The California Phenology Project: Tracking Plant Responses to Climate Change

A new phenological metric for use in pheno-climatic models: A case study using herbarium specimens of Streptanthus tortuosus

PREMISE

Herbarium specimens have been used to detect climate-induced shifts in flowering time by using the day of year of collection (DOY) as a proxy for first or peak flowering date. Variation among herbarium sheets in their phenological status, however, undermines the assumption that DOY accurately represents any particular phenophase. Ignoring this variation can reduce the explanatory power of pheno-climatic models (PCMs) designed to predict the effects of climate on flowering date.

METHODS

Here we present a protocol for the phenological scoring of imaged herbarium specimens using an ImageJ plugin, and we introduce a quantitative metric of a specimen's phenological status, the phenological index (PI), which we use in PCMs to control for phenological variation among specimens of Streptanthus tortuosus (Brassicaceeae) when testing for the effects of climate on DOY. We demonstrate that including PI as an independent variable improves model fit.

RESULTS

Including PI in PCMs increased the model R 2 relative to PCMs that excluded PI; regression coefficients for climatic parameters, however, remained constant.

DISCUSSION

Our protocol provides a simple, quantitative phenological metric for any observed plant. Including PI in PCMs increases R 2 and enables predictions of the DOY of any phenophase under any specified climatic conditions.

The potential for phenological mismatch between a perennial herb and its ground-nesting bee pollinator

Climate change may alter the timing of flowering and pollinator activity to differing degrees, resulting in phenological mismatches between mutualistic partners. Assessing the potential for such mismatches requires an understanding of the environmental factors that cue flowering and pollinator activity. Biological context is key to determining specific impacts of climate change, and therefore it is important to study mutualisms with pollinators of different nesting biologies. Our study focused on the phenology of two mutualists native to the coastal dunes of northwestern California: the silky beach pea (Lathyrus littoralis) and its main pollinator, the ground-nesting solitary silver bee (Habropoda miserabilis). We measured the current phenological overlap between the two species and took advantage of local fine-scale spatial variation in the timing of flowering and bee nesting activity to develop predictive models of flowering and flight period timing based on variation in soil temperature and moisture. Temperature best predicted both flowering and bee activity, although soil moisture influenced the timing as well. Comparison of linear regression slopes of phenology against temperature suggests that bee nesting time is more sensitive to differences in seasonal maximum temperatures, and may advance more rapidly than flowering with temperature increases. Although the current phenological overlap between the two species is high, this differential response to temperature could result in a decrease in overlap with climate warming. Our results highlight that nesting biology may be critical in determining impacts of climate change on pollination mutualisms, as ground-nesting bees may respond differently than other bee species. In addition, this work reveals the utility of studying bee species that nest in aggregations for understanding ground-nesting bee phenology.

Dynamically downscaling predictions for deciduous tree leaf emergence in California under current and future climate

Models that predict the timing of deciduous tree leaf emergence are typically very sensitive to temperature. However, many temperature data products, including those from climate models, have been developed at a very coarse spatial resolution. Such coarse-resolution temperature products can lead to highly biased predictions of leaf emergence. This study investigates how dynamical downscaling of climate models impacts simulations of deciduous tree leaf emergence in California. Models for leaf emergence are forced with temperatures simulated by a general circulation model (GCM) at ~200-km resolution for 1981-2000 and 2031-2050 conditions. GCM simulations are then dynamically downscaled to 32- and 8-km resolution, and leaf emergence is again simulated. For 1981-2000, the regional average leaf emergence date is 30.8 days earlier in 32-km simulations than in ~200-km simulations. Differences between the 32 and 8 km simulations are small and mostly local. The impact of downscaling from 200 to 8 km is ~15 % smaller in 2031-2050 than in 1981-2000, indicating that the impacts of downscaling are unlikely to be stationary.

Historical changes in flowering phenology are governed by temperature × precipitation interactions in a widespread perennial herb in western North America

For most species, a precise understanding of how climatic parameters determine the timing of seasonal life cycle stages is constrained by limited long-term data. Further, most long-term studies of plant phenology that have examined relationships between phenological timing and climate have been local in scale or have focused on single climatic parameters. Herbarium specimens, however, can expand the temporal and spatial coverage of phenological datasets. Using Trillium ovatum specimens collected over > 100 yr across its native range, we analyzed how seasonal climatic conditions (mean minimum temperature (Tmin ), mean maximum temperature and total precipitation (PPT)) affect flowering phenology. We then examined long-term changes in climatic conditions and in the timing of flowering across T. ovatum's range. Warmer Tmin advanced flowering, whereas higher PPT delayed flowering. However, Tmin and PPT were shown to interact: the advancing effect of warmer Tmin was strongest where PPT was highest, and the delaying effect of higher PPT was strongest where Tmin was coldest. The direction of temporal change in climatic parameters and in the timing of flowering was dependent on geographic location. Tmin , for example, decreased across the observation period in coastal regions, but increased in inland areas. Our results highlight the complex effects of climate and geographic location on phenology.

