Ten best practices for effective phenological research.

The number and diversity of phenological studies has increased rapidly in recent years. Innovative experiments, field studies, citizen science projects, and analyses of newly available historical data are contributing insights that advance our understanding of ecological and evolutionary responses to the environment, particularly climate change. However, many phenological data sets have peculiarities that are not immediately obvious and can lead to mistakes in analyses and interpretation of results. This paper aims to help researchers, especially those new to the field of phenology, understand challenges and practices that are crucial for effective studies. For example, researchers may fail to account for sampling biases in phenological data, struggle to choose or design a volunteer data collection strategy that adequately fits their project's needs, or combine data sets in inappropriate ways. We describe ten best practices for designing studies of plant and animal phenology, evaluating data quality, and analyzing data. Practices include accounting for common biases in data, using effective citizen or community science methods, and employing appropriate data when investigating phenological mismatches. We present these best practices to help researchers entering the field take full advantage of the wealth of available data and approaches to advance our understanding of phenology and its implications for ecology.

Digital Extended Specimens: Enabling an Extensible Network of Biodiversity Data Records as Integrated Digital Objects on the Internet.

The early twenty-first century has witnessed massive expansions in availability and accessibility of digital data in virtually all domains of the biodiversity sciences. Led by an array of asynchronous digitization activities spanning ecological, environmental, climatological, and biological collections data, these initiatives have resulted in a plethora of mostly disconnected and siloed data, leaving to researchers the tedious and time-consuming manual task of finding and connecting them in usable ways, integrating them into coherent data sets, and making them interoperable. The focus to date has been on elevating analog and physical records to digital replicas in local databases prior to elevating them to ever-growing aggregations of essentially disconnected discipline-specific information. In the present article, we propose a new interconnected network of digital objects on the Internet-the Digital Extended Specimen (DES) network-that transcends existing aggregator technology, augments the DES with third-party data through machine algorithms, and provides a platform for more efficient research and robust interdisciplinary discovery.

Conservation ethics in the time of the pandemic: Does increasing remote access advance social justice?

The COVID-19 pandemic is stimulating improvements in remote access and use of technology in conservation-related programs and research. In many cases, organizations have intended for remote engagement to benefit groups that have been marginalized in the sciences. But are they? It is important to consider how remote access affects social justice in conservation biology-i.e., the principle that all people should be equally respected and valued in conservation organizations, programs, projects, and practices. To support such consideration, we describe a typology of justice-oriented principles that can be used to examine social justice in a range of conservation activities. We apply this typology to three conservation areas: (1) remote access to US national park educational programs and data; (2) digitization of natural history specimens and their use in conservation research; and (3) remote engagement in conservation-oriented citizen science. We then address the questions: Which justice-oriented principles are salient in which conservation contexts or activities? How can those principles be best realized in those contexts or activities? In each of the three areas we examined, remote access increased participation, but access and benefits were not equally distributed and unanticipated consequences have not been adequately addressed. We identify steps that can and are being taken to advance social justice in conservation, such as assessing programs to determine if they are achieving their stated social justice-oriented aims and revising initiatives as needed. The framework that we present could be used to assess the social justice dimensions of many conservation programs, institutions, practices, and policies.

The growing and vital role of botanical gardens in climate change research.

Botanical gardens make unique contributions to climate change research, conservation, and public engagement. They host unique resources, including diverse collections of plant species growing in natural conditions, historical records, and expert staff, and attract large numbers of visitors and volunteers. Networks of botanical gardens spanning biomes and continents can expand the value of these resources. Over the past decade, research at botanical gardens has advanced our understanding of climate change impacts on plant phenology, physiology, anatomy, and conservation. For example, researchers have utilized botanical garden networks to assess anatomical and functional traits associated with phenological responses to climate change. New methods have enhanced the pace and impact of this research, including phylogenetic and comparative methods, and online databases of herbarium specimens and photographs that allow studies to expand geographically, temporally, and taxonomically in scope. Botanical gardens have grown their community and citizen science programs, informing the public about climate change and monitoring plants more intensively than is possible with garden staff alone. Despite these advances, botanical gardens are still underutilized in climate change research. To address this, we review recent progress and describe promising future directions for research and public engagement at botanical gardens.

Macrophenology: insights into the broad-scale patterns, drivers, and consequences of phenology.

