Variation In Phenology Research Articles

Unraveling the drivers and impacts of leaf phenological diversity in a subtropical forest: A fine-scale analysis using PlanetScope CubeSats.

Leaf phenology variations within plant communities shape community assemblages and influence ecosystem properties and services. However, questions remain regarding quantification, drivers, and productivity impacts of intra-site leaf phenological diversity. With a 50-ha subtropical forest plot in China's Heishiding Provincial Nature Reserve (part of the global ForestGEO network) as a testbed, we gathered a unique dataset combining ground-derived abiotic (topography, soil) and biotic (taxonomic diversity, functional diversity, functional traits) factors. We investigated drivers underlying leaf phenological diversity extracted from high-resolution PlanetScope data, and its influence on aboveground biomass (AGB) using structural equation modeling (SEM). Our results reveal considerable fine-scale leaf phenological diversity across the subtropical forest landscape. This diversity is directly and indirectly influenced by abiotic and biotic factors (e.g. slope, soil, traits, taxonomic diversity; r2 = 0.43). While a notable bivariate relationship between AGB and leaf phenological diversity was identified (r = -0.24, P < 0.05), this relationship did not hold in SEM analysis after considering interactions with other biotic and abiotic factors (P > 0.05). These findings unveil the underlying mechanism regulating intra-site leaf phenological diversity. While leaf phenology is known to be associated with ecosystem properties, our findings confirm that AGB is primarily influenced by functional trait composition and taxonomic diversity rather than leaf phenological diversity.

Long-term declines in chlorophyll a and variable phenology revealed by a 60-year estuarine plankton time series

Long-term ecological time series provide a unique perspective on the emergent properties of ecosystems. In aquatic systems, phytoplankton form the base of the food web and their biomass, measured as the concentration of the photosynthetic pigment chlorophyll a (chl a), is an indicator of ecosystem quality. We analyzed temporal trends in chl a from the Long-Term Plankton Time Series in Narragansett Bay, Rhode Island, USA, a temperate estuary experiencing long-term warming and changing anthropogenic nutrient inputs. Dynamic linear models were used to impute and model environmental variables (1959 to 2019) and chl a concentrations (1968 to 2019). A long-term chl a decrease was observed with an average decline in the cumulative annual chl a concentration of 49% and a marked decline of 57% in winter-spring bloom magnitude. The long-term decline in chl a concentration was directly and indirectly associated with multiple environmental factors that are impacted by climate change (e.g., warming temperatures, water column stratification, reduced nutrient concentrations) indicating the importance of accounting for regional climate change effects in ecosystem-based management. Analysis of seasonal phenology revealed that the winter-spring bloom occurred earlier, at a rate of 4.9 ± 2.8 d decade-1. Finally, the high degree of temporal variation in phytoplankton biomass observed in Narragansett Bay appears common among estuaries, coasts, and open oceans. The commonality among these marine ecosystems highlights the need to maintain a robust set of phytoplankton time series in the coming decades to improve signal-to-noise ratios and identify trends in these highly variable environments.

Seasonal Scale Climatic Factors on Grassland Phenology in Arid and Semi-Arid Zones

Influenced by climate change, significant alterations in vegetation phenology have been observed globally. Grassland phenology is highly sensitive to climate change. However, research on the variations in grassland phenology and its responses to seasonal climatic changes in arid and semi-arid regions remains scarce. This study, utilizing Solar-Induced Chlorophyll Fluorescence (SIF) data, meteorological station data, and grassland type data, employs trend analysis and time series analysis to explore the trends of seasonal climatic variability and the sensitivity response of grassland phenology in Xinjiang to seasonal climates. The findings reveal the following: (1) The region experiences more pronounced warming in winter and spring than in summer and autumn, with ground temperature increments outpacing those of air temperatures. The summer season registers the peak in precipitation volume and rate of increase, where mountainous zones accrue more rainfall compared to basins and plains. The distribution of sunshine duration is characterized by higher values in eastern areas than in the west and more in the plains than in mountainous regions, potentially due to escalating cloudiness, which has contributed to a diminishing trend in sunshine hours across Xinjiang over the past 20 years. (2) Over the past two decades, the perennial greening phase of Xinjiang grasslands has predominantly occurred in early May, showing an overall trend of occurring earlier by approximately 5.47 days per decade, while the yellowing phase mainly occurs at the end of September and the beginning of October, demonstrating a delaying trend (6.61 days/decade). The average length of the growing season is 145 days, generally showing a slightly increasing trend (11.97 days/decade). (3) In spring, the rise in air and ground temperatures, along with increased sunshine duration, all promote grassland growth, leading to an earlier greening phase. Conversely, in autumn, increases in air temperature, ground temperature, and sunshine duration can inhibit grassland growth, resulting in an earlier yellowing phase. Increased precipitation in summer and autumn can delay the yellowing phase and extend the length of the grassland growing season. This research provides new insights into the factors influencing large-scale grassland phenology and offers references for grassland adaptation to future climate changes.