Is there a weekend bias in clutch-initiation dates from citizen science? Implications for studies of avian breeding phenology

Accurate phenology data, such as the timing of migration and reproduction, is important for understanding how climate change influences birds. Given contradictory findings among localized studies regarding mismatches in timing of reproduction and peak food supply, broader-scale information is needed to understand how whole species respond to environmental change. Citizen science-participation of the public in genuine research-increases the geographic scale of research. Recent studies, however, showed weekend bias in reported first-arrival dates for migratory songbirds in databases created by citizen-science projects. I investigated whether weekend bias existed for clutch-initiation dates for common species in US citizen-science projects. Participants visited nests on Saturdays more frequently than other days. When participants visited nests during the laying stage, biased timing of visits did not translate into bias in estimated clutch-initiation dates, based on back-dating with the assumption of one egg laid per day. Participants, however, only visited nests during the laying stage for 25% of attempts of cup-nesting species and 58% of attempts in nest boxes. In some years, in lieu of visit data, participants provided their own estimates of clutch-initiation dates and were asked "did you visit the nest during the laying period?" Those participants who answered the question provided estimates of clutch-initiation dates with no day-of-week bias, irrespective of their answer. Those who did not answer the question were more likely to estimate clutch initiation on a Saturday. Data from citizen-science projects are useful in phenological studies when temporal biases can be checked and corrected through protocols and/or analytical methods.

Phenology research for natural resource management in the United States

Natural resource professionals in the United States recognize that climate-induced changes in phenology can substantially affect resource management. This is reflected in national climate change response plans recently released by major resource agencies. However, managers on-the-ground are often unclear about how to use phenological information to inform their management practices. Until recently, this was at least partially due to the lack of broad-based, standardized phenology data collection across taxa and geographic regions. Such efforts are now underway, albeit in very early stages. Nonetheless, a major hurdle still exists: phenology-linked climate change research has focused more on describing broad ecological changes rather than making direct connections to local to regional management concerns. To help researchers better design relevant research for use in conservation and management decision-making processes, we describe phenology-related research topics that facilitate "actionable" science. Examples include research on evolution and phenotypic plasticity related to vulnerability, the demographic consequences of trophic mismatch, the role of invasive species, and building robust ecological forecast models. Such efforts will increase phenology literacy among on-the-ground resource managers and provide information relevant for short- and long-term decision-making, particularly as related to climate response planning and implementing climate-informed monitoring in the context of adaptive management. In sum, we argue that phenological information is a crucial component of the resource management toolbox that facilitates identification and evaluation of strategies that will reduce the vulnerability of natural systems to climate change. Management-savvy researchers can play an important role in reaching this goal.

Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications

Phenology offers critical insights into the responses of species to climate change; shifts in species' phenologies can result in disruptions to the ecosystem processes and services upon which human livelihood depends. To better detect such shifts, scientists need long-term phenological records covering many taxa and across a broad geographic distribution. To date, phenological observation efforts across the USA have been geographically limited and have used different methods, making comparisons across sites and species difficult. To facilitate coordinated cross-site, cross-species, and geographically extensive phenological monitoring across the nation, the USA National Phenology Network has developed in situ monitoring protocols standardized across taxonomic groups and ecosystem types for terrestrial, freshwater, and marine plant and animal taxa. The protocols include elements that allow enhanced detection and description of phenological responses, including assessment of phenological "status", or the ability to track presence-absence of a particular phenophase, as well as standards for documenting the degree to which phenological activity is expressed in terms of intensity or abundance. Data collected by this method can be integrated with historical phenology data sets, enabling the development of databases for spatial and temporal assessment of changes in status and trends of disparate organisms. To build a common, spatially, and temporally extensive multi-taxa phenological data set available for a variety of research and science applications, we encourage scientists, resources managers, and others conducting ecological monitoring or research to consider utilization of these standardized protocols for tracking the seasonal activity of plants and animals.