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Noise pollution can affect species' behaviours and distributions and may hold significant consequences for natural communities. While several studies have researched short-term effects of noise, no long-term research has examined whether observed patterns persist or if community recovery can occur. We used a long-term study system in New Mexico to examine the effects of continuous natural gas well noise exposure on seedling recruitment of foundational tree species ( Pinus edulis , Juniperus osteosperma ) and vegetation diversity. First, we examined seedling recruitment and vegetation diversity at plots where current noise levels have persisted for greater than 15 years. We then examined recruitment and diversity on plots where noise sources were recently removed or added. We found support for long-term negative effects of noise on tree seedling recruitment, evenness of woody plants and increasingly dissimilar vegetation communities with differences in noise levels. Furthermore, seedling recruitment and plant community composition did not recover following noise removal, possibly due in part to a lag in recovery among animals that disperse and pollinate plants. Our results add to the limited evidence that noise has cascading ecological effects. Moreover, these effects may be long lasting and noise removal may not lead to immediate recovery.
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Spatial patterning among savanna trees in high-resolution, spatially extensive data
In savannas, predicting how vegetation varies is a longstanding challenge. Spatial patterning in vegetation may structure that variability, mediated by spatial interactions, including competition and facilitation. Here, we use unique high-resolution, spatially extensive data of tree distributions in an African savanna, derived from airborne Light Detection and Ranging (LiDAR), to examine tree-clustering patterns. We show that tree cluster sizes were governed by power laws over two to three orders of magnitude in spatial scale and that the parameters on their distributions were invariant with respect to underlying environment. Concluding that some universal process governs spatial patterns in tree distributions may be premature. However, we can say that, although the tree layer may look unpredictable locally, at scales relevant to prediction in, e.g., global vegetation models, vegetation is instead strongly structured by regular statistical distributions.
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- Award ID(s):
- 1802453
- PAR ID:
- 10107018
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- Volume:
- 116
- Issue:
- 22
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- 10681 to 10685
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1073/pnas.1819391116
