This blog mostly summarizes useful science I read, and promotes my own research. Content posted here is my own and does not reflect the opinions of my employer or anyone else. I tweet at @sciencejon and my bio is at http://fish.freeshell.org/bio.html
Wednesday, July 1, 2020
July 2020 science article summary
This month I have another short summary: one article on advice for scientists who want to work with policymakers, three on metrics, and two on wildlife migration.
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Hetherington & Phillips 2020 is a clear 10-step "how-to" guide for scientists to engage with policymakers. It focuses primarily on understanding, meeting with, and informing policymakers. It is a nice complement to our recent paper on a similar topic (available at http://impact.sciencejon.com/, which focuses more on research design and skimps on how precisely to engage with policymakers).
Banks-Leite et al. 2011 compares how indicator species vs. landscape indicators perform in capturing underlying biodiversity and ecological condition. They found that landscape indicators (e.g. patch area, edge effects [via perimeter and core area using different edhe buffers], connectivity, and % forest cover) worked better than species-based indicators for most applications.
Skidmore et al. 2015 calls for the creation of a global standard for how to measure biodiversity using satellites. The ten variables they recommend are species occurrence, plant traits (e.g. specific leaf area or leaf N content), ecosystem distribution, fragmentation & heterogeneity, land cover, vegetation height, fire occurrence, vegetation phenology (variability), primary productivity & leaf area index, and inundation (presence of standing water).
Uuemaa et al. 2009 is a long and wonky review of landscape metrics used to capture different ecological attributes. Table 1 has a nice list of how well several species-specific variables relate to landscape metrics (e.g. one study found that overall % forest cover was well correlated w/ riparian woody species richness), although it is a list of results from individual studies rather than a broadly representative meta-analysis or review.
LaCava et al. 2020 studied pronghorn in Wyoming, and found that despite their wide range (including several migration barriers), their genetics show that they are still interbreeding. So despite the challenges, their migration is successful enough to avoid isolation leading to genetic division.
Love Stowell et al. 2020 mapped out the genetics of 244 bighorn sheep in Wyoming (plus 109 more from Oregon, Montana, and Idaho used as sources for sheep brought to Wyoming). Fig 3 has the key results (for nuclear DNA) showing where the different genetically distinct herds live. They note that their mitochondrial results don't show the same pattern, possibly due to translocation or residual effects from formerly connected herds that are now fragmented. They conclude by calling for wildlife management to reflect genetic variation, balancing benefits and risks of translocation in particular (which reduces inbreeding, but can cause disease transmission).
Banks-Leite, C., Ewers, R. M., Kapos, V., Martensen, A. C., & Metzger, J. P. (2011). Comparing species and measures of landscape structure as indicators of conservation importance. Journal of Applied Ecology, 48(3), 706–714. https://doi.org/10.1111/j.1365-2664.2011.01966.x
Hetherington, E. D., & Phillips, A. A. (2020). A Scientist’s Guide for Engaging in Policy in the United States. Frontiers in Marine Science, 7(June), 1–8. https://doi.org/10.3389/fmars.2020.00409
LaCava, M. E. F., Gagne, R. B., Stowell, S. M. L., Gustafson, K. D., Buerkle, C. A., Knox, L., & Ernest, H. B. (2020). Pronghorn population genomics show connectivity in the core of their range. Journal of Mammalogy, (X), 1–11. https://doi.org/10.1093/jmammal/gyaa054
Love Stowell, S. M., Gagne, R. B., McWhirter, D., Edwards, W., & Ernest, H. B. (2020). Bighorn Sheep Genetic Structure in Wyoming Reflects Geography and Management. The Journal of Wildlife Management, jwmg.21882. https://doi.org/10.1002/jwmg.21882
Skidmore, A. K., Pettorelli, N., Coops, N. C., Geller, G. N., Hansen, M., Lucas, R., … Wegmann, M. (2015). Environmental science: Agree on biodiversity metrics to track from space. Nature, 523(7561), 403–405. https://doi.org/10.1038/523403a
Uuemaa, E., Antrop, M., Roosaare, J., Marja, R., & Mander, Ü. (2009). Landscape Metrics and Indices: An Overview of Their Use in Landscape Research. Living Reviews in Landscape Research, 3(1), 1–28. https://doi.org/10.12942/lrlr-2009-1
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