Plant phenology research has surged in recent decades, in part due to interest in phenological sensitivity to climate change and the vital role phenology plays in ecology. Many local-scale studies have generated important findings regarding the physiology, responses, and risks associated with shifts in plant phenology. By comparison, our understanding of regional- and global-scale phenology has been largely limited to remote sensing of green-up without the ability to differentiate among plant species. However, a new generation of analytical tools and data sources-including enhanced remote sensing products, digitized herbarium specimen data, and public participation in science-now permits investigating patterns and drivers of phenology across extensive taxonomic, temporal, and spatial scales, in an emerging field that we call macrophenology. Recent studies have highlighted how phenology affects dynamics at broad scales, including species interactions and ranges, carbon fluxes, and climate. At the cusp of this developing field of study, we review the theoretical and practical advances in four primary areas of plant macrophenology: (1) global patterns and shifts in plant phenology, (2) within-species changes in phenology as they mediate species' range limits and invasions at the regional scale, (3) broad-scale variation in phenology among species leading to ecological mismatches, and (4) interactions between phenology and global ecosystem processes. To stimulate future research, we describe opportunities for macrophenology to address grand challenges in each of these research areas, as well as recently available data sources that enhance and enable macrophenology research.

COVID-19 pandemic impacts on conservation research, management, and public engagement in US national parks.

The COVID-19 pandemic has disrupted the timing and substance of conservation research, management, and public engagement in protected areas around the world. This disruption is evident in US national parks, which play a key role in protecting natural and cultural resources and providing outdoor experiences for the public. Collectively, US national parks protect 34 million ha, host more than 300 million visits annually, and serve as one of the world's largest informal education organizations. The pandemic has altered park conditions and operations in a variety of ways. Shifts in operational conditions related to safety issues, reduced staffing, and decreased park revenues have forced managers to make difficult trade-offs among competing priorities. Long-term research and monitoring of the health of ecosystems and wildlife populations have been interrupted. Time-sensitive management practices, such as control of invasive plants and restoration of degraded habitat, have been delayed. And public engagement has largely shifted from in-person experiences to virtual engagement through social media and other online interactions. These changes pose challenges for accomplishing important science, management, and public engagement goals, but they also create opportunities for developing more flexible monitoring programs and inclusive methods of public engagement. The COVID-19 pandemic reinforces the need for strategic science, management planning, flexible operations, and online public engagement to help managers address rapid and unpredictable challenges.

Machine Learning Using Digitized Herbarium Specimens to Advance Phenological Research.

Machine learning (ML) has great potential to drive scientific discovery by harvesting data from images of herbarium specimens-preserved plant material curated in natural history collections-but ML techniques have only recently been applied to this rich resource. ML has particularly strong prospects for the study of plant phenological events such as growth and reproduction. As a major indicator of climate change, driver of ecological processes, and critical determinant of plant fitness, plant phenology is an important frontier for the application of ML techniques for science and society. In the present article, we describe a generalized, modular ML workflow for extracting phenological data from images of herbarium specimens, and we discuss the advantages, limitations, and potential future improvements of this workflow. Strategic research and investment in specimen-based ML methods, along with the aggregation of herbarium specimen data, may give rise to a better understanding of life on Earth.

Corrigendum: The Extended Specimen Network: A Strategy to Enhance US Biodiversity Collections, Promote Research and Education.

[This corrects the article DOI: 10.1093/biosci/biz140.].

Worldwide Engagement for Digitizing Biocollections (WeDigBio): The Biocollections Community's Citizen-Science Space on the Calendar.

The digitization of biocollections is a critical task with direct implications for the global community who use the data for research and education. Recent innovations to involve citizen scientists in digitization increase awareness of the value of biodiversity specimens; advance science, technology, engineering, and math literacy; and build sustainability for digitization. In support of these activities, we launched the first global citizen-science event focused on the digitization of biodiversity specimens: Worldwide Engagement for Digitizing Biocollections (WeDigBio). During the inaugural 2015 event, 21 sites hosted events where citizen scientists transcribed specimen labels via online platforms (DigiVol, Les Herbonautes, Notes from Nature, the Smithsonian Institution's Transcription Center, and Symbiota). Many citizen scientists also contributed off-site. In total, thousands of citizen scientists around the world completed over 50,000 transcription tasks. Here, we present the process of organizing an international citizen-science event, an analysis of the event's effectiveness, and future directions-content now foundational to the growing WeDigBio event.

