Plant Phenological Observations Research Articles

Northern hemisphere land-atmosphere feedback from prescribed plant phenology in CESM

Abstract Plant phenology influences both the terrestrial carbon cycle and land-atmosphere interactions, and therefore can potentially modify large-scale circulations in the atmosphere. However, considerable discrepancies are present among models and between model simulations and observations of plant phenology, adding large uncertainties to future climate projections. Here we modified plant phenology in the Northern Hemisphere in the Community Earth System Model and conducted simulations to characterize how differences in plant phenology influence land-atmosphere coupling. Plant phenology changes the land surface and land-atmosphere interactions by directly modulating absorbed solar radiation and evapotranspiration and indirectly modifying cloud feedback and snow-albedo feedback. Over the Northern Hemisphere, the largest effects occur from March to June when seasonal deciduous phenology is modified from satellite-derived values to model simulations, which results in a >3K increase in surface temperature that propagates to 500hPa (~5km height). Phenology-induced changes in canopy evapotranspiration and surface temperature depend on soil moisture availability during the growing season. Surface temperature decreases significantly due to increasing latent heat flux and cloud reflection where soil moisture is abundant, while soil moisture control over evapotranspiration increases and surface temperature remains little-changed or even increases in more arid regions. Characterizing the influence of phenology on biogeophysical processes is critical, as significant impacts are present both at the land surface and in the atmospheric layers above.

Climate change affects plant aboveground biomass by regulating the growth periods in alpine grasslands of the Tibetan Plateau, China

Climate change significantly affects plant biomass and phenological occurrence time in alpine grasslands of Tibetan Plateau. The changes in phenological periods are closely related to the length of vegetative and reproductive growth periods, which may further affect aboveground biomass accumulation. In this study, based on fixed-point observations of plant biomass and phenology as well as the corresponding climatic data from 1997 to 2020 in the alpine grasslands of Tibetan Plateau, we used statistical methods such as ordinary linear regression and piecewise structural equation model to explore the characteristics of interannual climate change in the study area, the variation trends of plant biomass and phenological periods, and the correlations between biomass and phenological and climatic factors. The results showed that mean annual temperature and annual precipitation in the study area increased significantly from 1997 to 2020, suggesting a clear "warm-wet" trend. Aboveground biomass and relative biomass of Stipa sareptana var. krylovii (the dominant species) decreased significantly. However, absolute and relative biomass of subdominant species (Kobresia humilis) increased significantly, indicating that the dominance of K. humilis increased. The warm-wet climates enhanced aboveground biomass accumulation of K. humilis by extending the period of reproductive growth. Mean annual temperature and annual precipitation decreased aboveground biomass of S. sareptana by shortening the length of vegetative growth period. In a word, the warmer and wetter climate significantly affected aboveground biomass accumulation by regulating the changes in the phenological period, and the interspecific difference in their response resulted in a larger change in community composition. This study area may show a trend from alpine grassland to alpine meadow, and thus further works are urgently needed.

Plant phenological dataset collated by the Finnish Society of Sciences and Letters.

Long records of phenological observations constitute data for ecological, climate and global change studies. Here we provide an extraordinary dataset of plant phenological observations made in Boreal Europe between 1750 and 1965 from locations situated across historical and modern Finland, mostly between 70° and 60°N and 30° and 20°E. This dataset has been initially generated by the efforts of several generations of volunteers representing naturalists whose field observations and notes have initially made the continuous collection of the data possible. Meanwhile, the data was collated by the Finnish Economic Society and the Finnish Society of Sciences and Letters and published irregularly in the form of several monographs and periodicals by contemporary academic enthusiasts. Each phenological observation contains 11 features including: site name, site latitude, site longitude, scientific species name, phenological stage and (if any) its substage, year, date (month and day) and the day since summer solstice, the original literature source, and outlier estimate. Species names given originally either in Latin, Finnish, German and/or Swedish were transformed into scientific species names. Moreover, outdated taxonomic names were updated as appropriate. Phenological stages given originally either in German, Finnish and/or Swedish were transformed into English and standardized by excluding synonyms. Site names were adopted at county level, with corresponding latitude and longitude generated herein. The digitized dataset represents 265478 observations of 985 taxa (assigned to variety/subspecies/species/hybrid/genus) for their 16 different phenological stages made in 371 locations across the region. We provide this dataset to support comparative studies and modeling projects seeking to improve understanding of terrestrial ecosystem dynamics and their responses to a changing environment from local to global scale. Use of this dataset for academic or educational purposes is encouraged as long as the data source is properly cited with attribution given to this presentation of the data. Users are free to use and analyze the data; additionally, we would like to hear from other researchers who use these data sets in teaching or for their own research. This article is protected by copyright. All rights reserved.