Genetics of phenological development and implications for seed yield in lentil.

Understanding phenology, its genetics and agronomic consequences, is critical for crop adaptation. Here we aim to (i) characterize lentil response to photoperiod with a focus on five loci: the lentil ELF3 orthologue Sn, two loci linked to clusters of lentil FT orthologues, and two loci without candidates in chromosomes 2 and 5 (Experiment 1: 36 lines, short and long days in a phytotron), and (ii) establish the phenology-yield relationship (Experiment 2: 25 lines, 11 field environments). A vintage perspective, where we quantify time trends in phenotype over three decades of breeding, links both experiments. Yield increased linearly from older to newer varieties at 29 kg ha-1 year-1 or 1.5% year-1, correlated negatively with flowering time in both winter- and summer-rainfall regimes, and decoupled from biomass in favourable environments. Time to flowering shortened from older to newer varieties at -0.56% year-1 in the field, and -0.42% year-1 (short days) and -0.99% year-1 (long days) in the phytotron. Early-flowering lines of diverse origin carried multiple early alleles for the five loci, indicating that at least some of these loci affect phenology additively. Current germplasm primarily features the early-flowering haplotype for an FTb cluster region, hence the potential to increase phenological diversity with yield implications.

Making temporal dynamics relevant: The role of macrophytes in the phenological complexity of a shallow freshwater lake

AbstractA multidisciplinary approach demonstrates how submerged macrophytes generate high phenological variability in Hungary's Lake Balaton. A 239‐month time series of water chlorophyll indices derived from Landsat 7 imagery from 1999 to 2019 was used. These data facilitated the generation of area‐based phenological patterns, which allowed an assessment of phenological variability by correlating chlorophyll index sequences with spatially adjacent values. The results showed that phenological variability was consistently low (below 5%) at the farthest points from the shore, indicating uniform phenological processes in the pelagic zone of Lake Balaton. Conversely, the littoral zone showed almost eight times higher variability, indicating increased diversity in shallow water areas. In particular, extensive macrophyte biomass datasets revealed a direct relationship between increased phenological variability in the littoral zone and macrophyte biomass (Spearman rank correlation: 0.893). This research highlights contrasting phenological patterns between phytoplankton and macrophyte communities, driven by different life cycles, and the possibility of effectively using satellite data to delineate phenological separation within lakes.

Drought shortens subtropical understory growing season by advancing leaf senescence.

Subtropical forests, recognized for their intricate vertical canopy stratification, exhibit high resistance to extreme drought. However, the response of leaf phenology to drought in the species-rich understory remains poorly understood. In this study, we constructed a digital camera system, amassing over 360,000 images through a 70% throughfall exclusion experiment, to explore the drought response of understory leaf phenology. The results revealed a significant advancement in understory leaf senescence phenology under drought, with 11.75 and 15.76 days for the start and end of the leaf-falling event, respectively. Pre-season temperature primarily regulated leaf development phenology, whereas soil water dominated the variability in leaf senescence phenology. Under drought conditions, temperature sensitivities for the end of leaf emergence decreased from -13.72 to -11.06 days °C-1, with insignificance observed for the start of leaf emergence. Consequently, drought treatment shortened both the length of the growing season (15.69 days) and the peak growth season (9.80 days) for understory plants. Moreover, this study identified diverse responses among intraspecies and interspecies to drought, particularly during the leaf development phase. These findings underscore the pivotal role of water availability in shaping understory phenology patterns, especially in subtropical forests.

