Warming experiments are increasingly relied on to estimate plant responses to global climate change. For experiments to provide meaningful predictions of future responses, they should reflect the empirical record of responses to temperature variability and recent warming, including advances in the timing of flowering and leafing. We compared phenology (the timing of recurring life history events) in observational studies and warming experiments spanning four continents and 1,634 plant species using a common measure of temperature sensitivity (change in days per degree Celsius). We show that warming experiments underpredict advances in the timing of flowering and leafing by 8.5-fold and 4.0-fold, respectively, compared with long-term observations. For species that were common to both study types, the experimental results did not match the observational data in sign or magnitude. The observational data also showed that species that flower earliest in the spring have the highest temperature sensitivities, but this trend was not reflected in the experimental data. These significant mismatches seem to be unrelated to the study length or to the degree of manipulated warming in experiments. The discrepancy between experiments and observations, however, could arise from complex interactions among multiple drivers in the observational data, or it could arise from remediable artefacts in the experiments that result in lower irradiance and drier soils, thus dampening the phenological responses to manipulated warming. Our results introduce uncertainty into ecosystem models that are informed solely by experiments and suggest that responses to climate change that are predicted using such models should be re-evaluated.

Forecasting how species and ecosystems will respond to climate change has been a major aim of ecology in recent years. Much of this research has focused on phenology -the timing of life-history events. Phenology has well-demonstrated links to climate, from genetic to landscape scales; yet our ability to explain and predict variation in phenology across species, habitats and time remains poor. Here, we outline how merging approaches from ecology, climate science and evolutionary biology can advance research on phenological responses to climate variability. Using insight into seasonal and interannual climate variability combined with niche theory and community phylogenetics, we develop a predictive approach for species' reponses to changing climate. Our approach predicts that species occupying higher latitudes or the early growing season should be most sensitive to climate and have the most phylogenetically conserved phenologies. We further predict that temperate species will respond to climate change by shifting in time, while tropical species will respond by shifting space, or by evolving. Although we focus here on plant phenology, our approach is broadly applicable to ecological research of plant responses to climate variability.

Abstract. Earlier spring phenology observed in many plant species in recent decades provides compelling evidence that species are already responding to the rising global temperatures associated with anthropogenic climate change. There is great variability among species, however, in their phenological sensitivity to temperature. Species that do not phenologically ''track'' climate change may be at a disadvantage if their growth becomes limited by missed interactions with mutualists, or a shorter growing season relative to earlieractive competitors. Here, we set out to test the hypothesis that phenological sensitivity could be used to predict species performance in a warming climate, by synthesizing results across terrestrial warming experiments. We assembled data for 57 species across 24 studies where flowering or vegetative phenology was matched with a measure of species performance. Performance metrics included biomass, percent cover, number of flowers, or individual growth. We found that species that advanced their phenology with warming also increased their performance, whereas those that did not advance tended to decline in performance with warming. This indicates that species that cannot phenologically ''track'' climate may be at increased risk with future climate change, and it suggests that phenological monitoring may provide an important tool for setting future conservation priorities.

Summary1. Phenological events -defined points in the life cycle of a plant or animal -have been regarded as highly plastic traits, reflecting flexible responses to various environmental cues. 2. The ability of a species to track, via shifts in phenological events, the abiotic environment through time might dictate its vulnerability to future climate change. Understanding the predictors and drivers of phenological change is therefore critical. 3. Here, we evaluated evidence for phylogenetic conservatism -the tendency for closely related species to share similar ecological and biological attributes -in phenological traits across flowering plants. We aggregated published and unpublished data on timing of first flower and first leaf, encompassing 4000 species at 23 sites across the Northern Hemisphere. We reconstructed the phylogeny for the set of included species, first, using the software program Phylomatic, and second, from DNA data. We then quantified phylogenetic conservatism in plant phenology within and across sites. 4. We show that more closely related species tend to flower and leaf at similar times. By contrasting mean flowering times within and across sites, however, we illustrate that it is not the time of year that is conserved, but rather the phenological responses to a common set of abiotic cues. 5. Our findings suggest that species cannot be treated as statistically independent when modelling phenological responses. 6. Synthesis. Closely related species tend to resemble each other in the timing of their life-history events, a likely product of evolutionarily conserved responses to environmental cues. The search for the underlying drivers of phenology must therefore account for species' shared evolutionary histories.

Most species in all ecosystems are rare in some form.