Ecological livelihoods of farmers and pollinators in the Himalayas: Doing critical physical geography using citizen science

In farming communities dependent on the cultivation of pollinator‐dependent crops, the livelihoods of farmers are inextricably linked with pollinator health. A global pollination crisis interlinked with a crisis of food production and farmer livelihoods, exacerbated by processes of socio‐environmental change, is emblematic of the Anthropocene and of the kinds of ecosocial problems with which critical physical geography (CPG) engages. We propose examining the farmer‐pollinator system in the Indian Himalayas through an ecological livelihoods approach using a range of collaborative citizen science methods including bloom observations to document pollinator visits, plant phenological observations to document year‐round floral resource availability, and farm diaries to document orchard management practices. An ecological livelihoods approach draws on posthumanist theory, which has remained largely disengaged with methodological questions that are of concern to CPG. Citizen science, although widely used across a range of disciplines, has seen limited engagement in CPG. After elaborating some of the opportunities and challenges that an engagement between CPG, posthumanist theory, and citizen science opens up, we propose a methodology that would be simultaneously epistemological (understanding interdependence between livelihoods of farmers and pollinators) and ontological (imagining and building worlds where farmer and pollinator habitats are recomposed).

Large-scale citizen science programs can support ecological and climate change assessments

Large-scale citizen science programs have the potential to support national climate and ecosystem assessments by providing data useful in estimating both status and trends in key phenomena. In this study, we demonstrate how opportunistic, unbalanced observations of biological phenomena contributed through a national-scale citizen science program can be used to (a) identify and evaluate candidate biotic climate change indicators and (b) generate yearly estimates of status of selected indicators. Using observations of plant phenology contributed to Nature’s Notebook, the USA National Phenology Network’s citizen science program, we demonstrate a procedure for identifying biotic indicators as well as several approaches leveraging these opportunistically-sampled data points to generate yearly status measures. Because the period of record for this dataset is relatively short and inconsistently sampled (13 yr), we focus on estimates of status, though over time, these measurements could be leveraged to also estimate trends. We first applied various spatial, seasonal, and biological criteria to narrow down the list of candidate indicators. We then constructed latitude-elevation models for individual species-phenophase events using all observations. This allowed us to visualize differences between predicted and reported phenophase onset dates in a year as anomalies, with the expectation that these anomalies—representing earlier or later activity in the species of interest—reflect plant response to local springtime temperatures. Plotting yearly anomalies revealed regions with geographic coherence as well as outliers. We also show how yearly anomaly values can be reduced to a single measure to characterize the early or late nature of phenological activity in a particular year. Finally, we demonstrate how the latitude-elevation models can be leveraged to characterize the pace at which phenological transitions occur along latitude gradients on a year-by-year basis.

Plants in the UK flower a month earlier under recent warming.

Global temperatures are rising at an unprecedented rate, but environmental responses are often difficult to recognize and quantify. Long-term observations of plant phenology, the annually recurring sequence of plant developmental stages, can provide sensitive measures of climate change and important information for ecosystem services. Here, we present 419 354 recordings of the first flowering date from 406 plant species in the UK between 1753 and 2019 CE. Community-wide first flowering advanced by almost one month on average when comparing all observations before and after 1986 (p < 0.0001). The mean first flowering time is 6 days earlier in southern than northern sites, 5 days earlier under urban than rural settings, and 1 day earlier at lower than higher elevations. Compared to trees and shrubs, the largest lifeform-specific phenological shift of 32 days is found in herbs, which are generally characterized by fast turnover rates and potentially high levels of genetic adaptation. Correlated with January–April maximum temperatures at −0.81 from 1952–2019 (p < 0.0001), the observed trends (5.4 days per decade) and extremes (66 days between the earliest and latest annual mean) in the UK's first flowering dataset can affect the functioning and productivity of ecosystems and agriculture.

