The advancement of spring is a widespread biological response to climate change observed across taxa and biomes. However, the species level responses to warming are complex and the underlying mechanisms are difficult to disentangle. This is partly due to a lack of data, which are typically collected by direct observations, and thus very time‐consuming to obtain. Data deficiency is especially pronounced in the Arctic where the warming is particularly severe. We present a method for automated monitoring of flowering phenology of specific plant species at very high temporal resolution through full growing seasons and across geographical regions. The method consists of image‐based monitoring of field plots using near‐surface time‐lapse cameras and subsequent automated detection and counting of flowers in the images using a convolutional neural network. We demonstrate the feasibility of collecting flower phenology data using automatic time‐lapse cameras and show that the temporal resolution of the results surpasses what can be collected by traditional observation methods. We focus on two Arctic species, the mountain avens
The Arctic is warming at an alarming rate, leading to earlier spring conditions and plant phenology. It is often unclear to what degree changes in reproductive fitness (flower, fruit and seed production) are a direct response to warming versus an indirect response through shifting phenology. The aim of this study was to quantify the relative importance of these direct and indirect pathways and project the net effects of warming on plant phenology and reproductive fitness under current and future climate scenarios.
We used two long-term datasets on 12 tundra species in the Canadian Arctic as part of the International Tundra Experiment (ITEX). Phenology and reproductive fitness were recorded annually on tagged individual plants at both Daring Lake, Northwest Territories (64° 52' N, - 111° 35' W) and Alexandra Fiord, Nunavut (78° 49' N, - 75° 48' W). The plant species encompassed a wide taxonomic diversity across a range of plant functional types with circumpolar/boreal distributions. We used hierarchical Bayesian structural equation models to compare the direct and indirect effects of climate warming on phenology and reproductive fitness across species, sites and years.
We found that warming, both experimental and ambient, drove earlier flowering across species, which led to higher numbers of flowers and fruits produced, reflecting directional phenotypic selection for earlier flowering phenology. Furthermore, this indirect effect of climate warming mediated through phenology was generally about two to three times stronger than the direct effect of climate on reproductive fitness. Under future climate predictions, individual plants showed a ~2- to 4.5-fold increase in their reproductive fitness (flower counts) with advanced flowering phenology.
Our results suggest that, on average, the benefits of early flowering, such as increased development time and subsequent enhanced reproductive fitness, might outweigh its risks. Overall, this work provides important insights into population-level consequences of phenological shifts in a warming Arctic over multi-decadal time scales.
- NSF-PAR ID:
- 10490543
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Annals of Botany
- ISSN:
- 0305-7364
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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