Variability in intermediate predator hatching does not alter top-down effects of top predators

Variability in phenological shifts (seasonal changes in biological events) has become more common with climate change. As phenological variability increases due to climatic factors, species interactions within diverse communities can be affected. Shifts in hatching phenology can lead to body size variability that can alter species interactions, especially within and across trophic levels in complex food webs. To understand the effects of hatching phenology and food web complexity on prey communities, we conducted an experiment with ectotherms from ponds by manipulating hatching synchrony of a prey species across three dates and food web complexity. We hypothesized that predation on prey would be highest in the lowest synchrony treatment due to predator satiation effects in high synchrony additions. Food webs with top predators present had the lowest survival rates for prey compared to other food webs. Prey size at metamorphosis was also highest in the top predator food webs, suggesting a thinning effect. Hatching synchrony treatments did not have a significant impact on prey survival or size at metamorphosis except in treatments where intermediate and top predators were absent. Overall, our results show that top-down effects of predators may be enough to suppress the influence of phenological shifts in prey.

Ecological correlates of alternative reproductive tactics: conspecific brood parasitism rates vary with nest predation and seasonal effects influenced by climate change

Ecological and social factors shape individual reproductive strategies. Climate change has wide‐ranging effects on the timing of reproduction and availability of nesting sites for many birds. Ecological factors such as season length or predation rate could in turn affect the relative success rates of alternative reproductive tactics (ARTs). A new article by Pöysä (2024) featuring a long‐term study of common goldeneyes Bucephala clangula highlights the role of climate change in altering rates of conspecific brood parasitism (CBP) by affecting nest initiation dates and season length. While some authors have emphasized the effects of spatial and temporal aggregation of nests in promoting tactics of reproductive interference, few studies have addressed the effects of environmental variables on rates of CBP and other ARTs. I review some of the evidence for a relationship between population‐level nest predation rate and rates of CBP, principally in ducks and rails, and suggest a role for high rates of nest loss from all sources in the evolution of CBP and host responses. There is a need for further studies that examine environmental correlates of ARTs. Long‐term studies have the highest potential to reveal how shifts in phenology and life history variables may respond to environmental perturbations. Comparative studies of similar species in remote geographic locations can add perspective of how different ecological variables affect the prevalence of ARTs.

Earlier Spring-Summer Phenology and Higher Photosynthetic Peak Altered the Seasonal Patterns of Vegetation Productivity in Alpine Ecosystems

Carbon uptake of vegetation is controlled by phenology and photosynthetic carbon uptake capacity. However, our knowledge of the seasonal responses of vegetation productivity to phenological and physiological changes in alpine ecosystems is still weak. In this study, we quantified the spatio-temporal variations of vegetation phenology and gross primary productivity (GPP) across the source region of the Yellow River (SRYR) by analyzing MODIS-derived vegetation phenology and GPP from 2001 to 2019, and explored how vegetation phenology and maximum carbon uptake capacity (GPPmax) affected seasonal GPP over the region. Our results showed that the SRYR experienced significantly advanced trends (p &lt; 0.05) for both start (SOS) and peak (POS) of the growing season from 2001 to 2019. Spring GPP (GPPspr) had a significantly increasing trend (p &lt; 0.01), and the earlier SOS had obvious positive effects on GPPspr. Summer GPP (GPPsum) was significantly and negatively correlated to POS (p &lt; 0.05). In addition, GPPmax had a significant and positive correlation with GPPsum and GPPann (p &lt; 0.01), respectively. It was found that an earlier spring-summer phenology and higher photosynthetic peak enhanced the photosynthetic efficiency of vegetation in spring and summer and altered the seasonal patterns of vegetation productivity in the SRYR under warming and wetting climates. This study indicated that not only spring and autumn phenology but also summer phenology and maximum carbon uptake capacity should be regarded as crucial indicators regulating the carbon uptake process in alpine ecosystems. This research provides important information about how changes in phenology affect vegetation productivity in alpine ecosystems under global climate warming.

