The use of photos to investigate ecological change

Abstract

Global change is causing ecosystems to change at unprecedented rates and the urgency to quantify ecological change is high. We therefore need all possible sources of ecological data to address key knowledge gaps. Ground‐based photos are a form of remote sensing and an unconventional data source with a high potential to improve our understanding of ecological change. They can provide invaluable information on ecological conditions in the past and present at relevant spatiotemporal scales that is very difficult to obtain with other approaches. Here we review the use of ground‐based photos in a set of relevant ecological research topics, such as biodiversity and community ecology, phenology, global change ecology and landscape ecology. We highlight three main photo‐based methods in ecological research (repeat photography, time‐lapse photography and public archives), alongside which we discuss three case studies to demonstrate novel applications of these methods, to answer fundamental ecological questions. Synthesis. Photos can significantly support ecological research to improve our understanding of biotic responses in a rapidly changing world. Photos cover relatively large temporal and spatial scales, and can provide large amounts of information with limited time investment. To exploit their full potential, we need to invest not only in technological advances to compile, process and analyse images but also in proper data management.

Where wolves were: setting historical baselines for wolf recovery in Spain

“…Similar approaches could be developed for different areas and/or different species, taking advantage of the rich documentary heritage existing in several areas of the world (Turvey, Crees, & Di Fonzo, 2015; Viana et al ., 2022). In regions and/or time frames for which written sources are not available, informative baselines for species or natural systems can also be generated from other sources, such as archaeological data (McKechnie et al ., 2014; Reeder‐Myers et al ., 2022), historical maps (Kitazawa et al ., 2022), pictorial sources (from rock art to photographs; Drake et al ., 2011; Depauw et al ., 2022) or from natural archives (e.g. palynological series; Szabó et al ., 2017).…”

AngleCam: Predicting the temporal variation of leaf angle distributions from image series with deep learning

“…This could, for instance, be used to efficiently feed leaf angle observations to trait databases such as TRY (Kattge et al, 2020), which are extremely sparse in this context. Such potentials may be even accelerated with the concurrent developments of big data in ecology (Depauw et al, 2022; Farley et al, 2018). Data gaps of leaf angles across species may be filled with AngleCam and in concert with the ever increasing availability of citizen science photographs and species labels (the iNaturalist project, Di Cecco et al, 2021; Schiller et al, 2021).…”

The International Tundra Experiment (ITEX): 30 years of research on tundra ecosystems

“…Combining the plot measurements with plot-level and landscape-level remote sensing will help to improve interpretations from satellite-based sensors. Use of spectral radiometers and cameras, either on platforms such as drones or kites or installed above plots at ITEX sites allows effective and efficient measurements of greening and flowering in plots and can be used to detect shifts in these variables in response to experimental and ambient climate change (e.g., Chen et al 2010;Beamish et al 2016;Depauw et al 2022;May et al 2022). A data base of plot photos at ITEX and other tundra sites linked to landscape images from plots and drone platforms has been established as part of the HiLDEN network (Assmann et al 2019), which will be useful for analyses of the continued changes in species composition and abundance.…”