Negin Katal | Max Planck Institute for Biogeochemistry (original) (raw)
Negin Katal is PhD candidate at Bio.AI lab and works on opportunistic citizen science data for plant phenology monitoring.
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Papers by Negin Katal
Frontiers in Plant Science, Oct 3, 2023
Frontiers in Plant Science, 2022
Climate change represents one of the most critical threats to biodiversity with far-reaching cons... more Climate change represents one of the most critical threats to biodiversity with far-reaching consequences for species interactions, the functioning of ecosystems, or the assembly of biotic communities. Plant phenology research has gained increasing attention as the timing of periodic events in plants is strongly affected by seasonal and interannual climate variation. Recent technological development allowed us to gather invaluable data at a variety of spatial and ecological scales. The feasibility of phenological monitoring today and in the future depends heavily on developing tools capable of efficiently analyzing these enormous amounts of data. Deep Neural Networks learn representations from data with impressive accuracy and lead to significant breakthroughs in, e.g., image processing. This article is the first systematic literature review aiming to thoroughly analyze all primary studies on deep learning approaches in plant phenology research. In a multi-stage process, we selected...
Topography influences evolutionary and ecological processes by isolating populations and enhancin... more Topography influences evolutionary and ecological processes by isolating populations and enhancing habitat diversity. While the effects of large-scale topography on patterns of species richness and endemism are increasingly well documented, the direct effect of local topography on endemism is less understood. This study compares different aspects of topographic isolation, namely the isolating effect of deep barrancos (ravines) and the effect of increasing isolation with elevation in influencing patterns of plant endemism within a topographically diverse oceanic island (La Palma, Canary Islands, Spain). We collected plant presence–absence data from 75 plots in 8 barrancos on the northern coast of La Palma, spanning an elevation gradient from 95 to 674m a.s.l. Using mixed-effects models, we assessed the effect of barranco depth and elevation on the percentage of single-island endemics, multi-island endemics, and archipelago endemics. We found that percent endemism was not significantl...
• Small-scale variation in topography may favour endemism if it causes species to be persistently... more • Small-scale variation in topography may favour endemism if it causes species to be persistently isolated • La Palma (Canary Islands) has many deep, steep-sided barrancos, containing unique habitat with many endemic plant species • The proportion of endemic plants on barranco floors decreases with elevation, while the co-linear increase with barranco depth is not significant • Local topography may complicate broader-scale relationships between endemism and elevation, and this requires further research
Frontiers in Plant Science, Oct 3, 2023
Frontiers in Plant Science, 2022
Climate change represents one of the most critical threats to biodiversity with far-reaching cons... more Climate change represents one of the most critical threats to biodiversity with far-reaching consequences for species interactions, the functioning of ecosystems, or the assembly of biotic communities. Plant phenology research has gained increasing attention as the timing of periodic events in plants is strongly affected by seasonal and interannual climate variation. Recent technological development allowed us to gather invaluable data at a variety of spatial and ecological scales. The feasibility of phenological monitoring today and in the future depends heavily on developing tools capable of efficiently analyzing these enormous amounts of data. Deep Neural Networks learn representations from data with impressive accuracy and lead to significant breakthroughs in, e.g., image processing. This article is the first systematic literature review aiming to thoroughly analyze all primary studies on deep learning approaches in plant phenology research. In a multi-stage process, we selected...
Topography influences evolutionary and ecological processes by isolating populations and enhancin... more Topography influences evolutionary and ecological processes by isolating populations and enhancing habitat diversity. While the effects of large-scale topography on patterns of species richness and endemism are increasingly well documented, the direct effect of local topography on endemism is less understood. This study compares different aspects of topographic isolation, namely the isolating effect of deep barrancos (ravines) and the effect of increasing isolation with elevation in influencing patterns of plant endemism within a topographically diverse oceanic island (La Palma, Canary Islands, Spain). We collected plant presence–absence data from 75 plots in 8 barrancos on the northern coast of La Palma, spanning an elevation gradient from 95 to 674m a.s.l. Using mixed-effects models, we assessed the effect of barranco depth and elevation on the percentage of single-island endemics, multi-island endemics, and archipelago endemics. We found that percent endemism was not significantl...
• Small-scale variation in topography may favour endemism if it causes species to be persistently... more • Small-scale variation in topography may favour endemism if it causes species to be persistently isolated • La Palma (Canary Islands) has many deep, steep-sided barrancos, containing unique habitat with many endemic plant species • The proportion of endemic plants on barranco floors decreases with elevation, while the co-linear increase with barranco depth is not significant • Local topography may complicate broader-scale relationships between endemism and elevation, and this requires further research