Phenology research for natural resource management in the United States

Disorder or a new order: How climate change affects phenological variability

Advancing spring phenology is a well documented consequence of anthropogenic climate change, but it is not well understood how climate change will affect the variability of phenology year to year. Species' phenological timings reflect the adaptation to a broad suite of abiotic needs (e.g., thermal energy) and biotic interactions (e.g., predation and pollination), and changes in patterns of variability may disrupt those adaptations and interactions. Here, we present a geographically and taxonomically broad analysis of phenological shifts, temperature sensitivity, and changes in interannual variability encompassing nearly 10,000 long-term phenology time series representing more than 1000 species across much of the Northern Hemisphere. We show that the timings of leaf-out, flowering, insect first-occurrence, and bird arrival were the most sensitive to temperature variation and have advanced at the fastest pace for early-season species in colder and less seasonal regions. We did not find evidence for changing variability in warmer years in any phenophase groups, although leaf-out and flower phenology have become moderately but significantly less variable over time. Our findings suggest that climate change has not to this point fundamentally altered the patterns of interannual phenological variability.

Flowering time advances since the 1970s in a sagebrush steppe community: Implications for management and restoration

Climate change is widely known to affect plant phenology, but little is known about how these impacts manifest in the widespread sagebrush ecosystem of the Western United States, which supports a number of wildlife species of concern. Shifts in plant phenology can trigger consequences for the plants themselves as well as the communities of consumers that depend upon them. We assembled historical observations of first-flowering dates for 51 species collected in the 1970s and 1980s in a montane sagebrush community in the Greater Yellowstone Ecosystem and compared these to contemporary phenological observations targeting the same species and locations (2016-2019). We also assembled regional climate data (average spring temperature, day of spring snowmelt, and growing degree days) and tested the relationship between first-flowering time and these variables for each species. We observed the largest change in phenology in early-spring flowers, which, as a group, bloomed on average 17 days earlier, and as much as 36 days earlier, in the contemporary data set. Mid-summer flowers bloomed on average 10 days earlier, nonnative species 15 days earlier, and berry-producing shrubs 5 days earlier, while late summer flowering plants did not shift. The greatest correlates of early-spring and mid-summer flowering were average spring temperature and day of snowmelt, which was 21 days earlier, on average, in 2016-2019 relative to the 1973-1978 observations. The shifts in flowering phenology that we observed could indicate developing asynchronies or novel synchronies of these plant resources and wildlife species of conservation concern, including Greater Sage-grouse, whose nesting success is tied to availability of spring forbs; grizzly bears, which rely heavily on berries for their fall diet; and pollinators. This underscores the importance of maintaining a diverse portfolio of native plants in terms of species composition, genetics, phenological responsiveness to climatic cues, and ecological importance to key wildlife and pollinator species. Redundancy within ecological niches may also be important considering that species roles in the community may shift as climate change affects them differently. These considerations are particularly relevant to restoration and habitat-enhancement projects in sagebrush communities across western North America.

Science and Management Advancements Made Possible by the USA National Phenology Network's Nature's Notebook Platform

The USA National Phenology Network was established in 2007 to formalize standardized phenology monitoring across the country. The aims of the network are to collect, store, and share phenology data and information to support scientific discovery, decision-making, an appreciation for phenology, and equitable engagement within the network. To support these aims, the network launched Nature's Notebook, a rigorous platform for monitoring plant and animal phenology, in 2009.

Since the launch of Nature's Notebook, participants across the country have contributed over 30 million phenology records. The participants range from backyard observers with an interest in nature to researchers and natural resource managers asking specific questions. We survey the breadth of studies and applied decisions that have used Nature's Notebook and the consequent data. The dimensionality of the data set maintained by the network is a function of Nature's Notebook users; this insight is key to shaping the network’s future data collection activities.

