are caused by a reduction of approximately 20% of canopy transpiration, but for different reasons: eCO<sub>2</sub>-driven reduction of stomatal conductance in the Physiology run; decreased leaf area index of pasture (-66%) and its dry-season lower surface vegetation coverage in the Deforestation run. Walker circulation is strengthened in the two scenarios (with enhanced convection over the Andes and a weak subsidence branch over east Amazon) but, again, through different mechanisms: enhanced west winds from the Pacific and reduced easterlies entering the basin in Physiology, and strongly increased easterlies in Deforestation. Although our results for the Deforestation scenario are in agreement with previous observational and modelling studies, the lack of direct field-based ecosystem-level experimental evidence on the effect of eCO<sub>2</sub> in moisture fluxes of tropical forests confers a substantial level of uncertainty to this and any other projections on the physiological effect of eCO<sub>2</sub> on Amazon rainfall. Furthermore, our results denote the incurred responsibilities of both Amazonian and non- Amazonian countries to mitigate potential future climatic change and its impacts in the region driven either by local deforestation (to be tackled by Amazonian countries) or global CO<sub>2</sub> emissions (to be handled by all countries).</p>

scholarly journals CO<sub>2</sub> physiological effect can cause rainfall decrease as strong as large-scale deforestation in the Amazon

2021 ◽  
Vol 18 (8) ◽  
pp. 2511-2525
Author(s):  
Gilvan Sampaio ◽  
Marília H. Shimizu ◽  
Carlos A. Guimarães-Júnior ◽  
Felipe Alexandre ◽  
Marcelo Guatura ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Strong Dependence ◽  
Physiological Effect ◽  
Heat Fluxes ◽  
Vegetation Coverage ◽  
Annual Rainfall ◽  
Area Index ◽  
Canopy Transpiration ◽  
Amazon Rainfall

Abstract. The climate in the Amazon region is particularly sensitive to surface processes and properties such as heat fluxes and vegetation coverage. Rainfall is a key expression of the land surface–atmosphere interactions in the region due to its strong dependence on forest transpiration. While a large number of past studies have shown the impacts of large-scale deforestation on annual rainfall, studies on the isolated effects of elevated atmospheric CO2 concentrations (eCO2) on canopy transpiration and rainfall are scarcer. Here, for the first time, we systematically compare the plant physiological effects of eCO2 and deforestation on Amazon rainfall. We use the CPTEC Brazilian Atmospheric Model (BAM) with dynamic vegetation under a 1.5×CO2 experiment and a 100 % substitution of the forest by pasture grasslands, with all other conditions held similar between the two scenarios. We find that both scenarios result in equivalent average annual rainfall reductions (Physiology: −257 mm, −12 %; Deforestation: −183 mm, −9 %) that are above the observed Amazon rainfall interannual variability of 5 %. The rainfall decreases predicted in the two scenarios are linked to a reduction of approximately 20 % in canopy transpiration but for different reasons: the eCO2-driven reduction of stomatal conductance drives the change in the Physiology experiment, and the smaller leaf area index of pasturelands (−72 % compared to tropical forest) causes the result in the Deforestation experiment. The Walker circulation is modified in the two scenarios: in Physiology due to a humidity-enriched free troposphere with decreased deep convection due to the heightening of a drier and warmer (+2.1 ∘C) boundary layer, and in Deforestation due to enhanced convection over the Andes and a subsidence branch over the eastern Amazon without considerable changes in temperature (−0.2 ∘C in 2 m air temperature and +0.4 ∘C in surface temperature). But again, these changes occur through different mechanisms: strengthened west winds from the Pacific and reduced easterlies entering the basin affect the Physiology experiment, and strongly increased easterlies influence the result of the Deforestation experiment. Although our results for the Deforestation scenario agree with the results of previous observational and modelling studies, the lack of direct field-based ecosystem-level experimental evidence regarding the effect of eCO2 on moisture fluxes in tropical forests confers a considerable level of uncertainty to any projections of the physiological effect of eCO2 on Amazon rainfall. Furthermore, our results highlight the responsibilities of both Amazonian and non-Amazonian countries to mitigate potential future climatic change and its impacts in the region, driven either by local deforestation or global CO2 emissions.

