Vegetation Dynamics Research Articles

Reconciling Global Terrestrial Evapotranspiration Estimates From Multi‐Product Intercomparison and Evaluation

AbstractTerrestrial evapotranspiration (ET) is a vital process regulating the terrestrial water balance. However, significant uncertainties persist in global ET estimates. Focusing on the area between 60°, we performed an intercomparison of 90 state‐of‐the‐art ET products from 1980 to 2014. These products were obtained from various sources or methods and were grouped into six categories: remote sensing, reanalysis, land surface models, climate models, machine learning methods, and ensemble estimates. It is shown that global ET magnitudes of categories differ considerably, with averages ranging from 518.4 to 706.3 mm yr−1. Spatial patterns are generally consistent but with significant divergence in tropical rainforests. Global trends are mildly positive or negative (−0.10 to 0.37 mm yr−2) depending on categories but with distinct spatial variability. Evaluation against site measurements reveals various performances across land cover types; the ideal point error values range from 0.45 to 0.83, with wetlands performing the worst and open shrublands the best. Using the three‐cornered hat method, there are spatial differences in ET uncertainty, with lower uncertainty for ensemble estimates, showing less than 15% relative uncertainty in most areas. The best global ET data set varies depending on the intended use and study region. Distinct spatial patterns of controlling factors across categories have been identified, with precipitation driving arid and semi‐arid regions and leaf area index dominating tropical regions. It is suggested to include advancing precipitation inputs, incorporate vegetation dynamics, and employ hybrid modeling in future ET estimates. Constraining estimates using complementary data and robust theoretical frameworks can enhance credibility in ET estimation.

Quantitative contributions of climate change and human activities to vegetation dynamics in the Zoige Plateau from 2001 to 2020

Quantitative contributions of climate change and human activities to vegetation dynamics in the Zoige Plateau from 2001 to 2020

A greater negative impact of future climate change on vegetation in Central Asia: Evidence from trajectory/pattern analysis

In the context of global warming, vegetation changes exhibit various patterns, yet previous studies have focused primarily on monotonic changes, often overlooking the complexity and diversity of multiple change processes. Therefore, it is crucial to further explore vegetation dynamics and diverse change trajectories in this region under future climate scenarios to obtain a more comprehensive understanding of local ecosystem evolution. In this study, we established an integrated machine learning prediction framework and a vegetation change trajectory recognition framework to predict the dynamics of vegetation in Central Asia under future climate change scenarios and identify its change trajectories, thus revealing the potential impacts of future climate change on vegetation in the region. The findings suggest that various future climate scenarios will negatively affect most vegetation in Central Asia, with vegetation change intensity increasing with increasing emission trajectories. Analyses of different time scales and trend variations consistently revealed more pronounced downward trends. Vegetation change trajectory analysis revealed that most vegetation has undergone nonlinear and dramatic changes, with negative changes outnumbering positive changes and curve changes outnumbering abrupt changes. Under the highest emission scenario (SSP5-8.5), the abrupt vegetation changes and curve changes are 1.7 times and 1.3 times greater, respectively, than those under the SSP1-2.6 scenario. When transitioning from lower emission pathways (SSP1-2.6, SSP2-4.5) to higher emission pathways (SSP3-7.0, SSP5-8.5), the vegetation change trajectories shift from neutral and negative curve changes to abrupt negative changes. Across climate scenarios, the key climate factors influencing vegetation changes are mostly evapotranspiration and soil moisture, with temperature and relative humidity exerting relatively minor effects. Our study reveals the negative response of vegetation in Central Asia to climate change from the perspective of vegetation dynamics and change trajectories, providing a scientific basis for the development of effective ecological protection and climate adaptation strategies.

Development of a new indicator for identifying vegetation destruction events using remote sensing data

Frequent climate change and intense anthropogenic activity increase the risk of vegetation destruction. Remote sensing technology, known for its timely observations and wide coverage, is a crucial tool for monitoring vegetation growth. However, accurately detecting vegetation destruction events remains challenging due to their spectral diversity, particularly in complex environments. Existing spectral indices (VIs) have limitations in effectively capturing vegetation dynamics as they are only sensitive to specific physiological parameters of vegetation, such as foliage, canopy, or water content, and are prone to background interference. To address this issue, we proposed the Slope Vegetation Index (SVI) based on Sentinel-2 imagery and PROSAIL model simulation data. Five representative VIs were selected for comprehensive comparison. The results showed that, compared with other VIs, SVI had the highest sensitivity to vegetation physiological parameters, with a correlation coefficient (R2) greater than 0.98. SVI performed best across all vegetation change scenes, with producer accuracy (PA), user accuracy (UA), and F1 score all exceeding 0.90. SVI proved effective in detecting various vegetation destruction events, including logging, insect infestation, landslides, and wildfires. Moreover, SVI was suitable for Landsat-8/9 imagery, achieving an F1 score of over 0.89. Overall, SVI is an effective and robust vegetation monitoring index, offering valuable insights for vegetation resource management and post-disaster ecological restoration.

