In 1970, the Institute of Geography of the University of Bern initiated the phenological observation network BernClim. Seasonality information from plants, fog and snow was originally available for applications in urban and regional planning and agricultural and touristic suitability and is now a valuable data set for climate change impact studies. Covering the growing season, volunteer observers record the dates of key development stages of hazel (Corylus avellana), dandelion (Taraxacum officinale), apple tree (Pyrus malus) and beech (Fagus sylvatica). All observations consist of detailed site information, including location, altitude, exposition (aspect) and inclination, that makes BernClim unique in its richness in detail on decadal timescales. Quality control (QC) by experts and statistical analyses of the data have been performed to flag impossible dates, dates outside the biologically plausible range, repeated dates in the same year, stretches of consecutive identical dates and statistically inconsistent dates (outliers in time or in space). Here, we report BernClim data of 7414 plant phenological observations from 1970 to 2018 from 1304 sites at 110 stations, the QC procedure and selected applications (Rutishauser et al., 2019: https://doi.org/10.1594/PANGAEA.900102). The QC points to very good internal consistency (only 0.2 % were flagged as internally inconsistent) and likely high quality of the data. BernClim data indicate a trend towards an extended growing season. They also track the regime shift in the late 1980s well to pronounced earlier dates like numerous other phenological records across the Northern Hemisphere.

Shifts in phenology of plants and animals have been widely observed as consequence of climate change impacts and temperature increase. Species-specific data are often assigned to limited and generalized site information on the precise location of the observation. However, as much meta-information as possible on the individual plant under observations is necessary to assess the impacts of changing weather patterns at the local scale that are related to changes in radiation, fog, frost and dominating circulation.

Vegetation phenology has a strong influence on the timing and phase of global terrestrial carbon and water exchanges and is an important indicator of climate change and variability. In this study we tested the application of inexpensive digital visible‐light cameras in monitoring phenology. A standard digital camera was mounted on a 45 m tall flux tower at the Lägeren FLUXNET/CarboEuropeIP site (Switzerland), providing hourly images of a mixed beech forest. Image analysis was conducted separately on a set of regions of interest representing two different tree species during spring in 2005 and 2006. We estimated the date of leaf emergence based on the levels of the extracted red, green and blue colors. Comparisons with validation data were in accordance with the phenology of the observed trees. The mean error of observed leaf unfolding dates compared with validation data was 3 days in 2005 and 3.6 days in 2006. An uncertainty analysis was performed and demonstrated moderate impacts on color values of changing illumination conditions due to clouds and illumination angles. We conclude that digital visible‐light cameras could provide inexpensive, spatially representative and objective information with the required temporal resolution for phenological studies.

The phenological development of plants provides information about the influence of weather on vegetation and may be assessed on both the individual plant level and on a global level. Since 2000, Switzerland has had a phenological monitoring network for forest trees which records the seasonality and is complementary to the ICP-Forests Assessments (International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests). A comparison of leaf discoloration at the monitoring plot Kaiseraugst has shown that beech, oak and ash trees have all been affected differently as a result of the summer drought of 2003. In 2004,a digital picture data base was developed for the research project 'Phenophot' at the Geographical Institute Berne which allows the phenological observations to become objective and reproducible. A Phenological Growing Index (PGI) is being derived from the red-green-blue channel data of the digital sensor, which complements the information of satellite based vegetation indices. These indices include the Normalized Differenced Vegetation Index (NDVI) on a sub-pixel level which provides improved accuracy for the information on the character and beginning and ending of the vegetation period. The first comparison of the phenological spring index from the satellite based NDVI revealed that the annual start of spring is reproduced most accurately by determining a threshold of the NDVI.

Observations of Beech trees in Switzerland show relevant differences in the phenology of the single individual. Within the collective of Beech trees, the state of phenological development differs from about one to nineteen days for leaf unfolding, and about six to thirty-six days for leaf coloring. Data on the occurrence of specific phenophases and their absolute differences within a collective are important aids to estimating the potential of climate damage in threshold situations (e.g., frost damage in spring), or the potential of degradation or drift within a population in relation to climate change. Mapping the observed phenological development of a single individual onto daily weather indices also provides a closer understanding of the different indications of natural growth processes. Phenology has established itself as a valuable instrument for monitoring the impact of climate change. Since such data also allows observation of natural development and variations, it is also an extremely useful way of obtaining additional biological information.