Spring understory herbs flower later in intensively managed forests

Many organisms respond to anthropogenic environmental change through shifts in their phenology. In plants, flowering is largely driven by temperature, and therefore affected by climate change. However, on smaller scales climatic conditions are also influenced by other factors, including habitat structure. A group of plants with a particularly distinct phenology are the understory herbs in temperate European forests. In these forests, management alters tree species composition (often replacing deciduous with coniferous species) and homogenizes stand structure, and as a consequence changes light conditions and microclimate. Forest management should thus also affect the phenology of understory herbs. To test this, we recorded the flowering phenology of 16 early-flowering herbs on 100 forest plots varying in management intensity, from near-natural to intensely managed forests, in central and southern Germany. We found that in forest stands with a high management intensity, such as Norway spruce plantations, the plants flowered on average about 2 weeks later than in unmanaged forests. This was largely because management also affected microclimate (e.g., spring temperatures of 5.9°C in managed coniferous, 6.7 in managed deciduous, and 7.0°C in unmanaged deciduous plots), which in turn affected phenology, with plants flowering later on colder and moister forest stands (+4.5 d per -1°C and 2.7 d per 10% humidity increase). Among forest characteristics, the percentage of conifers had the greatest influence on microclimate, but also the age, overall crown projection area, structural complexity and spatial distribution of the forest stands. Our study indicates that forest management alters plant phenology, with potential far-reaching consequences for the ecology and evolution of understorey communities. More generally, our study demonstrates that besides climate change other drivers of environmental change, too, can influence the phenology of organisms.

Coral damage by recreational diving activities in a Marine Protected Area of India: Unaccountability leading to 'tragedy of the not so commons'

Globally, coral reefs have drastically degraded due to local and global environmental stressors. Concurrently, coral reef tourism is rapidly growing in developing economies, which is one of many anthropogenic stressors impacting reefs. At the Malvan Marine Sanctuary, a Marine Protected Area (MPA) on the West coast of India, we investigated the impact of recreational diving on the reef from 2016 to 2019. To evaluate the diver's underwater behavior, a novel approach was used, wherein the video-log broadcasting website www.youtube.com was perused. Evidential proof substantiates heavy physical damage to corals because of recreational diving activity, which may lead to the collapse of coral habitat if it continues unabated. This resource depletion ironically elevates the economy of dependents averting consequences due to lost corals, thus making this a 'tragedy' for corals which are not meant to be 'commons'. The study asserts need for proactive conservation efforts with stringent implementation and restoration initiatives in this MPA.

How well do the spring indices predict phenological activity across plant species?

The spring indices, models that represent the onset of spring season biological activity, were developed using a long-term observational record from the mid-to-late twentieth century of three species of lilacs and honeysuckles contributed by volunteer observers across the nation. The USA National Phenology Network (USA-NPN) produces and freely delivers maps of spring index onset dates at fine spatial scale for the USA. These maps are used widely in natural resource planning and management applications. The extent to which the models represent activity in a broad suite of plant species is not well documented. In this study, we used a rich record of observational plant phenology data (37,819 onset records) collected in recent years (1981-2017) to evaluate how well gridded maps of the spring index models predict leaf and flowering onset dates in (a) 19 species of ecologically important, broadly distributed deciduous trees and shrubs, and (b) the lilac and honeysuckle species used to construct the models. The extent to which the spring indices predicted vegetative and reproductive phenology varied by species and with latitude, with stronger relationships revealed for shrubs than trees and with the Bloom Index compared to the Leaf Index, and reduced concordance between the indices at higher latitudes. These results allow us to use the indices as indicators of when to expect activity across widely distributed species and can serve as a yardstick to assess how future changes in the timing of spring will impact a broad array of trees and shrubs across the USA.

Exploring differences in spatial patterns and temporal trends of phenological models at continental scale using gridded temperature time-series

Phenological models are widely used to estimate the influence of weather and climate on plant development. The goodness of fit of phenological models often is assessed by considering the root-mean-square error (RMSE) between observed and predicted dates. However, the spatial patterns and temporal trends derived from models with similar RMSE may vary considerably. In this paper, we analyse and compare patterns and trends from a suite of temperature-based phenological models, namely extended spring indices, thermal time and photothermal time models. These models were first calibrated using lilac leaf onset observations for the period 1961-1994. Next, volunteered phenological observations and daily gridded temperature data were used to validate the models. After that, the two most accurate models were used to evaluate the patterns and trends of leaf onset for the conterminous US over the period 2000-2014. Our results show that the RMSEs of extended spring indices and thermal time models are similar and about 2 days lower than those produced by the other models. Yet the dates of leaf out produced by each of the models differ by up to 11 days, and the trends differ by up to a week per decade. The results from the histograms and difference maps show that the statistical significance of these trends strongly depends on the type of model applied. Therefore, further work should focus on the development of metrics that can quantify the difference between patterns and trends derived from spatially explicit phenological models. Such metrics could subsequently be used to validate phenological models in both space and time. Also, such metrics could be used to validate phenological models in both space and time.