Combination of plant species and water depth enhance soil quality in near-natural restoration of reclaimed wetland

Plant introduction and hydrological management are essential strategies for near-natural wetland restoration. However, the combined effects of plant species and water depth on soil quality restoration remain poorly understood. The wetland ecosystem is crucial for Earth ecosystem health and sustainable development, but it faces challenges due to environmental change and human activities leading to soil quality degradation. In this study, we conducted a five-year near-natural restoration experiment covering approximately 2071 m2 area in the Changbai Mountains region of northeastern China to assess the impact of plant species and water depth combinations on soil quality dynamics in reclaimed wetlands. Through an ecological engineering project, a meticulous controlled experiment was implemented to investigate the impact of different plant species and water depth combinations on soil quality in near-naturally restored wetlands. Over the five-year restoration period, we observed significant improvements in soil quality indicators, including pH, bulk density, soil organic carbon content, and labile organic carbon fractions. Soil pH and bulk density both showed a decreasing trend, with notable variations influenced by the combination of plant species and water depth. Particularly significant drops were observed in wetlands where Lythrum salicaria L. was introduced at 10 cm water depth and Iris wilsonii C. H. Wright was introduced at 30 cm water depth. Meanwhile, soil organic carbon content also appeared optimal restoration effects in the aforementioned combinations, highlighting the regulatory effect of these combinations on soil quality regulation. Linear regression modeling demonstrated a significant positive correlation between soil organic carbon and both above-ground and below-ground biomass, highlighting the interplay between vegetation dynamics and soil quality restoration. Our study provides valuable insights into the complex dynamics of soil quality restoration in reclaimed wetlands and underscores the importance of considering plant species-water depth combinations in restoration planning. By understanding these dynamics, restoration practitioners can make informed decisions to enhance the sustainability of wetland ecosystems and their invaluable ecological services.

Increasing Sensitivity of Tree Radial Growth to Precipitation

AbstractThe sensitivity of tree growth to precipitation regulates their responses to drought, and is a crucial metric for predicting ecosystem dynamics and vulnerability. Sensitivity may be changing with continuing climate change, yet a comprehensive assessment of its change is still lacking. We utilized tree ring measurements from 3,044 sites, climate data and CO2 concentrations obtained from monitoring stations, combined with dynamic global vegetation models to investigate spatiotemporal changes in the sensitivity over the past century. We observed an increasing sensitivity since around 1950. This increased sensitivity was particularly pronounced in arid biomes due to the combined effect of increased precipitation and elevated CO2. While elevated CO2 reduced the sensitivity of the humid regions, the intensified water pressure caused by decreased precipitation still increased the sensitivity. Our findings suggest an escalating vulnerability of tree growth to precipitation change, which may increase the risk of tree mortality under future intensified drought.

Impact of the extreme 2015-16 El Niño climate event on forest and savanna tree species of the Amazonia-Cerrado transition

Extreme drought events, driven by the El Niño Southern Oscillation (ENSO), are linked to increased tree mortality and alterations in vegetation structure, dynamics, and floristic composition in tropical forests. Existing analyses, primarily focusing on Africa, Central America, and Amazonia, overlook the floristic impacts on biome transitions. This study evaluates the profound effects of the severe 2015/2016 ENSO event on tree density and floristic composition in the critical transition zone between Amazonia and Cerrado, South America's largest biomes. Our findings not only document significant biodiversity loss but also offer insights into species resilience, guiding conservation strategies under changing climate conditions. We inventoried long-term plots before and after the extreme drought event, sampling 12,465 individuals from 526 species, 224 genera, and 65 families, in Open Ombrophilous Forest (OF), Seasonal Forest (SF), Cerradão (CD), and Typical Cerrado (TC). We document the disappearance from our plots of 97 species after the ENSO, with only 61 new species being recorded. The total loss of individuals across the transition zone was almost 10 %. The SF and CD forest plots showed the greatest replacements, species losses, and reductions in tree density. Their markedly seasonal baseline climate probably drove these changes. In most phytophysiognomies, there was an increase in pioneer species and drier environment habitat specialist species, indicating that although many species are vulnerable to extreme climate events, others benefit, especially those with a short life cycle. We found that the vegetation of the Amazonia-Cerrado transition overall is vulnerable to climate anomalies, with widespread loss of tree density and change in floristic composition. Our study also provides a species-by-species list of the most vulnerable and resistant trees which helps point to overall climate change vulnerabilities and assist with initiatives to recover degraded areas.