Artificial light pollution inhibits plant phenology advance induced by climate warming

Natural photic regime has been drastically altered by the artificial night sky luminance. Despite evidence of sufficient light brightness inducing plant physiology and affecting phenology, generalization regarding effects of light pollution on plant phenology across species and locations is less clear. Meanwhile, the relative contributions and joint effects of artificial light pollution and climate change or other anthropic stressors still remain unknown. To fill this knowledge gap, we utilized in situ plant phenological observations of seven tree species during 1991–2015 in Europe, night-time light dataset and gridded temperature dataset to investigate the impacts of the artificial light pollution on spatial-temporal shifts of plant phenological phases under climatic warming. We found 70% of the observation sites were exposed to increased light pollution during 1992–2015. Among them, plant phenological phases substantially delayed at 12–39% observation sites of leaf-out, and 6–53% of flowering. We also found plant species appeared to be more sensitive to artificial light pollution, and phenology advancement was hindered more prominently and even delay phenomenon exhibited when the color level showed stronger sky brightness. Linear mixed models indicate that although temperature plays a dominant role in shifts of plant phenological phases at the spatial scale, the inhibitory effect of artificial light pollution is evident considering the interactions. To our knowledge, this study is the first to quantitatively establish the relationship between artificial light pollution and plant phenology across species and locations. Meanwhile, these findings provide a new insight into the ecological responses of plant phenology to the potential but poorly understood environmental stressors under this warmer world and call for light pollution to be accorded the equal status as other global change phenomena.

Plant phenological responses to experimental warming-A synthesis.

Although there is abundant evidence that plant phenology is shifting with climatic warming, the magnitude and direction of these shifts can depend on the environmental context, plant species, and even the specific phenophase of study. These disparities have resulted in difficulties predicting future phenological shifts, detecting phenological mismatches and identifying other ecological consequences. Experimental warming studies are uniquely poised to help us understand how climate warming will impact plant phenology, and meta-analyses allow us to expose broader trends from individual studies. Here, we review 70 studies comprised 1226 observations of plant phenology under experimental warming. We find that plants are advancing their early-season phenophases (bud break, leaf-out, and flowering) in response to warming while marginally delaying their late-season phenophases (leaf coloration, leaf fall, and senescence). We find consistency in the magnitude of phenological shifts across latitude, elevation, and habitat types, whereas the effect of warming on nonnative annual plants is two times larger than the effect of warming on native perennial plants. Encouragingly for researchers, plant phenological responses were generally consistent across a variety of experimental warming methods. However, we found numerous gaps in the experimental warming literature, limiting our ability to predict the effects of warming on phenological shifts. In particular, studies outside of temperate ecosystems in the Northern Hemisphere, or those that focused on late-season phenophases, annual plants, nonnative plants, or woody plants and grasses, were underrepresented in our data set. Future experimental warming studies could further refine our understanding of phenological responses to warming by setting up experiments outside of traditionally studied biogeographic zones and measuring multiple plant phenophases (especially late-season phenophases) across species of varying origin, growth form, and life cycle.

Integrating a PhenoCam-derived vegetation index into a light use efficiency model to estimate daily gross primary production in a semi-arid grassland