scholarly journals CO<sub>2</sub> fertilization effect can cause rainfall decrease as strong as large-scale deforestation in the Amazon

2020 ◽  
Author(s):  
Gilvan Sampaio ◽  
Marília Shimizu ◽  
Carlos A. Guimarães-Júnior ◽  
Felipe Alexandre ◽  
Manoel Cardoso ◽  
...  
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Strong Dependence ◽  
Physiological Effect ◽  
Heat Fluxes ◽  
Vegetation Coverage ◽  
Annual Rainfall ◽  
Area Index ◽  
Canopy Transpiration ◽  
Amazon Rainfall

Abstract. Climate in the Amazon region is particularly sensitive to surface processes and properties such as heat fluxes and vegetation coverage. Rainfall is a key expression of land surface-atmosphere interactions in the region due to its strong dependence on forest transpiration. While a large number of past studies have shown the impacts of large-scale deforestation on annual rainfall, studies on the isolated effects of elevated atmospheric CO2 concentration (eCO2) on canopy transpiration and rainfall are scarcer. Here for the first time we make a systematic comparison of the plant physiological effects of eCO2 and deforestation on Amazon rainfall. We use the CPTEC-Brazilian Atmospheric Model (BAM) with dynamic vegetation under a 1.5xCO2 and a 100 % substitution of the forest by pasture grassland, with all other conditions held similar between the two scenarios. We find that both scenarios result in equivalent average annual rainfall reductions (Physiology: −252 mm, −12 %; Deforestation: −292 mm, −13 %) that are well above observed Amazon rainfall interannual variability of 5.1 %. Rainfall decrease in the two scenarios are caused by a reduction of approximately 20 % of canopy transpiration, but for different reasons: eCO2-driven reduction of stomatal conductance in Physiology; decreased leaf area index of pasture (−66 %) and its dry-season lower surface vegetation coverage in Deforestation. Walker circulation is strengthened in the two scenarios (with enhanced convection over the Andes and a weak subsidence branch over east Amazon) but, again, through different mechanisms: enhanced west winds from the Pacific and reduced easterlies entering the basin in Physiology, and strongly increased easterlies in the Deforestation. Although our results for the Deforestation scenario are in agreement with previous observational and modelling studies, the lack of direct field-based ecosystem-level experimental evidence on the effect of eCO2 in moisture fluxes of tropical forests confers a considerable level of uncertainty to any projections on the physiological effect of eCO2 on Amazon rainfall. Furthermore, our results highlight the responsibilities of both Amazonian and non-Amazonian countries to mitigate potential future climatic change and its impacts in the region driven either by local deforestation or global CO2 emissions.

scholarly journals Effects of Forest Changes on Summer Surface Temperature in Changbai Mountain, China

Forests ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1551
Author(s):  
Jiaqi Zhang ◽  
Xiangjin Shen ◽  
Yanji Wang ◽  
Ming Jiang ◽  
Xianguo Lu
Keyword(s):  
Climate Change ◽  
Surface Temperature ◽  
Land Surface ◽  
Climate Models ◽  
Regional Climate ◽  
Changbai Mountain ◽  
Vegetation Coverage ◽  
Area Index ◽  
Forest Coverage ◽  
Cooling Effects