Impact of native vegetation and soil moisture dynamics on evapotranspiration in green roof systems

Evapotranspiration (ET) is an important water budget term for understanding the recovery of stormwater retention in green roof systems (GRs). However, ET evaluations, particularly in full-scale GRs, remain challenging. This study investigated ET dynamics within a GR in the City of Pittsburgh, USA, using a water balance based on continuously monitored soil moisture from moisture sensors over 15 months. Results suggest under well-watered soil conditions, daily moisture loss correlated with solar radiation, temperature, and humidity, in decreasing order of correlation strength, while wind speed had limited effects. Compared to sensor-informed moisture loss (using moisture-based water balance), the Hargreaves and FAO-56 Penman-Monteith equations predicted cumulative ET that was 1.8 and 2.1 times higher, respectively. When soil moisture declined and approached the temporary wilting points, a noticeable reduction in daily moisture loss was observed. This suggests the necessity of using a water stress coefficient alongside a crop coefficient to represent actual ET based on FAO-56 Penman–Monteith estimates. Seasonal crop coefficients from dominant native plant species present at our monitored location, eastern bluestar (Amsonia tabernaemontana) and creeping woodsorrel (Oxalis corniculata), had mean values of 0.48, 0.62, and 0.65 for fall, spring, and summer, respectively. The impact of water stress on ET could be characterized by a linear relationship with moisture content. Our results highlight the importance of soil moisture in regulating ET processes and demonstrate the utility of soil moisture data for evaluating ET in GRs and informing irrigation practices.

Improved water use efficiency of vegetation due to carbon fertilization not translating to increased soil moisture in India

Soil moisture (SM) plays a critical role in land–atmosphere interaction. Literature shows that the CO2 fertilization effect (CFE) governs vegetation dynamics and its interactions with the atmosphere. However, the impacts of changing vegetation properties due to CFE, on SM, specifically in India, remains unexplored. Comparing Land-hist (observed CO2 concentration) and Land-cCO2 (constant preindustrial CO2 concentration) simulations with the same meteorological forcings from the Land Use Model Inter-comparison Project (LUMIP), we found that changing vegetation due to CFE impacts SM following two pathways. Enhanced water use efficiency (WUE) due to CFE seeks to ameliorate SM by regulating transpiration. Conversely, elevated CO2 increases leaf area index and plant water use, ultimately leading to a decrease in SM due to the combined impacts of CFE in India. This reduction is most prominent in arid regions, where we observe a decline in SM particularly during dry periods. Our study highlights the need to consider plant physiology in land surface modeling under increased CO2 concentration.

Spatial and Temporal Dynamics in Vegetation Greenness and Its Response to Climate Change in the Tarim River Basin, China

Vegetation in ecologically sensitive regions has experienced significant alterations due to global climate change. The underlying mechanisms remain somewhat obscure owing to the spatial heterogeneity of influencing factors, particularly in the Tarim River Basin (TRB) in China. Therefore, this study targets the TRB, analyzing the spatial and temporal dynamics of vegetation greenness and its climatic determinants across multiple spatial scales. Utilizing Normalized Difference Vegetation Index (NDVI) data, vegetation greenness trends over the past 23 years were assessed, with future projections based on the Hurst exponent. Partial correlation and multiple linear regression analyses were employed to correlate NDVI with temperature (TMP), precipitation (PRE), and potential evapotranspiration (PET), elucidating NDVI’s response to climatic variations. Results revealed that from 2000 to 2022, 90.1% of the TRB exhibited an increase in NDVI, with a significant overall trend of 0.032/decade (p < 0.01). The difference in NDVI change across sub-basins and vegetation types highlighted the spatial disparity in greening. Notable greening predominantly occurred near rivers at lower elevations and in extensive cropland areas, with projections indicating continued greening in some regions. Conversely, future trends mainly suggested a shift towards browning, particularly in higher-elevation areas with minimal human influence. From 2000 to 2022, the TRB experienced a gradual increase in TMP, PRE, and PET. The latter two factors were significantly correlated with NDVI, indicating their substantial role in greening. However, vegetation sensitivity to climate change varied across sub-basins, vegetation types, and elevations, likely due to differences in plant characteristics, hydrothermal conditions, and human disturbances. Despite climate change influencing vegetation dynamics in 51.5% of the TRB, its impact accounted for only 25% of the total NDVI trend. These findings enhance the understanding of vegetation ecosystems in arid regions and provide a scientific basis for developing ecological protection strategies in the TRB.