Differential changes in the onset of spring across US National Wildlife Refuges and North American migratory bird flyways

Warming temperatures associated with climate change can have indirect effects on migratory birds that rely on seasonally available food resources and habitats that vary across spatial and temporal scales. We used two heat-based indices of spring onset, the First Leaf Index (FLI) and the First Bloom Index (FBI), as proxies of habitat change for the period 1901 to 2012 at three spatial scales: the US National Wildlife Refuge System; the four major bird migratory flyways in North America; and the seasonal ranges (i.e., breeding and non-breeding grounds) of two migratory bird species, Blue-winged Warbler (Vermivora cyanoptera) and Whooping Crane (Grus americana). Our results show that relative to the historical range of variability, the onset of spring is now earlier in 76% of all wildlife refuges and extremely early (i.e., exceeding 95% of historical conditions) in 49% of refuges. In all flyways but the Pacific, the rate of spring advance is generally greater at higher latitudes than at lower latitudes. This differential rate of advance in spring onset is most pronounced in the Atlantic flyway, presumably because of a "warming hole" in the southeastern US. Both FLI and FBI have advanced markedly in the breeding ranges-but not the non-breeding ranges-of the two selected bird species, albeit with considerable intra-range variation. Differences among species in terms of migratory patterns and the location and extent of seasonal habitats, as well as shifts in habitat conditions over time, may complicate predictions of the vulnerability of migratory birds to climate change effects. This study provides insight into how differential shifts in the phenology of disparate but linked habitats could inform local- to landscape-scale management strategies for the conservation of migratory bird populations.

How training citizen scientists affects the accuracy and precision of phenological data

Monitoring plant and animal phenology is a critical step to anticipating and predicting changes in species interactions and biodiversity. Because phenology necessarily involves frequent and repeated observations over time, citizen scientists have become a vital part of collecting phenological data. However, there is still concern over the accuracy and precision of citizen science data. It is possible that training citizen scientists can improve data quality though there are few comparisons of trained and untrained citizen scientists in the ability of each to accurately and precisely measure phenology. We assessed how three types of observers-experts, trained citizen scientists that make repeated observations, and untrained citizen scientists making once-per-year observations-differ in quantifying temporal change in flower and fruit abundance of American mountain ash trees (Sorbus americana Marsh.) and arthropods in Acadia National Park, Maine, USA. We found that trained more so than untrained citizen science observers over- or under-estimated abundances leading to precise but inaccurate characterizations of phenological patterns. Our results suggest a new type of bias induced by repeated observations: A type of learning takes place that reduces the independence of observations taken on different trees or different dates. Thus, in this and many other cases, having individuals make one-off observations of marked plants may produce data as good if not better than individuals making repeated observations. For citizen science programs related to phenology, our results underscore the importance of (a) attracting the most number of observers possible even if they only make one observation, (b) producing easy-to-use and informative data sheets, and

The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data

Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

Snowmelt timing, phenology, and growing season length in conifer forests of Crater Lake National Park, USA

Anthropogenic climate change is having significant impacts on montane and high-elevation areas globally. Warmer winter temperatures are driving reduced snowpack in the western USA with broad potential impacts on ecosystem dynamics of particular concern for protected areas. Vegetation phenology is a sensitive indicator of ecological response to climate change and is associated with snowmelt timing. Human monitoring of climate impacts can be resource prohibitive for land management agencies, whereas remotely sensed phenology observations are freely available at a range of spatiotemporal scales. Little work has been done in regions dominated by evergreen conifer cover, which represents many mountain regions at temperate latitudes. We used moderate resolution imaging spectroradiometer (MODIS) data to assess the influence of snowmelt timing and elevation on five phenology metrics (green up, maximum greenness, senescence, dormancy, and growing season length) within Crater Lake National Park, Oregon, USA from 2001 to 2012. Earlier annual mean snowmelt timing was significantly correlated with earlier onset of green up at the landscape scale. Snowmelt timing and elevation have significant explanatory power for phenology, though with high variability. Elevation has a moderate control on early season indicators such as snowmelt timing and green up and less on late-season variables such as senescence and growing season length. PCA results show that early season indicators and late season indicators vary independently. These results have important implications for ecosystem dynamics, management, and conservation, particularly of species such as whitebark pine (Pinus albicaulis) in alpine and subalpine areas.