The area and vegetation coverage of forests in Changbai Mountain of China have changed significantly during the past decades. Understanding the effects of forests and forest coverage change on regional climate is important for predicting climate change in Changbai Mountain. Based on the satellite-derived land surface temperature (LST), albedo, evapotranspiration, leaf area index, and land-use data, this study analyzed the influences of forests and forest coverage changes on summer LST in Changbai Mountain. Results showed that the area and vegetation coverage of forests increased in Changbai Mountain from 2003 to 2017. Compared with open land, forests could decrease the summer daytime LST (LSTD) and nighttime LST (LSTN) by 1.10 °C and 0.07 °C, respectively. The increase in forest coverage could decrease the summer LSTD and LSTN by 0.66 °C and 0.04 °C, respectively. The forests and increasing forest coverage had cooling effects on summer temperature, mainly by decreasing daytime temperature in Changbai Mountain. The daytime cooling effect is mainly related to the increased latent heat flux caused by increasing evapotranspiration. Our results suggest that the effects of forest coverage change on climate should be considered in climate models for accurately simulating regional climate change in Changbai Mountain of China.

scholarly journals Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

2008 ◽  
Vol 5 (5) ◽  
pp. 4161-4207 ◽  
Author(s):  
H. W. Ter Maat ◽  
R. W. A. Hutjes
Keyword(s):  
Carbon Dioxide ◽  
Land Surface ◽  
Large Scale ◽  
Regional Scale ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Surface Model ◽  
Carbon Exchange ◽  
Regional Atmospheric Modelling System

Abstract. A large scale mismatch exists between our understanding and quantification of ecosystem atmosphere exchange of carbon dioxide at local scale and continental scales. This paper will focus on the carbon exchange on the regional scale to address the following question: What are the main controlling factors determining atmospheric carbon dioxide content at a regional scale? We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also sub models for urban and marine fluxes, which in principle include the main controlling mechanisms and capture the relevant dynamics of the system. To validate the model, observations are used which were taken during an intensive observational campaign in the central Netherlands in summer 2002. These included flux-site observations, vertical profiles at tall towers and spatial fluxes of various variables taken by aircraft. The coupled regional model (RAMS-SWAPS-C) generally does a good job in simulating results close to reality. The validation of the model demonstrates that surface fluxes of heat, water and CO2 are reasonably well simulated. The comparison against aircraft data shows that the regional meteorology is captured by the model. Comparing spatially explicit simulated and observed fluxes we conclude that in general simulated latent heat fluxes are underestimated by the model to the observations which exhibit large standard deviation for all flights. Sensitivity experiments demonstrated the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same test also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

Sensitivity of Summertime Heatwaves to Vegetation Cover in the Northern Hemisphere

2020 ◽  
Author(s):  
Jing Li ◽  
Chi-Yung Tam ◽  
Amos P. K. Tai ◽  
Ngar-Cheung Lau
Keyword(s):  
North America ◽  
Latent Heat ◽  
Vegetation Cover ◽  
Land Surface ◽  
Large Scale ◽  
Longwave Radiation ◽  
Surface Friction ◽  
Sensible Heat ◽  
Southeastern Part ◽  
Area Index

&lt;p&gt;Heatwaves are a serious threat to society and can lead to grave consequences. It is well known that persistent large-scale circulation anomalies are the key to generating heatwaves. Vegetation plays a vital role in energy and water exchange between land and atmosphere, through its responses to incoming radiation and emission of longwave radiation, its imposition of surface friction and transpiration. However, its impact on surface energy exchange during heatwaves is largely unknown. In this study, we first analyzed the relationship between summer heatwaves and vegetation cover, based on the Global Heatwave and Warm-spell Record (GHWR) and leaf area index (LAI) products from satellites during 1982-2011. Our results revealed differences in the correlation between heatwave characteristics and summertime LAI in different regions. In particular, lower LAI over Central Europe is associated with more frequent heatwaves locally. Over the south to the southeastern part of North America, a similar negative correlation is found. However, in the northeastern part of the continent, the reverse tends to be true, with higher-than-normal LAI associated with an increase of heatwave occurrence. These findings are in general supported by composite analyses of extreme LAI years in these regions and heatwave characteristics therein.&lt;/p&gt;&lt;p&gt;We speculate that the difference between surface heat flux responses for different vegetation types during heatwaves may explain the results. Focusing on North America, and using various datasets including those generated by the Global Land Data Assimilation System (GLDAS) with three different land surface models (CLM, MOS, NOAH), three reanalysis datasets (MERRA-2, NOAA-CIRES-DOS, NCEP/NCAR), and also observations from an extensive network of flux towers, it was found that over coniferous forests (both boreal and temperate), the sensible heat anomalies increase significantly during heatwaves in high-LAI years. Also, during high-LAI years, over boreal evergreen forests (BEF), changes of latent heat anomalies are much smaller than positive sensible heat anomalies, so that BEF can prolong and amplify heatwaves significantly. On the other hand, for temperate deciduous forests (TDF) and grassland (GSL), both negative sensible heat anomalies and positive latent heat anomalies during heatwaves are found in all datasets; these response act to weaken the heatwave amplitudes. Model experiments were further carried out, in order to test the sensitivity of heatwaves to LAI forcings. It was found that heatwaves are most sensitive to BEF LAI variations, but the response of heatwaves are opposite between middle and high latitudes when BEF LAI increased. For TDF and GSL, heatwaves shortened slightly when LAI increased.&lt;/p&gt;