Evolution and Mechanism Analysis of Terrestrial Ecosystems in China with Respect to Gross Primary Productivity

The gross primary productivity (GPP) of vegetation stores atmospheric carbon dioxide as organic compounds through photosynthesis. Its spatial heterogeneity is primarily influenced by the carbon uptake period (CUP) and maximum photosynthetic productivity (GPPmax). Grassland, cropland, and forest are crucial components of China’s terrestrial ecosystems and are strongly influenced by the seasonal climate. However, it remains unclear whether the evolutionary characteristics of GPP are attributable to physiology or phenology. In this study, terrestrial ecosystem models and remote sensing observations of multi-source GPP data were utilized to quantitatively analyze the spatio-temporal dynamics from 1982 to 2018. We found that GPP exhibited a significant upward trend in most areas of China’s terrestrial ecosystems over the past four decades. Over 60% of Chinese grassland and over 50% of its cropland and forest exhibited a positive growth trend. The average annual GPP growth rates were 0.23 to 3.16 g C m−2 year−1 for grassland, 0.40 to 7.32 g C m−2 year−1 for cropland, and 0.67 to 7.81 g C m−2 year−1 for forest. GPPmax also indicated that the overall growth rate was above 1 g C m−2 year−1 in most regions of China. The spatial trend pattern of GPPmax closely mirrored that of GPP, although local vegetation dynamics remain uncertain. The partial correlation analysis results indicated that GPPmax controlled the interannual GPP changes in most of the terrestrial ecosystems in China. This is particularly evident in grassland, where more than 99% of the interannual variation in GPP is controlled by GPPmax. In the context of rapid global change, our study provides an accurate assessment of the long-term dynamics of GPP and the factors that regulate interannual variability across China’s terrestrial ecosystems. This is helpful for estimating and predicting the carbon budget of China’s terrestrial ecosystems.

Revisiting evapotranspiration inputs in eco-hydrological modeling for climate change assessment

Evapotranspiration (ET) is an essential variable linking hydrological and ecological processes and is typically modeled as a function of potential evapotranspiration and soil moisture in traditional hydrological models. However, commonly used empirical ET models typically do not recognize the underlying vegetation dynamics. This can have implications when models are extrapolated under future climate change. In this study, the traditional HYMOD-BVM (THV) eco-hydrological model is adopted as a benchmark model. A modified HYMOD-BVM (MHV) is developed using an actual ET substitute for the traditional PET input to consider vegetation dynamics under climate change. The THV and MHV models are compared to evaluate how streamflow (Q) and leaf area index (LAI) vary under future climate in the Florentine River (FR, energy-limited) catchment and Murray River (MR, water-limited) catchment in Australia. Six global climate models (GCMs) from the latest Coupled Model Intercomparison Project (CMIP6) are bias-corrected and employed in the calibrated THV and MHV models, and ensemble mean results are analyzed. Results suggest that the streamflow projected by the MHV model tends to be higher than that from the THV model, while LAI presents an opposite trend. The energy-limited catchment appears more susceptible to climate change whereas larger vegetation effects are seen in the water-limited catchment. Overall, our research highlights the effects of evapotranspiration on future climate change scenario analysis and prompts the need for the development of spatial and temporal continuously accurate ET models for both current and future climates.