Disparate ecological datasets are often organized into databases post hoc and then analyzed and interpreted in ways that may diverge from the purposes of the original data collections. Few studies, however, have attempted to quantify how biases inherent in these data (for example, species richness, replication, climate) affect their suitability for addressing broad scientific questions, especially in under-represented systems (for example, deserts, tropical forests) and wild communities. Here, we quantitatively compare the sensitivity of species first flowering and leafing dates to spring warmth in two phenological databases from the Northern Hemisphere. One-PEP725-has high replication within and across sites, but has low species diver- Author Contributions: All authors contributed to the study design and offered comments on this manuscript as part of the ''Forecasting Phenology'' working group funded by the National Center for Ecological Analysis and Synthesis. Author Cook conceived of and designed the study, analyzed the data, and wrote the paper. Wolkovich and Davies contributed significantly to the refinement of the ideas and analyses and assisted with the writing. Ault contributed significantly to the analyses, including processing of the GHCN climate data. Betancourt contributed significantly to the writing and study design. The first five authors are listed in order of their contributions; all other authors are listed alphabetically.*Corresponding author; e-mail: benjamin.i.cook@nasa.gov Ecosystems DOI: 10.1007/s10021-012-9584-5 Ó 2012 Springer Science+Business Media, LLC (outside the USA) sity and spans a limited climate gradient. The other-NECTAR-includes many more species and a wider range of climates, but has fewer sites and low replication of species across sites. PEP725, despite low species diversity and relatively low seasonality, accurately captures the magnitude and seasonality of warming responses at climatically similar NECTAR sites, with most species showing earlier phenological events in response to warming. In NECTAR, the prevalence of temperature responders significantly declines with increasing mean annual temperature, a pattern that cannot be detected across the limited climate gradient spanned by the PEP725 flowering and leafing data. Our results showcase broad areas of agreement between the two databases, despite significant differences in species richness and geographic coverage, while also noting areas where including data across broader climate gradients may provide added value. Such comparisons help to identify gaps in our observations and knowledge base that can be addressed by ongoing monitoring and research efforts. Resolving these issues will be critical for improving predictions in understudied and undersampled systems outside of the temperature seasonal mid-latitudes.

Issue Geodiversity (i.e., the variation in Earth's abiotic processes and features) has strong effects on biodiversity patterns. However, major gaps remain in our understanding of how relationships between biodiversity and geodiversity vary over space and time. Biodiversity data are globally sparse and concentrated in particular regions. In contrast, many forms of geodiversity can be measured continuously across the globe with satellite remote sensing. Satellite remote sensing directly measures environmental variables with grain sizes as small as tens of metres and can therefore elucidate biodiversity–geodiversity relationships across scales. Evidence We show how one important geodiversity variable, elevation, relates to alpha, beta and gamma taxonomic diversity of trees across spatial scales. We use elevation from NASA's Shuttle Radar Topography Mission (SRTM) and c . 16,000 Forest Inventory and Analysis plots to quantify spatial scaling relationships between biodiversity and geodiversity with generalized linear models (for alpha and gamma diversity) and beta regression (for beta diversity) across five spatial grains ranging from 5 to 100 km. We illustrate different relationships depending on the form of diversity; beta and gamma diversity show the strongest relationship with variation in elevation. Conclusion With the onset of climate change, it is more important than ever to examine geodiversity for its potential to foster biodiversity. Widely available satellite remotely sensed geodiversity data offer an important and expanding suite of measurements for understanding and predicting changes in different forms of biodiversity across scales. Interdisciplinary research teams spanning biodiversity, geoscience and remote sensing are well poised to advance understanding of biodiversity–geodiversity relationships across scales and guide the conservation of nature.

Tropical forests are hyper‐diverse and perform critical functions that regulate global climate, yet they are also threatened by rising temperatures. Canopy temperatures depart considerably from air temperatures, sometimes by as much as air temperatures are projected to increase by the end of this century; however, canopy temperatures are rarely measured or considered in climate change analyses. Our results from near‐continuous thermal imaging of a well‐studied tropical forest show that canopy temperatures reached a maximum of ~34°C, and exceeded maximum air temperatures by as much as 7°C. Comparing different canopy surfaces reveals that bark was the warmest, followed by a deciduous canopy, flowers, and coolest was an evergreen canopy. Differences among canopy surfaces were largest during afternoon hours, when the evergreen canopy cooled more rapidly than other canopy surfaces, presumably due to transpiration. Gross primary productivity (GPP), estimated from eddy covariance measurements, was more strongly associated with canopy temperatures than air temperatures or vapor pressure deficit. The rate of GPP increase with canopy temperatures slowed above ~28–29°C, but GPP continued to increase until ~31–32°C. Although future warming is projected to be greater in high‐latitude regions, we show that tropical forest productivity is highly sensitive to small changes in temperature. Important biophysical and physiological characteristics captured by canopy temperatures allow more accurate predictions of GPP compared to commonly used air temperatures. Results suggest that as air temperatures continue to warm with climate change, canopy temperatures will increase at a ~40% higher rate, with uncertain but potentially large impacts on tropical forest productivity.