Fowler N, Keitt T, Schmidt O, Terry M, Trout K
. Border wall: bad for biodiversity
. Frontiers in Ecology and the Environment. 16 (3) :137-138. fowler_et_al_2018_frontiers_border_wall_letter.pdf
Salas A, Altieri AH, Wilson P, Keitt TH
. Predicting the reef acoustic cuescape from the perspective of larval fishes across a habitat quality gradient.
MARINE ECOLOGY PROGRESS SERIE. 605 :173-193.Abstract
ABSTRACT: The combined acoustic activity of soniferous organisms living in benthic habitats produces habitat-specific soundscapes, which are predicted to influence fish and invertebrate lar- val behavior during the settlement process. Not every sound will have the amplitude and fre- quency characteristics relative to hearing sensitivity to be used as an acoustic cue, thus the cuescape is a subset of the soundscape. These sounds vary through space and time, and little is known about how this variability could influence their role in settlement. We recorded the sound- scapes of 4 coral reefs in Caribbean Panama for 6 wk and conservatively identified the sounds most likely to compose the cuescapes used by larval fishes. While these sites represented the vari- ation in reef condition across the study area, we observed the same 4 dominant taxa groups emerge as the most likely producers of acoustic cues. These results were consistent across both time and space when compared to short-term recordings taken at these 4 reefs and at an addi- tional 11 sites 2 yr prior. Next, we used an individual-based model to test the relationship between settlement success and the natural spatiotemporal variability we observed in these potential cues. Temporal variation in the sounds resulted in variation in settlement success; however, even short- range, intermittent cues improved the likelihood of settlement. Overall, we observed similar acoustic cuescapes across reefs that varied in condition, suggesting that cuescapes can be resilient to some forms of reef degradation by retaining sounds potentially useful to larval fishes for both navigation and habitat selection.
KEY WORDS: Coral reef · Soundscape · Larval fish · Larval settlement · Acoustics · Modeling · Cues · Fish behavior
Dietze MC, Fox A, Beck-Johnson LM, Betancourt JL, Hooten MB, Jarnevich CS, Keitt TH, Kenney MA, Laney CM, Larsen LG, et al. Iterative near-term ecological forecasting: Needs, opportunities, and challenges
. Proceedings of the National Academy of Sciences [Internet]. Publisher's VersionAbstract
Two foundational questions about sustainability are “How are ecosystems and the services they provide going to change in the future?” and “How do human decisions affect these trajectories?” Answering these questions requires an ability to forecast ecological processes. Unfortunately, most ecological forecasts focus on centennial-scale climate responses, therefore neither meeting the needs of near-term (daily to decadal) environmental decision-making nor allowing comparison of specific, quantitative predictions to new observational data, one of the strongest tests of scientific theory. Near-term forecasts provide the opportunity to iteratively cycle between performing analyses and updating predictions in light of new evidence. This iterative process of gaining feedback, building experience, and correcting models and methods is critical for improving forecasts. Iterative, near-term forecasting will accelerate ecological research, make it more relevant to society, and inform sustainable decision-making under high uncertainty and adaptive management. Here, we identify the immediate scientific and societal needs, opportunities, and challenges for iterative near-term ecological forecasting. Over the past decade, data volume, variety, and accessibility have greatly increased, but challenges remain in interoperability, latency, and uncertainty quantification. Similarly, ecologists have made considerable advances in applying computational, informatic, and statistical methods, but opportunities exist for improving forecast-specific theory, methods, and cyberinfrastructure. Effective forecasting will also require changes in scientific training, culture, and institutions. The need to start forecasting is now; the time for making ecology more predictive is here, and learning by doing is the fastest route to drive the science forward. 1710231115.full_.pdf