Hi,
It occurred to me that since I focused on fire in April and water in May, I should continue with the elemental theme and cover terrestrial papers this month. Doing air/wind in July is unlikely :) It's still a bit of a mix with papers on global threats, forest degradation, protected areas, and wildlife migration.
If you know someone who wants to sign up to receive these summaries, they can do so at http://bit.ly/sciencejon (no need to email me).
GLOBAL THREATS:
Oakleaf et al. 2024 is a long-awaited global analysis of likelihood of short-term (by 2030) habitat conversion (1 km resolution, see Fig 5 for the results). They include not only cropland and city expansion, but also land use change for energy (fossil or renewable) and mining, and considered several suitability factors (like slope and land cover). Their approach assumes recent trends (2000-2015) will continue rather than modeling different scenarios of economic development. Like any global data you can find places where it seems wrong, but it's a great resource nonetheless. You can grab the data at https://figshare.com/articles/dataset/Conversion_Pressure_Index/25340668 or view the data in a web map at https://tnc-ps-web.s3.amazonaws.com/GDRA/CPI/index.html There's also a blog about the paper at https://blog.nature.org/science-brief/mapping-global-land-conversion-to-support-conservation-planning/
FOREST DEGRADATION:
Bourgoin et al. 2024 is a global analysis of degradation of tropical moist forests using LiDAR satellite data (from GEDI) along with Landsat optical imagery. It's worth reading the whole paper, but a few key findings: 1) degradation is hard to sense but a) a good predictor of deforestation in addition to b) being inherently meaningful. 2) Forest height is reduced by selective logging (15%) and fire (50%) and recovery is low after 20 years. 3) Expansion of ag and roads leads to a 20-30% drop in canopy height and biomass at the edge, with effects up to 1.5km in from the edge. Fig 1 has maps of global results - it's a bit confusing but the x-axis of the charts is height in meters, so lower numbers mean more degradation or younger forests. There's an article about this one at https://phys.org/news/2024-07-reveals-human-degradation-tropical-forests.html#google_vignette
EFFICACY OF PROTECTED AREAS:
Huais et al. 2025 looked at the impact of protected areas (PAs) in the Chaco (across Bolivia, Argentina, and Paraguay) in slowing deforestation both within their boundaries and nearby. The bad news: only 34% of PAs actually reduced deforestation within the area, and 9% of PAs actually saw MORE deforestation than expected (with the other 58% seeing no impact). Most of the effective area was in Bolivia (see Fig 3a), although Bolivia also had a lot of PAs they couldn't analyze due to a lack of suitable control / counterfactual areas. In good news, only 4% of PAs saw leakage (deforestation shifting from within a PA to a nearby area - they didn't consider long-distance leakage), and better yet 21% of PAs seemed to decrease deforestation in nearby areas. In other words ~2/3 of the PAs that actually slowed deforestation within their borders ALSO had a broader positive impact (Fig 3b), likely by a) discouraging infrastructure and access to the nearby areas, b) the presence of some Indigenous territories near PAs, and c) buffer areas around each PA.
WILDLIFE MIGRATION:
Aikens et al. 2025 has a nice summary up front already! They found that during a very bad snowstorm (see Fig 1), pronghorn died more when they couldn't get away from deep snow fast enough (Fig 2D). Roads and fences blocking their way meant they were exposed to snow longer (and thus at higher risk). 1/2 of monitored pronghorn (they had GPS collars) died from the storm, and they moved up to 400 km to try and get away! Pronghorn tend to crawl under fences so when snow is deep they may be unable to cross them at all (Fig 3D has a photo).
Haworth et al. 2025 (non-peer-reviewed) looked at a handful of roadways with different kinds of medians (e.g. vegetated, just paint, cable, concrete, or metal guardrail) to compare how medians affected wildlife crossings for different species (see Table 3 on p22). They assert that some species were impacted by median types, and that in general constructed medians lead to fewer animals entering the roadway at all (so less permeability may also reduce collision risk). But when you get into the results it’s less convincing – the pairwise comparisons don’t have any clear trends (except a weak tendency of fewer collisions from harder barriers). Figure 4 also has some weird findings for mule deer (painted stripe saw the most collisions, cable and gravel the lowest, but oddly concrete and metal beam are closer to the painted stripe) and then Figure 5 for coyote shows that painted stripe had the least collisions! My take-away is that either 1) it’s easy for small studies to show effects due to uncontrolled variables, especially for wildlife movement which can vary a lot and/or 2) the relationship is complicated and there’s not a simple policy answer (like X median will best reduce risk of WVC while also allowing wildlife movement).
REFERENCES:
Aikens, E. O., Merkle, J. A., Xu, W., & Sawyer, H. (2025). Pronghorn movements and mortality during extreme weather highlight the critical importance of connectivity. Current Biology, 35(8), 1927-1934.e2. https://doi.org/10.1016/j.cub.2025.03.010
Bourgoin, C., Ceccherini, G., Girardello, M., Vancutsem, C., Avitabile, V., Beck, P. S. A., Beuchle, R., Blanc, L., Duveiller, G., Migliavacca, M., Vieilledent, G., Cescatti, A., & Achard, F. (2024). Human degradation of tropical moist forests is greater than previously estimated. Nature, 631(8021), 570–576. https://doi.org/10.1038/s41586-024-07629-0
Haworth, L., Hodgson, B., Hecht, L., See, M., Henderson, A., Lemieux, S., Morris, L., Waetjen, D., Shilling, F., Haworth, L., Hodgson, B., Hecht, L., See, M., Henderson, A., Lemieux, S., Morris, L., Waetjen, D., & Shilling, F. (2025). Wildlife Connectivity and Which Median Barrier Designs Provide the Most Effective Permeability for Wildlife Crossings. https://doi.org/10.7922/G2BV7DZ6
Huais, P. Y., Kuemmerle, T., Nori, J., Tomba, A. N., Cordier, J. M., & Baumann, M. (2025). Only one-third of protected areas in the Chaco effectively curb woodland loss, but their impact extends beyond their boundaries. Biological Conservation, 308(March), 111196. https://doi.org/10.1016/j.biocon.2025.111196
Oakleaf, J., Kennedy, C., Wolff, N. H., Terasaki Hart, D. E., Ellis, P., Theobald, D. M., Fariss, B., Burkart, K., & Kiesecker, J. (2024). Mapping global land conversion pressure to support conservation planning. Scientific Data, 11(1), 830. https://doi.org/10.1038/s41597-024-03639-9
Sincerely,
Jon
p.s. this is a lovely mushroom I saw in West Virginia