scholarly journals JULES-crop: a parametrisation of crops in the Joint UK Land Environment Simulator

2014 ◽  
Vol 7 (5) ◽  
pp. 6773-6809
Author(s):  
T. Osborne ◽  
J. Gornall ◽  
J. Hooker ◽  
K. Williams ◽  
A. Wiltshire ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Land Surface Model ◽  
Water Security ◽  
Climate Change Impacts ◽  
Heat Fluxes ◽  
Surface Model ◽  
Yield Model ◽  
Area Index ◽  
The Impact

Abstract. Studies of climate change impacts on the terrestrial biosphere have been completed without recognition of the integrated nature of the biosphere. Improved assessment of the impacts of climate change on food and water security requires the development and use of models not only representing each component but also their interactions. To meet this requirement the Joint UK Land Environment Simulator (JULES) land surface model has been modified to include a generic parametrisation of annual crops. The new model, JULES-crop, is described and evaluation at global and site levels for the four globally important crops; wheat, soy bean, maize and rice is presented. JULES-crop demonstrates skill in simulating the inter-annual variations of yield for maize and soy bean at the global level, and for wheat for major spring wheat producing countries. The impact of the new parametrisation, compared to the standard configuration, on the simulation of surface heat fluxes is largely an alteration of the partitioning between latent and sensible heat fluxes during the later part of the growing season. Further evaluation at the site level shows the model captures the seasonality of leaf area index and canopy height better than in standard JULES. However, this does not lead to an improvement in the simulation of sensible and latent heat fluxes. The performance of JULES-crop from both an earth system and crop yield model perspective is encouraging however, more effort is needed to develop the parameterisation of the model for specific applications. Key future model developments identified include the specification of the yield gap to enable better representation of the spatial variability in yield.

scholarly journals Multi-site, multi-crop measurements in the soil-vegetation-atmosphere continuum: A comprehensive dataset from two climatically contrasting regions in South West Germany for the period 2009–2018

2021 ◽  
Author(s):  
Tobias K. D. Weber ◽  
Joachim Ingwersen ◽  
Petra Högy ◽  
Arne Poyda ◽  
Hans-Dieter Wizemann ◽  
...  
Keyword(s):  
Land Surface ◽  
Heat Fluxes ◽  
Data Availability ◽  
West Germany ◽  
Annual Precipitation ◽  
Data Set ◽  
Area Index ◽  
Carbon And Nitrogen ◽  
South West ◽  
Mean Temperature