Leaf out times of temperate woody plants are related to phylogeny, deciduousness, growth habit and wood anatomy.

Leaf out phenology affects a wide variety of ecosystem processes and ecological interactions and will take on added significance as leaf out times increasingly shift in response to warming temperatures associated with climate change. There is, however, relatively little information available on the factors affecting species differences in leaf out phenology. An international team of researchers from eight Northern Hemisphere temperate botanical gardens recorded leaf out dates of c. 1600 woody species in 2011 and 2012. Leaf out dates in woody species differed by as much as 3 months at a single site and exhibited strong phylogenetic and anatomical relationships. On average, angiosperms leafed out earlier than gymnosperms, deciduous species earlier than evergreen species, shrubs earlier than trees, diffuse and semi-ring porous species earlier than ring porous species, and species with smaller diameter xylem vessels earlier than species with larger diameter vessels. The order of species leaf out was generally consistent between years and among sites. As species distribution and abundance shift due to climate change, interspecific differences in leaf out phenology may affect ecosystem processes such as carbon, water, and nutrient cycling. Our open access leaf out data provide a critical framework for monitoring and modelling such changes going forward.

Determining past leaf-out times of New England's deciduous forests from herbarium specimens.

UNLABELLED: • PREMISE OF THE STUDY: There is great interest in studying leaf-out times of temperate forests because of the importance of leaf-out in controlling ecosystem processes, especially in the face of a changing climate. Remote sensing and modeling, combined with weather records and field observations, are increasing our knowledge of factors affecting variation in leaf-out times. Herbarium specimens represent a potential new source of information to determine whether the variation in leaf-out times observed in recent decades is comparable to longer time frames over past centuries.• METHODS: Here we introduce the use of herbarium specimens as a method for studying long-term changes in leaf-out times of deciduous trees. We collected historical leaf-out data for the years 1834-2008 from common deciduous trees in New England using 1599 dated herbarium specimens with young leaves.• KEY RESULTS: We found that leaf-out dates are strongly affected by spring temperature, with trees leafing out 2.70 d earlier for each degree C increase in mean April temperature. For each degree C increase in local temperature, trees leafed out 2.06 d earlier. Additionally, the mean response of leaf-out dates across all species and sites over time was 0.4 d earlier per decade. Our results are of comparable magnitude to results from studies using remote sensing and direct field observations.• CONCLUSIONS: Across New England, mean leaf-out dates varied geographically in close correspondence with those observed in studies using satellite data. This study demonstrates that herbarium specimens can be a valuable source of data on past leaf-out times of deciduous trees.

Cranberry flowering times and climate change in southern Massachusetts.

Plants in wild and agricultural settings are being affected by the warmer temperatures associated with climate change. Here we examine the degree to which the iconic New England cranberry, Vaccinium macrocarpon, is exhibiting signs of altered flowering phenology. Using contemporary records from commercial cranberry bogs in southeastern Massachusetts in the United States, we found that cranberry plants are responsive to temperature. Flowering is approximately 2 days earlier for each 1 °C increase in May temperature. We also investigated the relationship between cranberry flowering and flight dates of the bog copper, Lycaena epixanthe-a butterfly dependent upon cranberry plants in its larval stage. Cranberry flowering and bog copper emergence were found to be changing disproportionately over time, suggesting a potential ecological mismatch. The pattern of advanced cranberry flowering over time coupled with increased temperature has implications not only for the relationship between cranberry plants and their insect associates but also for agricultural crops in general and for the commercial cranberry industry.

Citizen science needs a name change.

Amidst attention towards improving equality, inclusivity, and diversity, citizen science is woefully anachronistic in its name. There is a critical need for this field to distance itself from the exclusionary nature of the term 'citizen'. We provide reasoning for abandoning this term and an outline for adopting a new name.

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.

Envisaging a global infrastructure to exploit the potential of digitised collections.

Tens of millions of images from biological collections have become available online over the last two decades. In parallel, there has been a dramatic increase in the capabilities of image analysis technologies, especially those involving machine learning and computer vision. While image analysis has become mainstream in consumer applications, it is still used only on an artisanal basis in the biological collections community, largely because the image corpora are dispersed. Yet, there is massive untapped potential for novel applications and research if images of collection objects could be made accessible in a single corpus. In this paper, we make the case for infrastructure that could support image analysis of collection objects. We show that such infrastructure is entirely feasible and well worth investing in.