The rise of phenology with climate change: an evaluation of IJB publications

In recent decades, phenology has become an important tool by which to measure both the impact of climate change on ecosystems and the feedback of ecosystems to the climate system. However, there has been little attempt to date to systematically quantify the increase in the number of scientific publications with a focus on phenology and climate change. In order to partially address this issue, we examined the number of articles (original papers, reviews and short communications) containing the terms 'phenology' and 'climate change' in the title, abstract or keywords, published in the International Journal of Biometeorology in the 60 years since its inception in 1957. We manually inspected all issues prior to 1987 for the search terms and subsequently used the search facility on the Web of Science online database. The overall number of articles published per decade remained relatively constant (255-378) but rose rapidly to 1053 in the most recent decade (2007-2016), accompanied by an increase (41-172) in the number of articles containing the search terms. A number of factors may have contributed to this rise, including the recognition of the value of phenology as an indicator of climate change and the initiation in 2010 of a series of conferences focusing on phenology which subsequently led to two special issues of the journal. The word 'phenology' was in use from the first issue, whereas 'climate change' only emerged in 1987 and peaked in 2014. New technologies such as satellite remote sensing and the internet led to an expansion of and greater access to a growing reservoir of phenological information. The application of phenological data included determining the impact of warming of phenophases, predicting wine quality and the pollen season, demonstrating the potential for mismatch to occur and both reconstructing and forecasting climate. Even though this analysis was limited to one journal, it is likely to be indicative of a similar trend across other scientific publications.

USA National Phenology Network's volunteer-contributed observations yield predictive models of phenological transitions

Purpose

In support of science and society, the USA National Phenology Network (USA-NPN) maintains a rapidly growing, continental-scale, species-rich dataset of plant and animal phenology observations that with over 10 million records is the largest such database in the United States. The aim of this study was to explore the potential that exists in the broad and rich volunteer-collected dataset maintained by the USA-NPN for constructing models predicting the timing of phenological transition across species’ ranges within the continental United States. Contributed voluntarily by professional and citizen scientists, these opportunistically collected observations are characterized by spatial clustering, inconsistent spatial and temporal sampling, and short temporal depth (2009-present). Whether data exhibiting such limitations can be used to develop predictive models appropriate for use across large geographic regions has not yet been explored.

Methods

We constructed predictive models for phenophases that are the most abundant in the database and also relevant to management applications for all species with available data, regardless of plant growth habit, location, geographic extent, or temporal depth of the observations. We implemented a very basic model formulation—thermal time models with a fixed start date.

Results

Sufficient data were available to construct 107 individual species × phenophase models. Remarkably, given the limited temporal depth of this dataset and the simple modeling approach used, fifteen of these models (14%) met our criteria for model fit and error. The majority of these models represented the “breaking leaf buds” and “leaves” phenophases and represented shrub or tree growth forms. Accumulated growing degree day (GDD) thresholds that emerged ranged from 454 GDDs (Amelanchier canadensis-breaking leaf buds) to 1,300 GDDs (Prunus serotina-open flowers). Such candidate thermal time thresholds can be used to produce real-time and short-term forecast maps of the timing of these phenophase transition. In addition, many of the candidate models that emerged were suitable for use across the majority of the species’ geographic ranges. Real-time and forecast maps of phenophase transitions could support a wide range of natural resource management applications, including invasive plant management, issuing asthma and allergy alerts, and anticipating frost damage for crops in vulnerable states.

Implications

Our finding that several viable thermal time threshold models that work across the majority of the species ranges could be constructed from the USA-NPN database provides clear evidence that great potential exists this dataset to develop more enhanced predictive models for additional species and phenophases. Further, the candidate models that emerged have immediate utility for supporting a wide range of management applications.