Continuous monitoring of forest canopy structure and phenology is pivotal for the assessment of ecosystem responses to environmental variability and changes. The present study evaluated the use of repeat digital trail cameras as a low-cost, flexible, and accessible in situ monitoring solution for quantifying daily canopy attributes, including effective leaf area index (Le) and canopy cover. A trial camera monitoring network (CrowNet) was established encompassing 20 forest stands in Italy, under different management and environmental conditions, resulting in over 44,000 daily images collected over three years. We demonstrated that taking the mean daily canopy attribute allowed to obtain smooth time series from trail cameras, from which phenological transition dates can be inferred. Daily canopy attributes were validated against manual digital cover photography measurement. To further explore the applicability of this monitoring solution, we performed a comparison between daily Le time series derived from a subset of trail cameras located in beech forests and data collected by multitemporal UAV LiDAR. Results demonstrated the close agreement between the two methods across the entire phenological period (start and end of season). We also illustrated use of continuous trail camera estimates to calibrate a vegetation index (NDVI) to infer leaf area and canopy cover from optical multi-temporal UAV data. We further investigated use of trail camera to detect species-specific differences in tree phenology from time series acquired in a mixed oak-hornbeam forest. We found different canopy structure and phenological transition dates in three broadleaved species (oak, ash, hornbeam), supporting the effectiveness of trail cameras for species-oriented phenology monitoring. We conclude that trail cameras provide a reliable solution for daily canopy monitoring, offering a significant cost-effective and flexible alternative to traditional field methods and providing potential to calibrate, validate or integrate remotely-sensed information. However, camera failures during adverse weather, and the need for more efficient image data quality checking procedures, still represent open challenges. Future improvements, such as weatherproof housing and automated pre-processing screening procedures, are therefore recommended for making trail camera fully operational in ground canopy and phenology monitoring. © 2025 Elsevier B.V.

Forest phenology plays a key role in the global terrestrial ecosystem influencing a range of ecosystem processes such as the annual carbon uptake period, and many food webs and changes in their timing and progression. The timing of the start of the phenology season has been successfully determined at a range of scales, from the individual tree by in situ observations to landscape and continental scales by using remotely sensed vegetation indices (VIs). The spatial resolution of satellites is much coarser than traditional methods, creating a gap between space-borne and actual field observations, which brings limitations to phenological research at the ecosystem level. Several unconsidered methodological and observational-related limitations may lead to misinterpretation of the timing of the satellite-derived signals. The aim of this study is therefore to clarify the meaning of a set of spring phenology metrics derived from Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI) time series in beech forests distributed across Europe with respect to PEP725 in situ observations, from 2003 to 2020. To this aim, we (i) tested the differences between remotely sensed and in situ start-of-season (SOS) metrics and (ii) quantified the influence of latitude, elevation, temperature, and precipitation on such differences. Results demonstrated that there is a clear temporal gradient among the different SOS metrics, all of them occurring prior to the in situ observations. Furthermore, latitude and temperatures proved to be the main factors guiding the differences between remotely sensed and in situ SOS metrics. Evidence from this study may help in recognizing the actual meaning of what we see by means of remotely sensed phenology metrics. In this perspective, field observations are crucial in understanding phenology events and provide a reference base. Satellite data, on the other hand, complement field observations by filling in gaps in spatial and temporal coverage, thus enhancing the overall understanding. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Masting is a complex mechanism which is mainly driven by a combination of internal plant resources and climatic conditions. While the driving role of climate in masting is being intensively studied, the interplay among climate, seed production, vegetation growth and phenology still needs further investigation. The objectives of this study were to identify the climatic determinants of different levels of seed production and of NDVI-based vegetation growth and phenology in European beech, and to evaluate if exists a trade-off between these two plant processes. To answer these questions, we used a 25-year-long dataset of beech seed production. We exploited the concept of ecological niche assuming that a mast year can be modeled like a species with variable preferences for different resources, which are the underlying annual climatic conditions; we performed an Ecological Niche Factor Analysis (ENFA), a presence-only modeling tool conventionally used in zoology and botany, and used seasonal (spring, summer, autumn) Standardized Precipitation-Evaporation Index (SPEI) observations, considering the current year (y−0), and up to one (y−1) and two (y−2) years before the masting event. For analyzing the role of vegetation growth and phenology, we used seasonal Normalized Difference Vegetation Index (NDVI) values and associated NDVI-based phenological metrics derived from Landsat imagery. Results indicated the driving role of climate for masting, especially in VHSP years. A moist summer and dry spring at y−2 and a dry summer at y−1 represented the main driving climatic conditions for masting; while a moist spring during the observation year represented the key condition for triggering higher intensities of seed production. Summer NDVI at y−0 and y−1 represented the variables discriminating best between masting and non-masting years and resulted as driven by opposite summer climatic conditions than seed production, thus indicating a trade-off between seed production and vegetation phenology. We concluded that reproduction and vegetation growth act as two different climate-dependent plant responses in beech, in a way that certain conditions through the years promote mast seeding and the opposite conditions favor vegetation growth. The understanding of climate-growth-masting relationships represents indispensable knowledge for providing a holistic view of masting mechanisms and developing adaptive forest management strategies in this species. © 2020