Abstract. We present a comprehensive, high-quality dataset characterising soil-vegetation and land-surface processes from continuous measurements conducted in two climatically contrasting study regions in South West Germany: the warmer and drier Kraichgau region with a mean temperature of 9.7 °C and annual precipitation of 890 mm, and the cooler and wetter Swabian Alp with mean temperature 7.5 °C and annual precipitation 1042 mm. In each region, measurements were conducted over a time period of nine cropping seasons from 2009 to 2018. The backbone of the investigation was formed by six eddy-covariance stations (EC) which measured fluxes of water, energy and carbon dioxide between the land surface and the atmosphere at half-hourly resolution. This resulted in a dataset containing measurements from a total of 54 site*years containing observations with a multitude of crops, as well as considerable variation in local growing season climates. The presented multi-site, multi-year data set is composed of crop-related data on phenological development stages, canopy height, leaf area index, vegetative and generative biomass and their respective carbon and nitrogen content. Time series of soil temperature and soil water content were monitored with 30-min resolution at various points in the soil profile, including ground heat fluxes. Moreover, more than 1,200 soil samples were taken to study changes of carbon and nitrogen contents. The data set was uploaded to the Pangaea database and can be accessed at https://doi.org/10.20387/bonares-a0qc-46jc (for the review process, please refer to the data availability section). One station in each region has now been set up as continuous observatories of state variables and fluxes in intensively managed agricultural fields.

scholarly journals Impact of climate, vegetation, soil and crop management variables on multi-year ISBA-A-gs simulations of evapotranspiration over a Mediterranean crop site

2015 ◽  
Vol 8 (10) ◽  
pp. 3033-3053 ◽  
Author(s):  
S. Garrigues ◽  
A. Olioso ◽  
D. Carrer ◽  
B. Decharme ◽  
J.-C. Calvet ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Surface Model ◽  
Data Sets ◽  
Data Set ◽  
Area Index ◽  
Hydrodynamic Parameters ◽  
Land Surface Parameter ◽  
Crop Succession

Abstract. Generic land surface models are generally driven by large-scale data sets to describe the climate, the soil properties, the vegetation dynamic and the cropland management (irrigation). This paper investigates the uncertainties in these drivers and their impacts on the evapotranspiration (ET) simulated from the Interactions between Soil, Biosphere, and Atmosphere (ISBA-A-gs) land surface model over a 12-year Mediterranean crop succession. We evaluate the forcing data sets used in the standard implementation of ISBA over France where the model is driven by the SAFRAN (Système d'Analyse Fournissant des Renseignements Adaptés à la Nivologie) high spatial resolution atmospheric reanalysis, the leaf area index (LAI) time courses derived from the ECOCLIMAP-II land surface parameter database and the soil texture derived from the French soil database. For climate, we focus on the radiations and rainfall variables and we test additional data sets which include the ERA-Interim (ERA-I) low spatial resolution reanalysis, the Global Precipitation Climatology Centre data set (GPCC) and the MeteoSat Second Generation (MSG) satellite estimate of downwelling shortwave radiations. The evaluation of the drivers indicates very low bias in daily downwelling shortwave radiation for ERA-I (2.5 W m−2) compared to the negative biases found for SAFRAN (−10 W m−2) and the MSG satellite (−12 W m−2). Both SAFRAN and ERA-I underestimate downwelling longwave radiations by −12 and −16 W m−2, respectively. The SAFRAN and ERA-I/GPCC rainfall are slightly biased at daily and longer timescales (1 and 0.5 % of the mean rainfall measurement). The SAFRAN rainfall is more precise than the ERA-I/GPCC estimate which shows larger inter-annual variability in yearly rainfall error (up to 100 mm). The ECOCLIMAP-II LAI climatology does not properly resolve Mediterranean crop phenology and underestimates the bare soil period which leads to an overall overestimation of LAI over the crop succession. The simulation of irrigation by the model provides an accurate irrigation amount over the crop cycle but the timing of irrigation occurrences is frequently unrealistic. Errors in the soil hydrodynamic parameters and the lack of irrigation in the simulation have the largest influence on ET compared to uncertainties in the large-scale climate reanalysis and the LAI climatology. Among climate variables, the errors in yearly ET are mainly related to the errors in yearly rainfall. The underestimation of the available water capacity and the soil hydraulic diffusivity induce a large underestimation of ET over 12 years. The underestimation of radiations by the reanalyses and the absence of irrigation in the simulation lead to the underestimation of ET while the overall overestimation of LAI by the ECOCLIMAP-II climatology induces an overestimation of ET over 12 years. This work shows that the key challenges to monitor the water balance of cropland at regional scale concern the representation of the spatial distribution of the soil hydrodynamic parameters, the variability of the irrigation practices, the seasonal and inter-annual dynamics of vegetation and the spatiotemporal heterogeneity of rainfall.

