Phenological Characterization of Desert Sky Island Vegetation Communities with Remotely Sensed and Climate Time Series Data

Using spectral indices as early warning signals of forest dieback: The case of drought-prone Pinus pinaster forests

Forest dieback processes linked to drought are expected to increase due to climate warming. Remotely sensed data offer several advantages over common field monitoring methods such as the ability to observe large areas on a systematic basis and monitoring their changes, making them increasingly used to assess changes in forest health. Here we aim to use a combined approximation of fieldwork and remote sensing to explore possible links between forest dieback and land surface phenological and trend variables derived from long Landsat time series. Forest dieback was evaluated in the field over 31 plots in a Mediterranean, xeric Pinus pinaster forest. Landsat 31-year time series of three greenness (EVI, NDVI, SAVI) and two wetness spectral indices (NMDI and TCW) were derived covering the period 1990-2020. Spectral indices from time series were decomposed into trend and seasonality using a Bayesian estimator while the relationships of the phenological and trend variables among levels of damage were assessed using linear and additive mixed models. We have not found any statistical pieces of evidence of extension or shortening patterns for the length of the phenological season over the examined 31-year period. Our results indicate that the dieback process was mainly related to the trend component of the spectral indices series whereas the phenological metrics were not related to forest dieback. We also found that plots with more dying or damaged trees displayed lower spectral indices trends after a severe drought event in the middle of the 1990s, which confirms the Landsat-derived spectral indices as indicators of early-warning signals. Drops in trends occurred earlier for wetness indices rather than for greenness indices which suggests that the former could be more appropriate for dieback detection, i.e. they could be used as early warning signals of impending loss of tree vigor.

Savannah Phenological Dynamics Reveal Spatio-Temporal Landscape Heterogeneity in Karamoja Sub-region, Uganda

Phenological properties are critical in understanding global environmental change patterns. This study analyzed phenological dynamics in a savannah dominated semi-arid environment of Uganda. We used moderate-resolution imaging spectroradiometer normalized difference vegetation index (MODIS NDVI) imagery. TIMESAT program was used to analyse the imagery to determine key phenological metrics; onset of greenness (OGT), onset of greenness value, end of greenness time (EGT), end of greenness value, maximum NDVI, time of maximum NDVI, duration of greenup (DOG) and range of normalized difference vegetation index (RNDVI). Results showed that thicket and shrubs had the earliest OGT on day 85 ± 14, EGT on day 244 ± 32 and a DOG of 158 ± 25 days. Woodland had the highest NDVI value for maximum NDVI, OGT, EGT, and RNDVI. In the bushland, OGT occurs on average around day 90 ± 11, EGT on day 255 ± 33 with a DOG of 163 ± 36 days. The grassland showed that OGT occurs on day 96 ± 13, EGT on day 252 ± 36 with a total DOG of 156 ± 33 days. Early photosynthesis activity was observed in central to eastern Karamoja in the districts of Moroto and Kotido. There was a positive relationship between rainfall and NDVI across all vegetation cover types as well as between phenological parameters and season dynamics. Vegetation senescence in the sub-region occurs around August to mid-September (day 244–253). The varied phenophases observed in the sub-region reveal an inherent landscape heterogeneity that is beneficial to extensive pastoral livestock production. Continuous monitoring of savannah phenological patterns in the sub-region is required to decipher landscape ecosystem processes and functioning.

Water Addition Prolonged the Length of the Growing Season of the Desert Shrub Nitraria tangutorum in a Temperate Desert

Climate models often predict that more extreme precipitation events will occur in arid and semiarid regions, where plant phenology is particularly sensitive to precipitation changes. To understand how increases in precipitation affect plant phenology, this study conducted a manipulative field experiment in a desert ecosystem of northwest China. In this study, a long-term in situ water addition experiment was conducted in a temperate desert in northwestern China. The following five treatments were used: natural rain plus an additional 0, 25, 50, 75, and 100% of the local mean annual precipitation. A series of phenological events, including leaf unfolding (onset, 30%, 50%, and end of leaf unfolding), cessation of new branch elongation (30, 50, and 90%), and leaf coloration (80% of leaves turned yellow), of the locally dominant shrub Nitraria tangutorum were observed from 2012 to 2018. The results showed that on average, over the seven-year-study and in all treatments water addition treatments advanced the spring phenology (30% of leaf unfolding) by 1.29-3.00 days, but delayed the autumn phenology (80% of leaves turned yellow) by 1.18-11.82 days. Therefore, the length of the growing season was prolonged by 2.11-13.68 days, and autumn phenology contributed more than spring phenology. In addition, water addition treatments delayed the cessation of new branch elongation (90%) by 5.82-12.61 days, and nonlinear relationships were found between the leaves yellowing (80% of leaves) and the amount of watering. Linear relationships were found between the cessation of new branch elongation (90%), the length of the growing season, and amount of water addition. The two response patterns to water increase indicated that predictions of phenological events in the future should not be based on one trend only.