Vegetation Dynamics and Driving Mechanisms Considering Time-Lag and Accumulation Effects: A Case Study of Hubao–Egyu Urban Agglomeration

Vegetation Dynamics and Driving Mechanisms Considering Time-Lag and Accumulation Effects: A Case Study of Hubao–Egyu Urban Agglomeration

Integrated nexus approach to assessing climate change impacts on grassland ecosystem dynamics: A case study of the grasslands in Tanzania

This study addresses the intricate interplay between climate, vegetation, and livestock dynamics in Tanzania within the Climate-Vegetation-Livestock (CVL) nexus through a quantitative assessment. By examining the temporal and spatial relationships between vegetation indices (NDVI, EVI, NPP) and key climatic variables (Precipitation, Temperature, Evapotranspiration) from 2009 to 2019, and projecting to 2050, this research aims to elucidate vegetation responses to climate change and its subsequent impacts on livestock. To this end, the relationship between the vegetation dynamics indicators (NDVI, NPP) and climate parameters is evaluated to quantify the vegetation response to climate change using statistical models. Next, an examination of multicollinearity is conducted to investigate potential interactions (nexus) between variables, incorporating the correlation among independent variables. Notably, the evaluation of performance and accuracy for the mentioned models is conducted through the cross-validation method and validation indices. Ultimately, the variation between projected NPP and NDVI (average for 2040–2060) and the present NPP and NDVI (average for 2009–2020) identifies the regions that are most likely susceptible, showcasing the vegetation cover's reaction to climate change in different emission scenarios. The results unveil significant spatio-temporal variations in vegetation dynamics influenced by climatic factors, where higher precipitation and temperatures correlate with increased vegetation health and productivity. The projected fluctuations in NDVI and NPP values indicate varying trends across different regions, with a general decrease in vegetation density and productivity from the northeast to the west under both RCP2.6 and RCP8.5 scenarios by 2050. This decline is attributed to anticipated changes in precipitation and temperature patterns driven by climate change. Furthermore, significant declines in vegetation density and productivity under emission scenarios, particularly in the southern regions compared to the present, suggest greater vulnerability to climate change impacts. This highlights the need for targeted mitigation strategies in these vulnerable areas. Meanwhile, northeast areas under both NDVI and NPP will remain unchanged across both climate scenarios. Moreover, analysis of livestock distribution maps indicates areas of vulnerability under climate change scenarios, with implications for future livestock management and agricultural practices. These findings underscore the importance of proactive planning and targeted interventions to enhance resilience and sustainable development in vulnerable regions, emphasizing the need for integrated approaches that consider the complex interactions between climate, vegetation, and livestock dynamics.

Region-scale decline in streamflow across New South Wales catchments

ABSTRACT Changing climate and its interactions with catchments may result in changes to water resources. This study examines the temporal trends in streamflow across New South Wales, Australia. Across 163 catchments with over 35 years of records up to September 2020, we used Mann-Kendall and Sen’s Slope methods to estimate trends in different flow indicators, including the annual, low and high flows, cease to flow, and the rainfall-–runoff relationship. Nearly all (160) catchments have decreasing trends in annual flow, with 62 of these being statistically significant, indicating an overall drying pattern. Most declines are 10–20% per decade relative to the mean annual flows of individual catchments. Trends in rainfall-–runoff relationship suggest that the flow declines are generally greater than expected with given rainfall, and likely due to region-scale processes such as groundwater and vegetation dynamics. Our finding has important implications for future water security for New South Wales and similar environments, such as planning for future reduction in water resources availability with likely increasing demands.

Influence of wild ungulates on the secondary succession of an Apennine silver fir forest after windthrow

Windstorms are natural factors in vegetation dynamics, but their intensity is increasing and undermines the forest resilience. Post-event interventions depend on forest types and management purposes. To promote mixed stands that are less susceptible to windthrow than monocultures, natural tree regeneration is usually recommended. However, wild ungulates attracted by the increased food supply in the new clearings can influence the secondary succession and slow down vegetation recovery. The impact of ungulate pressure on secondary successions in blowdown areas is still poorly known, especially in Mediterranean areas, which is particularly vulnerable to climate stressors. We investigated this topic using a monospecific silver fir (Abies alba) forest of artificial origin in the Apennines as a model system. The forest was left to natural succession after a severe windthrow in 2015, offering the opportunity to establish an ungulate exclosure experiment to analyse vegetation changes over six years. For the whole plant community, cover and height, α-diversity (species richness, Shannon and evenness indexes), and species composition were recorded yearly, together with tree seedling density, in open and fenced plots at increasing distances from the forest edge. Ecological and functional traits (proportion of light-demanding and forest specialists, endo-/epi-zoochorous species), and life-forms of the community samples were also analysed. Overall, we found that ungulates significantly influenced the dynamic trajectories of secondary succession. The effects on plant cover and diversity were negative and increased with distance from the forest edge. The presence of ungulates favoured generalist species and endozoochorous taxa. However, distance from the forest edge strongly reduced the latter effect. The average density of tree seedlings was overall high (ca. 10,000/ha), but it was strongly reduced by ungulates for three deciduous species and A. alba, the most browsed species. Natural recolonization after windthrow in Apennine pure silver fir stands may favour the formation of mixed, less susceptible forests, but the current ungulate pressure slows down this process, especially in the areas furthest from the forest edge.