The accurate estimation of temporally-continuous gross primary production (GPP) is important for a mechanistic understanding of the global carbon budget, as well as the carbon exchange between land and atmosphere. Ground-based PhenoCams can provide near-surface observations of plant phenology with high temporal resolution and possess great potential for use in modeling the seasonal dynamics of GPP. However, due to the site-level empirical approaches for estimating the fraction of absorbed photosynthetically active radiation (fAPAR), a broad application of PhenoCams in GPP modeling has been restricted. In this study, the stage of vegetation phenology (Pscalar) is proposed, which is calculated from the excess green index (ExGI) derived from PhenoCam data. We integrate Pscalar with the enhanced vegetation index (EVI) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to generate a daily time-series of the fAPAR (fAPARCAM), and then to estimate daily GPP (GPPCAM) with a light use efficiency model in a semi-arid grassland area from 2012 to 2014. Over the three continuous years, the daily fAPARCAM exhibited similar temporal behavior to the eddy covariance–measured GPP (GPPEC), and the overall determination coefficients (R2) were all > 0.81. GPPCAM agreed well with GPPEC, and these agreements were highly statistically significant (p < 0.01); R2 varied from 0.80 to 0.87, the relative error (RE) varied from -2.9% to 2.81%, and the root mean square error (RMSE) ranged from 0.83 to 0.98 gC/m2/d. GPPCAM was then resampled to 8-day temporal resolution (GPPCAM8d), and further evaluated by comparisons with MODIS GPP products (GPPMOD17) and vegetation photosynthesis model (VPM)–derived GPP (GPPVPM). Validation revealed that the variance explained by GPPCAM8d was still the greatest among these three GPP products. The RMSE and RE of GPPCAM8d were also lower than those of the other two GPP products. The explanatory power of predictors in GPP modeling was also explored; the fAPAR was found to be the most influential predictor, followed by photosynthetically active radiation (PAR). The contributions of the environmental stress indices of temperature and water (Tscalar and Wscalar, respectively) were less than that of PAR. These results highlight the potential for PhenoCam images in high temporal resolution GPP modeling. Our GPP modeling method will help reduce uncertainties by using PhenoCam images for monitoring the seasonal development of vegetation production.

The effect of urbanization on plant phenology depends on regional temperature.

Plant and animal phenology is shifting in response to urbanization, with most hypotheses focusing on the 'urban heat island' (UHI) effect as the driver. However, generalities regarding the direction and magnitude of phenological response to urbanization have not yet emerged because most studies have focused on remote-sensed vegetative phenologies or at local scales with relatively few species. Furthermore, how urbanization interacts with broad-scale climate gradients remains an unknown but important component of anthropogenically driven phenological change. Here, we used a database with >22 million in situ plant phenological observations from the United States and Europe to study the joint influence of varying human population density, which serves as an urbanization measure, and of regional temperature on median flowering and leaf-out dates across a wide plant phylogenetic spectrum. Separately, increasing population density and warmer regional temperature both advanced plant flowering and leaf-out. However, the influence of human population density on plant flowering and leaf-out depends on the regional temperature: high population density advanced plant phenology in cold areas but this effect disappeared or even reversed in warm areas. UHI effects (as measured by daily land surface temperature) alone cannot explain the overall influence of urbanization on plant phenology, suggesting that urbanization also affects plant phenology via other mechanisms. Shorter plants with large specific leaf areas and early flower or leaf-out dates were most affected by urbanization and temperature changes. Our study provides strong empirical evidence that the influence of urbanization on plant phenology varies with regional temperature. Therefore, robust understanding and accurate prediction of phenological changes must take this interaction into account.

The BernClim plant phenological data set from the canton of Bern (Switzerland) 1970–2018

Abstract. In 1970, the Institute of Geography of the University of Bern initiated the phenological observation network BernClim. Seasonality information from plants, fog and snow was originally available for applications in urban and regional planning and agricultural and touristic suitability and is now a valuable data set for climate change impact studies. Covering the growing season, volunteer observers record the dates of key development stages of hazel (Corylus avellana), dandelion (Taraxacum officinale), apple tree (Pyrus malus) and beech (Fagus sylvatica). All observations consist of detailed site information, including location, altitude, exposition (aspect) and inclination, that makes BernClim unique in its richness in detail on decadal timescales. Quality control (QC) by experts and statistical analyses of the data have been performed to flag impossible dates, dates outside the biologically plausible range, repeated dates in the same year, stretches of consecutive identical dates and statistically inconsistent dates (outliers in time or in space). Here, we report BernClim data of 7414 plant phenological observations from 1970 to 2018 from 1304 sites at 110 stations, the QC procedure and selected applications (Rutishauser et al., 2019: https://doi.org/10.1594/PANGAEA.900102). The QC points to very good internal consistency (only 0.2 % were flagged as internally inconsistent) and likely high quality of the data. BernClim data indicate a trend towards an extended growing season. They also track the regime shift in the late 1980s well to pronounced earlier dates like numerous other phenological records across the Northern Hemisphere.