Progressive Midlatitude Afforestation: Impacts on Clouds, Global Energy Transport, and Precipitation

2016 ◽  
Vol 29 (15) ◽  
pp. 5561-5573 ◽  
Author(s):  
Marysa M. Laguë ◽  
Abigail L. S. Swann
Keyword(s):  
Vegetation Cover ◽  
Land Surface ◽  
Large Scale ◽  
Forest Cover ◽  
Energy Transport ◽  
Climate Impacts ◽  
Heat Fluxes ◽  
Tree Cover ◽  
Climate Response ◽  
Cloud Feedbacks

Abstract Vegetation influences the atmosphere in complex and nonlinear ways, such that large-scale changes in vegetation cover can drive changes in climate on both local and global scales. Large-scale land surface changes have been shown to introduce excess energy to one hemisphere, causing a shift in atmospheric circulation on a global scale. However, past work has not quantified how the climate response scales with the area of vegetation. Here, the response of climate to linearly increasing the area of forest cover in the northern midlatitudes is systematically evaluated. This study shows that the magnitude of afforestation of the northern midlatitudes determines the local climate response in a nonlinear fashion, and the authors identify a threshold in vegetation-induced cloud feedbacks—a concept not previously addressed by large-scale vegetation manipulation experiments. Small increases in tree cover drive compensating cloud feedbacks, while latent heat fluxes reach a threshold after sufficiently large increases in tree cover, causing the troposphere to warm and dry, subsequently reducing cloud cover. Increased absorption of solar radiation at the surface is driven by both surface albedo changes and cloud feedbacks. This study shows how atmospheric cross-equatorial energy transport changes as the area of afforestation is incrementally increased. The results highlight the importance of considering both local and remote climate effects of large-scale vegetation change and explore the scaling relationship between changes in vegetation cover and resulting climate impacts.

scholarly journals Constraints and Opportunities for Detecting Land Surface Phenology in Drylands

2021 ◽  
Author(s):  
Shawn D Taylor ◽  
Dawn M Browning ◽  
Ruben A Baca ◽  
Feng Gao
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Land Surface ◽  
Satellite Remote Sensing ◽  
Large Scale ◽  
Vegetation Index ◽  
Scale Effects ◽  
Simulated Data ◽  
Area Index ◽  
Land Surface Phenology

Land surface phenology, the tracking of seasonal productivity via satellite remote sensing, enables global scale tracking of ecosystem processes, but its utility is limited in some areas. In dryland ecosystems low vegetation cover can cause the growing season vegetation index (VI) to be indistinguishable from the dormant season VI, making phenology extraction impossible. Here, using simulated data and multi-temporal UAV imagery of a desert shrubland, we explore the feasibility of detecting LSP with respect to fractional vegetation cover, plant functional types, and VI uncertainty. We found that plants with distinct VI signals, such as deciduous shrubs with a high leaf area index, require at least 30-40\% fractional cover on the landscape to consistently detect pixel level phenology with satellite remote sensing. Evergreen plants, which have lower VI amplitude between dormant and growing seasons, require considerably higher cover and can have undetectable phenology even with 100\% vegetation cover. We also found that even with adequate cover, biases in phenological metrics can still exceed 20 days, and can never be 100\% accurate due to VI uncertainty from shadows, sensor view angle, and atmospheric interference. Many dryland areas do not have detectable LSP with the current suite of satellite based sensors. Our results showed the feasibility of dryland LSP studies using high-resolution UAV imagery, and highlighted important scale effects due to within canopy VI variation. Future sensors with sub-meter resolution will allow for identification of individual plants and are the best path forward for studying large scale phenological trends in drylands.

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