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Abstract Changes in land use and climate change threaten global biodiversity and ecosystems, calling for the urgent development of effective conservation strategies. Recognizing landscape heterogeneity, which refers to the variation in natural features within an area, is crucial for these strategies. While remote sensing images quantify landscape heterogeneity, they might fail to detect ecological patterns in moderately disturbed areas, particularly at minor spatial scales. This is partly because satellite imagery may not effectively capture undergrowth conditions due to its resolution constraints. In contrast, soundscape analysis, which studies environmental acoustic signals, emerges as a novel tool for understanding ecological patterns, providing reliable information on habitat conditions and landscape heterogeneity in complex environments across diverse scales and serving as a complement to remote sensing methods.We propose an unsupervised approach using passive acoustic monitoring data and network inference methods to analyse acoustic heterogeneity patterns based on biophony composition. This method uses sonotypes, unique acoustic entities characterized by their specific time‐frequency spaces, to establish the acoustic structure of a site through sonotype occurrences, focusing on general biophony rather than specific species and providing information on the acoustic footprint of a site. From a sonotype composition matrix, we use the Graphical Lasso method, a sparse Gaussian graphical model, to identify acoustic similarities across sites, map ecological complexity relationships through the nodes (sites) and edges (similarities), and transform acoustic data into a graphical representation of ecological interactions and landscape acoustic diversity.We implemented the proposed method across 17 sites within an oil palm plantation in Santander, Colombia. The resulting inferred graphs visualize the acoustic similarities among sites, reflecting the biophony achieved by characterizing the landscape through its acoustic structures. Correlating our findings with ecological metrics like the Bray–Curtis dissimilarity index and satellite imagery indices reveals significant insights into landscape heterogeneity.This unsupervised approach offers a new perspective on understanding ecological and biological interactions and advances soundscape analysis. The soundscape decomposition into sonotypes underscores the method's advantage, offering the possibility to associate sonotypes with species and identify their contribution to the similarity proposed by the graph.
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Zooming Out: Methods and Future Directions in Landscape‐Scale Functional Assessment of Inland Wetlands
ABSTRACT Wetlands play a vital role in supporting hydrologic, biogeochemical, and ecological processes across landscapes, yet understanding and quantifying their functional contributions at large spatial scales remains a challenge. In response to increasing demand for regional and national assessments, a growing number of methods have emerged that estimate wetland function using widely available geospatial data. This systematic review describes and evaluates currently available approaches to quantifying wetland function at landscape scales and highlights key lessons for future assessments. We identify two primary methodological categories: classification‐based approaches, such as hydrogeomorphic (HGM) and LLWW (Landscape Position, Landform, Water Flow Path, Waterbody Type) frameworks, which assign functional scores based on mapped wetland class; and indicator‐based approaches, which derive metrics or indices directly linked to functional processes using remote sensing and other spatial data. Across both, we find that validation against field data remains limited, habitat functions are consistently the most difficult to assess, and that many assessments estimate only thepotentialof wetlands to perform specific functions rather than how they are actually functioning under current landscape conditions. At the same time, advances in high‐resolution remote sensing, automation, and ecological modeling are creating new opportunities for more scalable, repeatable, and functionally relevant assessments. Hybrid approaches that bridge classification and indicator methods, and that integrate land‐use and disturbance metrics, represent a promising path toward national‐scale functional assessments. Together, these findings point to a way forward for producing wetland functional assessments that are both scientifically rigorous and actionable for conservation and policy. This article is categorized under:Water and Life > Nature of Freshwater EcosystemsWater and Life > Conservation, Management, and AwarenessScience of Water > Water and Environmental Change
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- Award ID(s):
- 2239715
- PAR ID:
- 10674282
- Publisher / Repository:
- Wiley
- Date Published:
- Journal Name:
- WIREs Water
- Volume:
- 13
- Issue:
- 1
- ISSN:
- 2049-1948
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript
- Journal Article:
- https://doi.org/10.1002/wat2.70044