Warming shortens flowering seasons of tundra plant communities.

Advancing phenology is one of the most visible effects of climate change on plant communities, and has been especially pronounced in temperature-limited tundra ecosystems. However, phenological responses have been shown to differ greatly between species, with some species shifting phenology more than others. We analysed a database of 42,689 tundra plant phenological observations to show that warmer temperatures are leading to a contraction of community-level flowering seasons in tundra ecosystems due to a greater advancement in the flowering times of late-flowering species than early-flowering species. Shorter flowering seasons with a changing climate have the potential to alter trophic interactions in tundra ecosystems. Interestingly, these findings differ from those of warmer ecosystems, where early-flowering species have been found to be more sensitive to temperature change, suggesting that community-level phenological responses to warming can vary greatly between biomes.

Herbarium specimens reveal substantial and unexpected variation in phenological sensitivity across the eastern United States.

Phenology is a key biological trait that can determine an organism's survival and provides one of the clearest indicators of the effects of recent climatic change. Long time-series observations of plant phenology collected at continental scales could clarify latitudinal and regional patterns of plant responses and illuminate drivers of that variation, but few such datasets exist. Here, we use the web tool CrowdCurio to crowdsource phenological data from over 7000 herbarium specimens representing 30 diverse flowering plant species distributed across the eastern United States. Our results, spanning 120 years and generated from over 2000 crowdsourcers, illustrate numerous aspects of continental-scale plant reproductive phenology. First, they support prior studies that found plant reproductive phenology significantly advances in response to warming, especially for early-flowering species. Second, they reveal that fruiting in populations from warmer, lower latitudes is significantly more phenologically sensitive to temperature than that for populations from colder, higher-latitude regions. Last, we found that variation in phenological sensitivities to climate within species between regions was of similar magnitude to variation between species. Overall, our results suggest that phenological responses to anthropogenic climate change will be heterogeneous within communities and across regions, with large amounts of regional variability driven by local adaptation, phenotypic plasticity and differences in species assemblages. As millions of imaged herbarium specimens become available online, they will play an increasingly critical role in revealing large-scale patterns within assemblages and across continents that ultimately can improve forecasts of the impacts of climatic change on the structure and function of ecosystems.This article is part of the theme issue 'Biological collections for understanding biodiversity in the Anthropocene'.

Digitizing the plant phenological dataset (1750–1875) from collections of Professor Adolf Moberg: Towards the development of historical climate records

Long records of phenological observations are commonly used as data in global change and palaeoclimate research and to analyse plants' responses to climatic changes. Here we delve into the historical archives of plant phenological observations (1750–1875) compiled and published previously by Professor Adolf Moberg (Imperial Alexander University of Finland). The digitized dataset represents 44,487 observations of 450 different plant species for their 15 different phenological phases made in 193 sites across Finland, and results in 662 different phenological variables. The five most frequently observed variables are the blooming of rye, the sowing of barley, the blooming of bird cherry, the leaf outbreak of birch, and the sowing of oat. The spring and summer observations demonstrate positive relationships between the onset date and the site latitude, this relationship becoming negative for observations made in the autumn. This latitudinal effect is evident in the raw data as demonstrated by the temporal correlations between the unadjusted mean phenological records and the mean latitude of the sites. After the latitudinal effect is removed from the original data such correlations are much reduced and the new set of phenological records based on the adjusted dates can be computed. The resulting mean phenological records correlate negatively and statistically significantly with the mean temperatures from April through July. Linear trends indicate (i) summer onsets having become delayed by more than one week over the full period and (ii) shortening of the growing seasons since 1846. The dataset is made available in an open repository.