Effects of spatial variability in vegetation phenology, climate, landcover, biodiversity, topography, and soil property on soil respiration across a coastal ecosystem

Coastal terrestrial-aquatic interfaces (TAIs) are crucial contributors to global biogeochemical cycles and carbon exchange. The soil carbon dioxide (CO2) efflux in these transition zones is however poorly understood due to the high spatiotemporal dynamics of TAIs, as various sub-ecosystems in this region are compressed and expanded by complex influences of tides, changes in river levels, climate, and land use. We focus on the Chesapeake Bay region to (i) investigate the spatial heterogeneity of the coastal ecosystem and identify spatial zones with similar environmental characteristics based on the spatial data layers, including vegetation phenology, climate, landcover, diversity, topography, soil property, and relative tidal elevation; (ii) understand the primary driving factors affecting soil respiration within sub-ecosystems of the coastal ecosystem. Specifically, we employed hierarchical clustering analysis to identify spatial regions with distinct environmental characteristics, followed by the determination of main driving factors using Random Forest regression and SHapley Additive exPlanations. Maximum and minimum temperature are the main drivers common to all sub-ecosystems, while each region also has additional unique major drivers that differentiate them from one another. Precipitation exerts an influence on vegetated lands, while soil pH value holds importance specifically in forested lands. In croplands characterized by high clay content and low sand content, the significant role is attributed to bulk density. Wetlands demonstrate the importance of both elevation and sand content, with clay content being more relevant in non-inundated wetlands than in inundated wetlands. The topographic wetness index significantly contributes to the mixed vegetation areas, including shrub, grass, pasture, and forest. Additionally, our research reveals that dense vegetation land covers and urban/developed areas exhibit distinct soil property drivers. Overall, our research demonstrates an efficient method of employing various open-source remote sensing and GIS datasets to comprehend the spatial variability and soil respiration mechanisms in coastal TAI. There is no one-size-fits-all approach to modeling carbon fluxes released by soil respiration in coastal TAIs, and our study highlights the importance of further research and monitoring practices to improve our understanding of carbon dynamics and promote the sustainable management of coastal TAIs.

The potential of optical and SAR time-series data for the improvement of aboveground biomass carbon estimation in Southwestern China’s evergreen coniferous forests

ABSTRACT Accurate assessments of forest biomass carbon are invaluable for managing forest resources, evaluating effects on ecological protection, and achieving goals related to climate change and sustainable development. Currently, the integration of optical and synthetic aperture radar (SAR) data has been extensively utilized in estimating forest aboveground biomass carbon (AGC), while it is limited by using single-phase remote sensing images. Time-series data, which capture the interannual dynamic growth and seasonal variations of photosynthetic phenology in forests, can sufficiently describe forest growth characteristics. However, there remains a gap in research focusing on utilizing satellite-based time-series data for AGC estimation, especially for SAR sensors. This study investigated the potential of satellite-based optical and SAR time-series data for estimating AGC. Here, we undertook nine quantitative experiments of AGC estimation from Landsat 8 and Sentinel-1 and tested several regression algorithms (including multiple linear regression (MLR), random forests (RF), artificial neural network (ANN), and extreme gradient boosting (XGBoost)) to explore the contributions of spatiotemporal features to AGC estimation. The results suggested that the XGBoost algorithm was suitable for AGC estimation with explanatory solid power and stable performance. The temporal features representing forest growth trends and periodic change characteristics (such as coefficients of continuous wavelet transform) were more valuable for AGC estimation than spatial features for both sensor types, accounting for around 40% ~50% of the variance compared to 17% ~25%. The combination of optical and SAR time-series data produced the best performance (R2 = 0.814, RMSE = 18.789 Mg C/ha, rRMSE = 26.235%), compared with when utilizing optical or SAR time-series data alone (optical: R2 of 0.657 and rRMSE of 35.317%; SAR: R2 of 0.672 and rRMSE of 34.701%). Feature importance analysis also verified that temporal features of optical vegetation indices, SWIR 1/2 bands, and SAR backscatter from VV polarization were the most critical variables for AGC estimation. Furthermore, incorporating temporal features into the modeling is illustrated to be effective in reducing saturation effects within high-biomass forests. This study demonstrated the superiority of time-series data for forest carbon estimation. While the applicability of this methodology has only been investigated in evergreen coniferous forests, it may provide a viable approach needed to make full use of increasingly better and free satellite time-series data to estimate forest AGC with high accuracy, supporting policy making of forest management and sustainable development.

