More Like this

1. Plant Species Richness in Multiyear Wet and Dry Periods in the Chihuahuan Desert

   https://doi.org/10.3390/cli9080130  

   Peters, Debra P.; Savoy, Heather M.; Stillman, Susan; Huang, Haitao; Hudson, Amy R.; Sala, Osvaldo E.; Vivoni, Enrique R. (August 2021, Climate)

   null (Ed.)

   In drylands, most studies of extreme precipitation events examine effects of individual years or short-term events, yet multiyear periods (>3 y) are expected to have larger impacts on ecosystem dynamics. Our goal was to take advantage of a sequence of multiple long-term (4-y) periods (dry, wet, average) that occurred naturally within a 26-y time frame to examine responses of plant species richness to extreme rainfall in grasslands and shrublands of the Chihuahuan Desert. Our hypothesis was that richness would be related to rainfall amount, and similar in periods with similar amounts of rainfall. Breakpoint analyses of water-year precipitation showed five sequential periods (1993–2018): AVG1 (mean = 22 cm/y), DRY1 (mean = 18 cm/y), WET (mean = 30 cm/y), DRY2 (mean = 18 cm/y), and AVG2 (mean = 24 cm/y). Detailed analyses revealed changes in daily and seasonal metrics of precipitation over the course of the study: the amount of nongrowing season precipitation decreased since 1993, and summer growing season precipitation increased through time with a corresponding increase in frequency of extreme rainfall events. This increase in summer rainfall could explain the general loss in C3 species after the wet period at most locations through time. Total species richness in the wet period was among the highest in the five periods, with the deepest average storm depth in the summer and the fewest long duration (>45 day) dry intervals across all seasons. For other species-ecosystem combinations, two richness patterns were observed. Compared to AVG2, AVG1 had lower water-year precipitation yet more C3 species in upland grasslands, creosotebush, and mesquite shrublands, and more C4 perennial grasses in tarbush shrublands. AVG1 also had larger amounts of rainfall and more large storms in fall and spring with higher mean depths of storm and lower mean dry-day interval compared with AVG2. While DRY1 and DRY2 had the same amount of precipitation, DRY2 had more C4 species than DRY1 in creosote bush shrublands, and DRY1 had more C3 species than DRY2 in upland grasslands. Most differences in rainfall between these periods occurred in the summer. Legacy effects were observed for C3 species in upland grasslands where no significant change in richness occurred from DRY1 to WET compared with a 41% loss of species from the WET to DRY2 period. The opposite asymmetry pattern was found for C4 subdominant species in creosote bush and mesquite shrublands, where an increase in richness occurred from DRY1 to WET followed by no change in richness from WET to DRY2. Our results show that understanding plant biodiversity of Chihuahuan Desert landscapes as precipitation continues to change will require daily and seasonal metrics of rainfall within a wet-dry period paradigm, as well as a consideration of species traits (photosynthetic pathways, lifespan, morphologies). Understanding these relationships can provide insights into predicting species-level dynamics in drylands under a changing climate. 

   more » « less
2. Near-Surface and High-Resolution Satellite Time Series for Detecting Crop Phenology

   https://doi.org/10.3390/rs14091957  

   Diao, Chunyuan; Li, Geyang (May 2022, Remote Sensing)

   Detecting crop phenology with satellite time series is important to characterize agroecosystem energy-water-carbon fluxes, manage farming practices, and predict crop yields. Despite the advances in satellite-based crop phenological retrievals, interpreting those retrieval characteristics in the context of on-the-ground crop phenological events remains a long-standing hurdle. Over the recent years, the emergence of near-surface phenology cameras (e.g., PhenoCams), along with the satellite imagery of both high spatial and temporal resolutions (e.g., PlanetScope imagery), has largely facilitated direct comparisons of retrieved characteristics to visually observed crop stages for phenological interpretation and validation. The goal of this study is to systematically assess near-surface PhenoCams and high-resolution PlanetScope time series in reconciling sensor- and ground-based crop phenological characterizations. With two critical crop stages (i.e., crop emergence and maturity stages) as an example, we retrieved diverse phenological characteristics from both PhenoCam and PlanetScope imagery for a range of agricultural sites across the United States. The results showed that the curvature-based Greenup and Gu-based Upturn estimates showed good congruence with the visually observed crop emergence stage (RMSE about 1 week, bias about 0–9 days, and R square about 0.65–0.75). The threshold- and derivative-based End of greenness falling Season (i.e., EOS) estimates reconciled well with visual crop maturity observations (RMSE about 5–10 days, bias about 0–8 days, and R square about 0.6–0.75). The concordance among PlanetScope, PhenoCam, and visual phenology demonstrated the potential to interpret the fine-scale sensor-derived phenological characteristics in the context of physiologically well-characterized crop phenological events, which paved the way to develop formal protocols for bridging ground-satellite phenological characterization. 

   more » « less
3. Using Near-Infrared-Enabled Digital Repeat Photography to Track Structural and Physiological Phenology in Mediterranean Tree–Grass Ecosystems

   https://doi.org/10.3390/rs10081293  

   Luo, Yunpeng; El-Madany, Tarek S.; Filippa, Gianluca; Ma, Xuanlong; Ahrens, Bernhard; Carrara, Arnaud; Gonzalez-Cascon, Rosario; Cremonese, Edoardo; Galvagno, Marta; Hammer, Tiana W.; et al (August 2018, Remote Sensing)