Spring green-up phenology products derived from MODIS NDVI and EVI: Intercomparison, interpretation and validation using National Phenology Network and AmeriFlux observations

Advances in the timing of spring green-up date are a typical response of vegetation global change. Long-term observations of plant phenology have been used to track vegetation response to climate change. Normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have been the most commonly used indicators in reconstructing spring green-up dates from remote sensing over the past several decades. The Moderate Resolution Imaging Spectroradiometer (MODIS) based phenology time series from NDVI and EVI with an enhanced TIMESAT algorithm are the two operational phenology products developed recently with sun-sensor geometry corrected reflectance. However, a comprehensive intercomparison and evaluation of these two spring green-up datasets using intensive ground observations have not been conducted, limiting their applications in regional interpretation of land surface phenology. Therefore, we used 455 ground observations from USA National Phenology Network (NPN) and 106 observations from 21 AmeriFlux sites to assess and validate the spring green-up dates for United States for 2000–2013. Our results indicate that the spring green-up dates from NDVI and EVI showed a good agreement in eastern United States, while substantial differences (70days) were found in western and southern areas. Ground observations generally had a significant correlation (p<0.01) with the two MODIS spring green-up dates, especially for deciduous broadleaf forests with root mean square error (RMSE) of 12days and 16days when compared with USA-NPN and AmeriFlux observations, respectively. Spring green-up dates from EVI overall showed a better relationship and a lower RMSE in reference to both USA-NPN and AmeriFlux observations than NDVI-based spring green-up dates. Our results highlight the importance of a rigorous validation of remote sensing products to better understand their limitations in operational applications.

Plant phenological observations in rural and industrial central Italy areas.

The physiological stress caused by particular pollution conditions can result in phenological phase shifts that can include a block in vegetative or reproductive development. The main aim of the present study was to determine and analyse the mean development trends of some winter deciduous species in comparison to the climate tendencies, as calculated within two phenological gardens in the Arezzo and Perugia areas of central Italy. Moreover, a phenological comparison between the guide species of the two phenological gardens, one located in an industrial area, and the other in a farming area, was carried out. The phenological evidences showed significant phase displacements for the common guide species present in both the gardens which however may be explained by the meteorological performances above all in the Perugia not polluted area. In these terms, there were no evident phenological effects on the plants from the industrial area pollutants in the Arezzo garden. Moreover, also the temperature reduction tendencies at the end of spring not influenced significantly the phenological behaviours of the plant species not inducing them toward a predictable delay of reproductive and adult leaves phases.

Synergistic Use of Citizen Science and Remote Sensing for Continental-Scale Measurements of Forest Tree Phenology

There is great potential value in linking geographically dispersed multitemporal observations collected by lay volunteers (or “citizen scientists”) with remotely-sensed observations of plant phenology, which are recognized as useful indicators of climate change. However, challenges include a large mismatch in spatial scale and diverse sources of uncertainty in the two measurement types. These challenges must be overcome if the data from each source are to be compared and jointly used to understand spatial and temporal variation in phenology, or if remote observations are to be used to predict ground-based observations. We investigated the correlation between land surface phenology derived from Moderate Resolution Imaging Spectrometer (MODIS) data and citizen scientists’ phenology observations from the USA National Phenology Network (NPN). The volunteer observations spanned 2004 to 2013 and represented 25 plant species and nine phenophases. We developed quality control procedures that removed observations outside of an a priori determined acceptable period and observations that were made more than 10 days after a preceding observation. We found that these two quality control steps improved the correlation between ground- and remote-observations, but the largest improvement was achieved when the analysis was restricted to forested MODIS pixels. These results demonstrate a high degree of correlation between the phenology of individual trees (particularly dominant forest trees such as quaking aspen, white oak, and American beech) and the phenology of the surrounding forested landscape. These results provide helpful guidelines for the joint use of citizen scientists’ observations and remote sensing phenology in work aimed at understanding continental scale variation and temporal trends.