Using Hidden Markov Models for Land Surface Phenology: An Evaluation Across a Range of Land Cover Types in Southeast Spain

Land Surface Phenology (LSP) metrics are increasingly being used as indicators of climate change impacts in ecosystems. For this purpose, it is necessary to use methods that can be applied to large areas with different types of vegetation, including vulnerable semiarid ecosystems that exhibit high spatial variability and low signal-to-noise ratio in seasonality. In this work, we evaluated the use of hidden Markov models (HMM) to extract phenological parameters from Moderate Resolution Imaging Spectroradiometer (MODIS) derived Normalized Difference Vegetation Index (NDVI). We analyzed NDVI time-series data for the period 2000–2018 across a range of land cover types in Southeast Spain, including rice croplands, shrublands, mixed pine forests, and semiarid steppes. Start of Season (SOS) and End of Season (EOS) metrics derived from HMM were compared with those obtained using well-established smoothing methods. When a clear and consistent seasonal variation was present, as was the case in the rice croplands, and when adjusting average curves, the smoothing methods performed as well as expected, with HMM providing consistent results. When spatial variability was high and seasonality was less clearly defined, as in the semiarid shrublands and steppe, the performance of the smoothing methods degraded. In these cases, the results from HMM were also less consistent, yet they were able to provide pixel-wise estimations of the metrics even when comparison methods did not.

Phenology Response to Climatic Dynamic across China’s Grasslands from 1985 to 2010

Because the dynamics of phenology in response to climate change may be diverse in different grasslands, quantifying how climate change influences plant growth in different grasslands across northern China should be particularly informative. In this study, we explored the spatiotemporal variation of the phenology (start of the growing season [SOS], peak of the growing season [POS], end of the growing season [EOS], and length of the growing season [LOS]) across China’s grasslands using a dataset of the GIMMS3g normalized difference vegetation index (NDVI, 1985–2010), and determined the effects of the annual mean temperature (AMT) and annual mean precipitation (AMP) on the significantly changed phenology. We found that the SOS, POS, and EOS advanced at the rates of 0.54 days/year, 0.64 days/year, and 0.65 days/year, respectively; the LOS was shortened at a rate of 0.62 days/year across China’s grasslands. Additionally, the AMT combined with the AMP explained the different rates (ER) for the significantly dynamic SOS in the meadow steppe (R2 = 0.26, p = 0.007, ER = 12.65%) and typical steppe (R2 = 0.28, p = 0.005, ER = 32.52%); the EOS in the alpine steppe (R2 = 0.16, p < 0.05, ER = 6.22%); and the LOS in the alpine (R2 = 0.20, p < 0.05, ER = 6.06%), meadow (R2 = 0.18, p < 0.05, ER = 16.69%) and typical (R2 = 0.18, p < 0.05, ER = 19.58%) steppes. Our findings demonstrated that the plant phenology in different grasslands presented discrepant dynamic patterns, highlighting the fact that climate change has played an important role in the variation of the plant phenology across China’s grasslands, and suggested that the variation and relationships between the climatic factors and phenology in different grasslands should be explored further in the future.

Relationships among phenology, climate and biomass across subtropical forests in Argentina

Phenology is a key ecosystem process that reflects climate–vegetation functioning, and is an indicator of global environmental changes. Recently, it has been suggested that land-use change and timber extraction promote differences in forest phenology. We use remote-sensing data to describe regional leaf phenological patterns in combination with field data from 131 plots in old-growth and disturbed forests distributed over subtropical forests of Argentina (54–65°W). We assessed how climate is related to phenological patterns, and analysed how changes in forest structural characteristics such as stock of above-ground biomass relate to the observed phenological signals across the gradient. We found that the first three axes of a principal component analysis explained 85% of the variation in phenological metrics across subtropical forests, ordering plots mainly along indicators of seasonality and productivity. At the regional scale, the relative importance of forest biomass in explaining variation in phenological patterns was about 15%. Climate showed the highest relative importance, with temperature and rainfall explaining Enhanced Vegetation Index metrics related to seasonality and productivity patterns (27% and 47%, respectively). Within forest types, climate explains the major fraction of variation in phenological patterns, suggesting that forest function may be particularly sensitive to climate change. We found that forest biomass contributed to explaining a proportion of leaf phenological variation within three of the five forest types studied, and this may be related to changes in species composition, probably as a result of forest use.

Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile

Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems. Normalized difference vegetation index time series (2000-2013) data from the moderate resolution imaging spectroradiometer (MODIS) was processed to monitor the trends and patterns of vegetation productivity and phenology observed over the last decade. An analysis of the relationship between (i) vegetation productivity and (ii) precipitation and temperature data for representative natural land-use cover classes was made. Using these data and ground measurements, productivity estimates were projected for two climate change scenarios (RCP2.6 and RCP8.5) at two altitudinal levels. Results showed negative trends of vegetation productivity below 2000 m a.s.l. and positive trends for higher elevations. Phenology analysis suggested that mountainous ecosystems were starting their growing period earlier in the season, coinciding with a decreased productivity peak during the growing season. The coastal shrubland/grassland land cover class had a significant positive relation with rainfall and a significant negative relation with temperature, suggesting that these ecosystems are vulnerable to climate change. Future productivity projections indicate that under an RCP8.5 climate change scenario, productivity could decline by 12% in the period of 2060-2100, leading to a severe vegetation degradation at lower altitudes and in drier areas.

Land Use and Environmental Variability Impacts on the Phenology of Arid Agro-Ecosystems

The overexploitation of water resources in arid environments often results in abandonment of large extensions of agricultural lands, which may (1) modify phenological trends, and (2) alter the sensitivity of specific phenophases to environmental triggers. In Mexico, current governmental policies subsidize restoration efforts, to address ecological degradation caused by abandonments; however, there is a need for new approaches to assess their effectiveness. Addressing this, we explore a method to monitor and assess (1) land surface phenology trends in arid agro-ecosystems, and (2) the effect of climatic factors and restoration treatments on the phenology of abandoned agricultural fields. We used 16-day normalized difference vegetation index composites from the moderate resolution imaging spectroradiometer from 2000 to 2009 to derive seasonal phenometrics. We then derived phenoclimatic variables and land cover thematic maps, to serve as a set of independent factors that influence vegetation phenology. We conducted a multivariate analysis of variance to analyze phenological trends among land cover types, and developed multiple linear regression models to assess influential climatic factors driving phenology per land cover analyzed. Our results suggest that the start and length of the growing season had different responses to environmental factors depending on land cover type. Our analysis also suggests possible establishment of arid adapted species (from surrounding ecosystems) in abandoned fields with longer times since abandonment. Using this approach, we were able increase our understanding on how climatic factors influence phenology on degraded arid agro-ecosystems, and how this systems evolve after disturbance.

Solar energy development and aquatic ecosystems in the southwestern United States: potential impacts, mitigation, and research needs

The cumulative impacts of utility-scale solar energy facilities on aquatic ecosystems in the Southwestern United States are of concern, considering the many existing regional anthropogenic stressors. We review the potential impacts of solar energy development on aquatic habitat and biota. The greatest potential for impacts is related to the loss, fragmentation, or prolonged drying of ephemeral water bodies and drainage networks resulting from the loss of desert washes within the construction footprint of the facility. Groundwater-dependent aquatic habitat may also be affected by operational groundwater withdrawal in the case of water-intensive solar technologies. Solar panels have also been found to attract aquatic insects and waterbirds, potentially resulting in mortality. Avoiding construction activity near perennial and intermittent surface waters is the primary means of reducing impacts on aquatic habitats, followed by measures to minimize erosion, sedimentation, and contaminant inputs into waterways. Currently, significant data gaps make solar facility impact assessment and mitigation more difficult. Examples include the need for more regional and site-specific studies of surface-groundwater connectivity, more detailed maps of regional stream networks and riparian vegetation corridors, as well as surveys of the aquatic communities inhabiting ephemeral streams. In addition, because they often lack regulatory protection, there is also a need to develop valuation criteria for ephemeral waters based on their ecological and hydrologic function within the landscape. By addressing these research needs, we can achieve the goal of greater reliance on solar energy, while at the same time minimizing impacts on desert ecosystems.