   Tree–grass ecosystems are widely distributed. However, their phenology has not yet been fully characterized. The technique of repeated digital photographs for plant phenology monitoring (hereafter referred as PhenoCam) provide opportunities for long-term monitoring of plant phenology, and extracting phenological transition dates (PTDs, e.g., start of the growing season). Here, we aim to evaluate the utility of near-infrared-enabled PhenoCam for monitoring the phenology of structure (i.e., greenness) and physiology (i.e., gross primary productivity—GPP) at four tree–grass Mediterranean sites. We computed four vegetation indexes (VIs) from PhenoCams: (1) green chromatic coordinates (GCC), (2) normalized difference vegetation index (CamNDVI), (3) near-infrared reflectance of vegetation index (CamNIRv), and (4) ratio vegetation index (CamRVI). GPP is derived from eddy covariance flux tower measurement. Then, we extracted PTDs and their uncertainty from different VIs and GPP. The consistency between structural (VIs) and physiological (GPP) phenology was then evaluated. CamNIRv is best at representing the PTDs of GPP during the Green-up period, while CamNDVI is best during the Dry-down period. Moreover, CamNIRv outperforms the other VIs in tracking growing season length of GPP. In summary, the results show it is promising to track structural and physiology phenology of seasonally dry Mediterranean ecosystem using near-infrared-enabled PhenoCam. We suggest using multiple VIs to better represent the variation of GPP. 

   more » « less
4. A sequence of multiyear wet and dry periods provides opportunities for grass recovery and state change reversals

   https://doi.org/10.1002/ecm.1590  

   Peters, Debra P. C.; Savoy, Heather M. (September 2023, Ecological Monographs)

   Abstract Multiyear periods (≥4 years) of extreme rainfall are increasing in frequency as climate continues to change, yet there is little understanding of how rainfall amount and heterogeneity in biophysical properties affect state changes in a sequence of wet and dry periods. Our objective was to examine the importance of rainfall periods, their legacies, and vegetation and soil properties to either the persistence of woody plants or a shift toward perennial grass dominance and a state reversal. We examined a 28‐year record of rainfall consisting of a sequence of multiyear periods (average, dry, wet, dry, average) for four ecosystem types in the Jornada Basin. We analyzed relationships between above ground net primary production (ANPP) and rainfall for three plant functional groups that characterize alternative states (perennial grasses, other herbaceous plants, dominant shrubs). A multimodel comparison was used to determine the relative importance of rainfall, soil, and vegetation properties. For perennial grasses, the greatest mean ANPP in mesquite‐ and tarbush‐dominated shrublands occurred in the wet period and in the dry period following the wet period in grasslands. Legacy effects in grasslands were asymmetric, where the lowest production was found in a dry period following an average period, and the greatest production occurred in a dry period following a wet period. For other herbaceous plants, in contrast, the greatest ANPP occurred in the wet period. Mesquite was the only dominant shrub species with a significant positive response in the wet period. Rainfall amount was a poor predictor of ANPP for each functional group when data from all periods were combined. Initial herbaceous biomass at the plant scale, patch‐scale biomass, and soil texture at the landscape scale improved the predictive relationships of ANPP compared with rainfall alone. Under future climate, perennial grass production is expected to benefit the most from wet periods compared with other functional groups with continued high grass production in subsequent dry periods that can shift (desertified) shrublands toward grasslands. The continued dominance by shrubs will depend on the effects that rainfall has on perennial grasses and the sequence of high‐ and low‐rainfall periods rather than the direct effects of rainfall on shrub production. 

   more » « less
5. HP-LSP: A reference of land surface phenology from fused Harmonized Landsat and Sentinel-2 with PhenoCam data

   https://doi.org/10.1038/s41597-023-02605-1  

   Tran, Khuong H.; Zhang, Xiaoyang; Ye, Yongchang; Shen, Yu; Gao, Shuai; Liu, Yuxia; Richardson, Andrew (December 2023, Scientific Data)

   Abstract Land surface phenology (LSP) products are currently of large uncertainties due to cloud contaminations and other impacts in temporal satellite observations and they have been poorly validated because of the lack of spatially comparable ground measurements. This study provided a reference dataset of gap-free time series and phenological dates by fusing the Harmonized Landsat 8 and Sentinel-2 (HLS) observations with near-surface PhenoCam time series for 78 regions of 10 × 10 km²across ecosystems in North America during 2019 and 2020. The HLS-PhenoCam LSP (HP-LSP) reference dataset at 30 m pixels is composed of: (1) 3-day synthetic gap-free EVI2 (two-band Enhanced Vegetation Index) time series that are physically meaningful to monitor the vegetation development across heterogeneous levels, train models (e.g., machine learning) for land surface mapping, and extract phenometrics from various methods; and (2) four key phenological dates (accuracy ≤5 days) that are spatially continuous and scalable, which are applicable to validate various satellite-based phenology products (e.g., global MODIS/VIIRS LSP), develop phenological models, and analyze climate impacts on terrestrial ecosystems. 

   more » « less