Spatio-temporal remote sensing evaluation of drought impact on vegetation dynamics in Balochistan, Pakistan

Spatio-temporal remote sensing evaluation of drought impact on vegetation dynamics in Balochistan, Pakistan

Revealing the long-term impacts of plant invasion and reclamation on native saltmarsh vegetation in the Yangtze River estuary using multi-source time series remote sensing data

Understanding the long-term dynamics of saltmarsh vegetation and their driving factors is crucial for the restoration of degraded coastal wetlands. Reclamation and plant invasion, identified as the two most significant environmental contributors to saltmarsh vegetation degradation, profoundly influence the evolution of saltmarsh vegetation. However, the long-term impacts of reclamation and plant invasion on native saltmarsh vegetation remain unclear. This study utilized multi-source time series remote sensing data to quantify the long-term impacts of Spartina alterniflora invasion and reclamation on native saltmarsh vegetation in the Yangtze River estuary from 1985 to 2020. Unlike other studies, this study generated annual saltmarsh cover data using image composite, zoning classification, object-based phenology algorithm, and random forest algorithm, which largely addressed the problem that existing studies could not capture transient change and gradual change because of insufficient observation frequency. Results showed that: (1) Reclamation had resulted in a loss of 503.93 km2 of native saltmarsh vegetation from 1985 to 2020, including 286.16 km2 of Phragmites australis community and 217.77 km2 of Scirpus spp. community; Spartina alterniflora invasion had resulted in a loss of 78.96 km2 of native saltmarsh vegetation from 1985 to 2020, including 12.48 km2 of Phragmites australis community and 66.48 km2 of Scirpus spp. community; (2) Significant differences of spatial-temporal evolution patterns of native saltmarsh vegetation were observed under different degrees of Spartina alterniflora invasion and reclamation, including irrecoverable scenario under severe plant invasion and excessive reclamation, recoverable scenario under moderate degree of reclamation and plant invasion, and competitive scenario under plant invasion and without reclamation.; (3) From a long-term remote sensing perspective, spread limitation determined by reclamation intensity was a decisive factor in the evolution of Phragmites australis community in the study area, while interspecific competition between invasive Spartina alterniflora and Scirpus spp. determined the evolution of Scirpus spp. community. This study provides a theoretical basis and baseline for the protection strategies of native saltmarsh vegetation in the study area.

Vegetation dynamics 1946–2018 in an old‐growth conifer forest

We analysed ground vegetation in 250 plots in 2018 in the old‐growth Picea abies‐dominated forest Säby Västerskog, south‐east Sweden as a follow‐up of studies in 1946 and 1998 with the same layout of plots. The vegetation changes were not clearly directional: the species composition in 2018 was intermediate between that of 1946 and 1998, whereas in 1998 species richness was higher and with the unique presence of a number of species indicating small‐scale disturbances. Vaccinium myrtillus increased in cover since 1946 and Avenella flexuosa decreased. This goes against regional trends that have been attributed to nitrogen deposition. Regional changes are overshadowed by local dynamics.

Decorrelation rate and daily cycle in sub-daily time series of SAR coherence amplitude

A dataset of sub-daily C-band data, acquired with a ground-based synthetic aperture radar, has been used to study soil and vegetation dynamics during a complete growing season in a controlled agricultural test site. The data have been exploited to analyse the rate and sources of decorrelation in the scene, as well as the consequences of the observation conditions of a sub-daily satellite (with either low, medium or geosynchronous orbit): short revisit times, availability of multiple acquisitions during a single day, and shallow observations at some incidence angles. Repeat-pass coherence is found to be less affected by temporal decorrelation when the primary image is acquired during nighttime or the last hours predawn. Regarding the incidence angle, VV has increased sensitivity to certain phenological stages as the incidence angle increases. Additionally, a periodic oscillation on a sub-daily scale is observed when creating coherence time series with increasing temporal baseline. Factors which strongly contribute to these oscillations are the daily cycles of temperature, soil moisture and vegetation water dynamics.