Changes in phenology are often cited as a key biotic impact of climate change. Consequently, understanding the major environmental cues and responses to those cues in different species is important for making predictions about the future impacts and ecological implications of changing phenology. In this thesis, I set out to explore the phenological cues, mechanisms of response to temperature and the potential for interacting species to experience phenological mismatch in a range of UK plants. To do this, I utilised phenological records from two citizen science schemes; the well-established Nature’s Calendar, which collects observations for the UK Phenology Network (UKPN), and Track a Tree, a novel project I set up specifically to examine the phenology of interacting plant species in UK woodlands. I first assessed the ability of plasticity to track shifts in the optimum phenology for 22 plant species. I employed a statistical approach to estimate the plasticity and temperature sensitivity of the phenological optimum for leafing and flowering dates obtained from the UKPN. In identifying the most important cues I found that all species are sensitive to spring forcing temperatures, with plastic responses ranging from -3 to -8 days °C-1. Chilling temperatures in autumn/winter and photoperiod were important in species with early and late phenology, respectively. In seven species, plasticity was sufficient to track geographic variation in the optimum phenology. In four species, plasticity did not track the optimum, which is consistent with clinal local adaptation to temperature, and which could place phenology under directional selection in a changing climate. I then performed a phylogenetic comparative analysis on the median phenology and estimates of plasticity and local adaptation for the 22 species analysed previously. I found that phenological event (leafing or flowering) and growth form (woody or herbaceous perennial) predicted plasticity in phenological response. These traits may help inform future predictions of phenological responses to temperature. In contrast, the median date of phenology and clinal local adaptation over latitude were not predicted by any of the ecological traits considered. I next used records from the Track a Tree project to examine the relative phenology of canopy tree and understorey flowering species across UK woodlands. I found that first leafing and peak flowering of focal species pairs were correlated over space, and that the time between canopy leafing and the ground flora flowering (relative phenology) was spatially consistent. Relative phenology of two canopy tree species pairs was spatially consistent, but for a native versus non-native tree species pair the relationship varied over space (with a slope close to 0). If temperature-mediated plasticity determines these species’ phenology, my results suggest understorey flowering may be able to track canopy leafing in future, maintaining shading interactions. Finally, I used the Track a Tree data to partition the variance in phenology for seven tree species, and test what predicts variation in oak and birch. I found that the contributors to variance differ among tree species, with spatial variables important, and within site variance low, for all species except sycamore. The low intraspecific within-site variance suggests that some species may have a limited capacity for phenological buffering. These findings contribute to understanding what impacts on the phenological distribution of different species, an important requirement for assessing the phenological buffering of mismatch. In this thesis, I broadened the range of approaches that can be used to understand plant phenology in a changing climate. I demonstrated the value of employing novel statistical methods to analyse existing phenology data and the utility of hypothesis driven citizen science for predicting phenological shifts and the subsequent ecological implications for interacting species.

The impacts of climate change on temperate forests are predicted to accelerate, with widespread implications for forest biodiversity and function. Remote sensing has provided insights into regional patterns of vegetation dynamics, and experimental studies have demonstrated impacts of specific changes on individual species. However, forests are diverse and complex ecosystems. To understand how different species in different forests respond to interacting environmental pressures, widespread ground-based monitoring is needed. The only practical way to achieve this is through the involvement of non-professional researchers, i.e., with citizen science. However, many techniques used to identify subtle changes in forests require expensive equipment and professional expertise. This thesis aimed to identify practical methods for citizen scientists to collect useful data on forest ecosystem dynamics in relation to climate change. Methods for monitoring tree phenology and canopy-understorey interactions were the main focus, as tree phenology exerts strong control on understorey light and forest biodiversity, and is already responding to climate change. The response of understorey vegetation to canopy closure in four woodlands from a single region of England (Devon) was examined in detail. These geographically close woodlands differed considerably in their composition and seasonal dynamics. The spring period was particularly important for herb-layer development, and small variations in canopy openness had important effects on herb-layer cover and composition. This work highlights the need to monitor a range of different woodlands at the regional scale, with sufficient resolution to pick up small but crucial differences through time. Citizen scientists could help to collect such data by monitoring herb-layer cover and changes in the abundance of key species, alongside monitoring the overstorey canopy. The spring leaf phenology of four canopy trees (ash, beech, oak and sycamore) were monitored intensively in one woodland using a range of methods: counts, percentage estimates and photography. First budburst and leaf expansion dates were compared with estimates of leaf expansion timing and rate, derived from time-series data using logistic growth models. Frequently used first-event dates were potentially misleading due to high variation in leaf development rates within and between species. Percentage estimates and counts produced similar estimates of leaf expansion timing and rate. A photo-derived greenness index produced similar estimates of timing, but not rate, and was compromised by practical issues of photographing individual crowns in closed canopy woodland. Citizen science should collect time-series data instead of frequently-used first event dates―visual observations offer the most practical way to do this, but further work is needed to test reliability with citizen scientists. Given high intra- and inter-species variation in tree phenology, whole forest canopies need to be monitored to infer canopy closure timing. Canopy openness was assessed using sophisticated hemispherical photography and a range of low-cost alternatives, across four Devon woodlands over a year. Visual estimates and ordinary photography were too coarse to identify fine-scale variation in canopies. Smartphone fisheye photography analysed with free software was identified as a reliable surrogate for estimating relative, though not absolute, canopy openness. The method has high potential as a citizen science tool, as different phone models and users gave similar canopy openness estimates. In a detailed follow-up study, smartphone fisheye photography, hemispherical photography and visual observations of leaf expansion were used every other day to characterise spring canopy development. Logistic growth models estimated canopy closure timing and rate. Visual observations identified much earlier canopy development than either photographic method. Smartphone fisheye photography performed comparably to hemispherical photography. There is good potential for practical application of smartphone fisheye photography, as similar canopy closure estimates were gained from photos taken once every two weeks. The research in this thesis identifies a range of methods suitable for widespread monitoring of forest ecosystem dynamics in relation to climate change. Developing a smartphone app for automatic analysis and submission of canopy images will be an important next step to enabling widespread use. A pilot project is underway to begin testing methods with citizen scientists. Further research into data quality with citizen scientists is needed before the methods can be rolled out widely with confidence.