An optical image of Kliuchevskoi volcano on the left, with a radar image on the left (Image credit: Michigan Tech Volcanology, Image Cropped)
Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series (2020), Lopes et al., Methods in Ecology and Evolution, https://doi.org/10.1111/2041-210X.13359
Most ecologist has at some point run across or used a land cover map in their career. Whether it’s used for figuring out the canopy diversity of a forest, or figuring out which habitat a species is using, land cover maps are incredibly useful tools for everyone from conservationists to architects. But have you ever wondered how they are produced?
Until recently, land cover maps were created using either images from optical satellites or images from radar satellites with a coarse to medium spatial resolution (check out the Did You Know Section for more details, or the image above for an example). Combined with classification algorithms, land cover maps can be created automatically. That makes it sound simple, but the final output depends greatly on the quality and amount of images you use for the classification. Since 2014, the Copernicus Programme has made satellite imaginary freely available at high spatial and temporal spatial resolution. Due to this, optical and radar images can be combined more efficiently to produce land cover classification maps with enhanced accuracy. This is especially useful in tropical and boreal areas, as optical images often don’t show the entire landscape due to persistent cloud over.
Image Credit: Danyell Odhiambo/ICRAF, CC BY-NC-SA 2.0
Local Adaptation to Biotic Interactions: A Meta-analysis across Latitudes (2020) Hargreaves et al., The American Naturalist, https://doi.org/10.1086/707323
Local adaptation is a process whereby individuals native to a given area are better-suited to live in that environment than foreign individuals, and those local individuals will out-compete foreign individuals. This adaptation to local conditions can range from a predator that is better at finding and catching prey, to a plant that is more efficient than another at taking nutrients from the soil, or to a host that has evolved defenses against a local parasite. Despite a wealth of literature and science that has been dedicated to the study of local adaptation, it is not clear what it is about the environment that commonly drives it.
Early studies of local adaptation measured abiotic (non-living) factors like temperature and the amount of light, but this ignores the fact that all environments include biotic factors like other species and any interactions with them. A small amount of studies have shown that biotic interactions (i.e. interactions with other species) can drive local adaptation, but there isn’t a consensus on how common of a pattern that is. Today’s authors used a meta-analysis of previous studies to test how these biotic interactions affect local adaptation. Read more
Image Credit: The Little Mermaid, 1989
Adam regales us with one of the weirdest stories I’ve ever heard, and in case you were wondering, yes we do talk about how mermaids have sex. Jesus. Also there’s some cool ecology. Like how did mermaids evolve? Was it from a mutated baby tossed overboard? Probably not.
05:19 – Mermaids in Cinema
16:35 – Ecology of the Mermaids
33:25 – Mermaid Copulation (you were warned)
38:07 – The Mermaids vs. Jaws
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Species richness is much higher in waters near the equator, but do we see that in a phylogenetic tree? (Image Credit: Rich Brooks, CC BY 2.0)
An inverse latitudinal gradient in speciation rate for marine fishes (2018) Rabosky et al., Nature doi:10.1038/s41586-018-0273-1
The tropical regions of the Earth are the most species-rich and diverse ecosystems on the planet, with this diversity and species-richness declining as you move further and further from the equator. One hypothesis explaining this is that speciation rates are simply higher in the tropics, meaning that more species are evolving in a given time in the tropics than anywhere else. To test for this, the authors used the largest phylogenetic tree available and analyzed speciation rates (how many new species evolve from older species) per million years.