Different Approaches of Forest Type Classifications for Argentina Based on Functional Forests and Canopy Cover Composition by Tree Species

Modern forestry systems rely on typologies of forest types (FTs). In Argentina, several proposals have been developed, but they lack unified criteria. The objective was to compare different approaches, specifically focusing on (i) phenoclusters (functional forests based on vegetation phenology variations and climate variables) and (ii) forest canopy cover composition by tree species. We conducted comparative uni-variate analyses using data from national forest inventories, forest models (biodiversity, carbon, structure), and regional climate. We assessed the performance of phenoclusters in differentiating the variability of native forests (proxy: forest structure), biodiversity (proxy: indicator species), and environmental factors (proxies: soil carbon stock, elevation, climate). Additionally, we proposed a simple FT classification methodology based on species composition, considering the basal area of tree species. Finally, we compared the performance of both proposals. Our findings showed that classifications based on forest canopy cover composition are feasible to implement in regions dominated by mono-specific forests. However, phenoclusters allowed for the increased complexity of categories at the landscape level. Conversely, in regions where multi-specific stands prevailed, classifications based on forest canopy cover composition proved ineffective; however, phenoclusters facilitated a reduction in complexity at the landscape level. These results offer a pathway to harmonize national FT classifications by employing criteria and indicators to achieve sustainable forest management and conservation initiatives.

Synergistic Impacts of Built-Up Characteristics and Background Climate on Urban Vegetation Phenology: Evidence from Beijing, China

Vegetation is an important strategy for mitigating heat island effects, owed to its shading and evaporative cooling functions. However, urbanization has significantly affected regional vegetation phenology and can potentially weaken the cooling potential of vegetation. Previous studies have mainly focused on national and regional vegetation phenology, but local-scale vegetation phenology and dynamic variations in built-up areas remain unclear. Therefore, this study characterized the vegetation phenology in the densely built-up area of Beijing, China over the period of 2000–2020 based on high-resolution NDVI data using Savitzky–Golay filtering and explored its spatiotemporal characteristics and drivers. The results indicate that the vegetation phenology exhibits significant spatial heterogeneity and clustering characteristics. Compared with vegetation in peripheral blocks, vegetation in central urban blocks generally has an earlier start in the growing season (SOS), later end in the growing season (EOS), and a longer growing season length (GSL). However, the overall distribution of these parameters has experienced a process of decentralization along with urbanization. In terms of drivers, vegetation phenology indicators are mainly influenced by background climate. Specifically, SOS and GSL are mainly affected by temperature (TEP), whereas EOS is mainly influenced by annual precipitation (PRE). Additionally, local environmental factors, particularly the percentage of water body (WAP), also have an impact. Notably, the local environment and background climate have a synergistic effect on vegetation phenology, which is greater than their individual effects. Overall, this study extends the current knowledge on the response of vegetation phenology to urbanization by investigating long-term vegetation phenology dynamics in dense urban areas and provides new insights into the complex interactions between vegetation phenology and built environments.

Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022

Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022

Forecasting nocturnal bird migration for dynamic aeroconservation: The value of short‐term datasets