Greater Abundance of Betula nana and Early Onset of the Growing Season Increase Ecosystem CO2 Uptake in West Greenland

Expansion of deciduous shrubs is a common observation throughout the Arctic, with implications for carbon (C) cycling. Shrubs may increase net ecosystem C uptake through greater leaf area and gross ecosystem photosynthesis (GEP), and/or through cooler summer soils and reduced ecosystem respiration (ER). We used a space-for-time substitution combined with experimental warming at a Low Arctic site in West Greenland to examine the biophysical effects of increased temperature and Betula nana abundance on ecosystem CO2 exchange. Communities dominated by Betula were much stronger C sinks than graminoid communities due to greater GEP and lower ER. The warming treatment had little effect on GEP, ER, or net ecosystem CO2 exchange (NEE). The start of the growing season has been advancing at our study site, as indicated by long-term observations of plant phenology. In a retrospective analysis, we estimate that earlier onset of the growing season has increased the strength of the ecosystem C sink at rates of 1.3 and 2.1 g C m−2 y−1 in Betula and graminoid tundra, respectively, since 2002. However, earlier, and presumably longer, growing seasons may be associated with greater potential for drought stress. Our data suggest that mid-summer drought-induced GEP declines may partially offset C gains associated with an earlier start to the growing season. Our results suggest greater deciduous shrub abundance and longer growing seasons will likely lead to greater net C uptake in our study area, while highlighting important complexities associated with drought and plant community composition.

The plant phenology monitoring design for The National Ecological Observatory Network

AbstractPhenology is an integrative science that comprises the study of recurring biological activities or events. In an era of rapidly changing climate, the relationship between the timing of those events and environmental cues such as temperature, snowmelt, water availability, or day length are of particular interest. This article provides an overview of the observer‐based plant phenology sampling conducted by the U.S. National Ecological Observatory Network (NEON), the resulting data, and the rationale behind the design. Trained technicians will conduct regular in situ observations of plant phenology at all terrestrial NEON sites for the 30‐yr life of the observatory. Standardized and coordinated data across the network of sites can be used to quantify the direction and magnitude of the relationships between phenology and environmental forcings, as well as the degree to which these relationships vary among sites, among species, among phenophases, and through time. Vegetation at NEON sites will also be monitored with tower‐based cameras, satellite remote sensing, and annual high‐resolution airborne remote sensing. Ground‐based measurements can be used to calibrate and improve satellite‐derived phenometrics. NEON's phenology monitoring design is complementary to existing phenology research efforts and citizen science initiatives throughout the world and will produce interoperable data. By collocating plant phenology observations with a suite of additional meteorological, biophysical, and ecological measurements (e.g., climate, carbon flux, plant productivity, population dynamics of consumers) at 47 terrestrial sites, the NEON design will enable continental‐scale inference about the status, trends, causes, and ecological consequences of phenological change.

Evaluating the level of agreement between human and time-lapse camera observations of understory plant phenology at multiple scales

The growing popularity of digital-repeat photography in field research is seeing traditional field efforts being assisted and even replaced by low-cost cameras. The efficiency of using cameras is obvious, but there is an assumption that they capture the same information as observations made by humans. This paper aims to determine the level of agreement between these two methods of interpreting understory vegetation phenology. We compared daily phenological observations made by low-cost cameras with those made by personnel during field visits every 10days. Phenophases were defined as the non-spectral, physical developmental stages of Canadian buffaloberry (Shepherdia canadensis) and alpine sweetvetch (Hedysarum alpinum). The relationship between observation methods was quantified using a weighted kappa statistic at three spatial scales ranging from individual plants to areas up to 6ha. Agreement between the camera observations and those made by field personnel was nearly perfect (Kappa>0.9) for both the vegetative and reproductive phenology of both study species at all spatial scales. The level of agreement was found to be more variable early in the season when plant growth is more rapid. Overall there was a slight bias in the image interpretations to underestimate the rate of development. Time-lapse photography was found to be an analogous replacement for field visits; however, some plant species are more suitable for observation by camera than others. Spatially, it was determined that observations of a single plant are all that is required to capture the phenology of the surrounding region in excess of 6ha. This analysis was carried out over a single growing season in the in the Rocky Mountains of western Alberta, Canada.