Abstract Placing wind turbines within large migration flyways, such as the North Sea basin, can contribute to the decline of vulnerable migratory bird populations by increasing mortality through collisions. Curtailment of wind turbines limited to short periods with intense migration can minimize these negative impacts, and near‐term bird migration forecasts can inform such decisions. Although near‐term forecasts are usually created with long‐term datasets, the pace of environmental alteration due to wind energy calls for the urgent development of conservation measures that rely on existing data, even when it does not have long temporal coverage. Here, we use 5 years of tracking bird radar data collected off the western Dutch coast, weather and phenological variables to develop seasonal near‐term forecasts of low‐altitude nocturnal bird migration over the southern North Sea. Overall, the models explained 71% of the variance and correctly predicted migration intensity above or below a threshold for intense hourly migration in more than 80% of hours in both seasons. However, the percentage of correctly predicted intense migration hours (top 5% of hours with the most intense migration) was low, likely due to the short‐term dataset and their rare occurrence. We, therefore, advise careful consideration of a curtailment threshold to achieve optimal results. Synthesis and applications: Near‐term forecasts of migration fluxes evaluated against measurements can be used to define curtailment thresholds for offshore wind energy. We show that to minimize collision risk for 50% of migrants, if predicted correctly, curtailments should be applied during 18 h in spring and 26 in autumn in the focal year of model assessments, resulting in an estimated annual wind energy loss of 0.12%. Drawing from the Dutch curtailment framework, which pioneered the ‘international first’ offshore curtailment, we argue that using forecasts developed from limited temporal datasets alongside expert insight and data‐driven policies can expedite conservation efforts in a rapidly changing world. This approach is particularly valuable in light of increasing interannual variability in weather conditions.

Insights into Canopy Escape Ratio from Canopy Structures: Correlations Uncovered through Sentinel-2 and Field Observation

This study explores the quantitative relationship between canopy structure and the canopy escape ratio (fesc), measured as the ratio of near-infrared reflectance of vegetation (NIRv) to the fraction of absorbed photosynthetically active radiation (fAPAR). We analyzed the correlation between fesc and key indicators of canopy structure—specifically, leaf area index (LAI) and clumping index (CI)—utilizing both Sentinel-2 satellite data and in situ observations. Our analysis revealed a moderate correlation between fesc and LAI, evidenced by an R2 value of 0.37 for satellite-derived LAI, which contrasts with the lower correlation (R2 of 0.15) observed with field-measured LAI. Conversely, the relationship between fesc and CI proved to be significantly weaker (R2 &lt; 0.1), indicating minimal interaction between foliage distribution and light escape at the canopy level. This disparity in correlation strength was further evidenced in time series analysis, which showed little phenological variation in fesc compared to LAI. Our findings elucidate the complexities of estimating fesc based on the NIRv to fAPAR ratio and underscore the need for advanced methodologies in future research to enhance the accuracy of canopy escape models.

Seasonal aridity regulates drivers and temporal variability of wood phenology: A meta-analysis of dendrometer monitoring data across the Northern Hemisphere

The secondary growth phenology of trees, also known as wood phenology, plays a vital role in assessing the timing of carbon sequestration in forests. However, its spatio-temporal variability and determinants in the Northern Hemisphere remain debated. Here, we presented a meta-analysis using secondary growth phenology data based on dendrometer monitoring of 59 tree species and 84 sites to explore the drivers and temporal connections of phenology across seasonal arid and humid regions in the Northern Hemisphere. We found spring temperatures and precipitation co-regulated the start of secondary growth (SOG) in spring arid regions, and SOG advanced with the increase in spring temperatures and precipitation. However, SOG was only influenced by spring temperatures in spring humid regions. The end of secondary growth (EOG) indicated strong correlations with autumn temperatures only in autumn arid regions but not in humid regions. Interestingly, the earlier SOG promoted advancement of the time of maximum secondary growth rate (MOG) and EOG both in seasonal humid and arid regions, while the end of secondary growth in the previous year (prEOG) negatively affected SOG only in seasonal arid regions. The legacy effects of previous phenological events on subsequent ones should be integrated into phenological prediction models to help accurately assess global carbon, water, and energy cycles.

Variation of Phenology of Flacourtia rukam in Two Different Habitats and Their Relation to Rainfall, Dry Days, and the Plant Water Status

Phenological shifts in the emergence of vegetative and generative parts, occur due to the response of plants to water received due to climate change. The rukam tree (Flacourtia rukam (Zoll &amp; Moritzi)) is a local Indonesian plant with potential as an edible fruit and antioxidant agent, but its existence is increasingly rare. F. rukam can be found in Pasuruan, East Java, including Purwodadi Botanical Garden (PBG) as collected plants and Sekarmojo Village as cultivated plants. These populations show a shift in phenology, but this has never been studied. This study aimed to analyze the spatial variation of the phenology of two rukam populations and its relation to plant water status, rainfall quantity (RQ), and drought days (DD). This research was conducted on two individual trees at each location, was conducted from August 2020 to October 2022 using secondary data from BMKG, such as daily rainfall and the number of days without rain. Phenology was directly observed every week with an estimated abundance of numbers 1-4; plant water status was observed by calculating relative water content (RWC); soil physical analysis was carried out in mid-season. Data were analyzed by Mann-Whitney test and SEM WarpPLS. The results showed differences in phenology in the phases of leaf fall, flower buds, young fruit, and ripe fruit on the trees in the different locations. The decreased RQ in the past month significantly reduced the RWC value of F. rukam in both places, while the number of DD contributed to a decrease in the RWC value in PBG only, not in Sekarmojo. In both sites, decreasing the RWC of the rukam increased the abundance of fallen leaves and the chances of flowering. Rainfall and drought days affected plant phenology directly or indirectly through RWC mediation. In both places, RQ had a direct positive and significant effect on blooming flowers and new leaves but had negative effect on fallen leaves. While DD had a positive effect on leaf fall, flower formation, and fruit ripening, but had a negative effect on the appearance of young fruit (in PBG). Indirectly, RQ mainly affected several phenological parameters, while DD did not affect all phenological parameters.

Remotely-sensed phenoclusters of Wisconsin’s forests, shrublands, and grasslands for biodiversity applications

Heterogeneous vegetation supports higher species richness than homogenous vegetation, which is why efficiently identifying heterogenous vegetation can be useful for biodiversity conservation. Satellite remote-sensing data provide an opportunity to generate vegetation heterogeneity metrics and to explore the phenology of vegetation patterns. Phenoclusters are vegetation types with similar phenological characteristics, and valuable for capturing vegetation habitat heterogeneity patterns. Our goal was to map phenoclusters for Wisconsin, USA, at 10-m spatial resolution based on land surface phenology metrics from EVI (Enhanced Vegetation Index) Sentinel-2 data. We characterized each phenocluster based on landcover composition and structure, phenology timing, and environmental factors, and compared them to bird species richness. We also calculated the diversity of phenoclusters at multiple spatial extents. We identified 14 phenoclusters in Wisconsin, each with distinct landcover composition and structure, and unique phenological characteristics. Our remotely-sensed phenoclusters effectively captured environmental gradients, with elevation and temperature emerging as the most important driving variables. Furthermore, the phenoclusters successfully captured bird biodiversity patterns, especially richness of forest and grassland specialist. Our results identified phenological patterns among Wisconsin’s forests, shrublands, and grasslands, capturing phenological timing both among and within the same tree species. Phenoclusters are a valuable tool for capturing vegetation habitat heterogeneity, phenology diversity and biodiversity patterns, as well as climate change effects.

Patterns and trends in the spatial heterogeneity of land surface phenology of global forests

Land-surface phenology is a widely used indicator of how terrestrial ecosystems respond to environmental change. The spatial variability of this plant functional trait has also been advocated as an indicator of the functional composition of ecosystems. However, a global-scale assessment of spatial patterns in the spatial heterogeneity of forest phenology is currently lacking. To address this knowledge gap, we developed an index based on satellite retrievals and used it to quantify phenological diversity across global forest biomes. We show that there is considerable variation in phenological diversity among biomes, with the highest overall levels occurring in arid and temperate regions. An analysis of the drivers of the spatial patterns revealed that temperature-related factors primarily determine the variation in phenological diversity. Notably, temperature seasonality and mean annual temperature emerged as the most significant variables in explaining this global-scale variability. Furthermore, an assessment of temporal changes over an 18-year period revealed strong climate-driven shifts of phenological diversity in boreal and arid regions, suggesting that there may be an ongoing widespread homogenisation of land surface phenology within forest ecosystems. Our findings ultimately contribute to the development of a novel Essential Biodiversity Variable, which may enable scientists and practitioners to quantify the functional composition of ecosystems at unprecedented spatial and temporal scales.