Remote Sensing in Ecology and Conservation最新文献

{"title":"Environmental Stressors Influence Spatial Complexity in a Fluvial Macrophyte meadow","authors":"Arthur de Grandpré, Christophe Kinnard, Andrea Bertolo","doi":"10.1002/rse2.70084","DOIUrl":"https://doi.org/10.1002/rse2.70084","url":null,"abstract":"Submerged aquatic vegetation (SAV) are a key element of aquatic ecosystems, having a strong influence on their structure and functioning. Because of their key effect on aquatic habitats and the scale‐dependent mechanisms driving their distribution (e.g., local facilitation vs. stress driven inhibition), we expect the spatial complexity of SAV landscapes to be an indicator of ecological integrity and ecosystem resilience. In this paper, we analyze the fine‐scale spatial complexity of SAV along spatial gradients of environmental stress in the largest fluvial lake of the St. Lawrence River, in Quebec, Canada. The hypothesis that spatial complexity metrics of SAV landscapes are sensitive to environmental changes was tested by using very high‐resolution remote sensing and a public database of field observations related to water quality and SAV. Multivariate spatial correlation analysis was used to generate a composite index of spatial complexity, as well as to define dominant environmental gradients. In this specific context, generalized additive models revealed that, while water depth and SAV abundance are strong predictors of spatial complexity, variation explained by the interaction between depth, SAV abundance, and water quality was an important predictor for the multidimensional variation of spatial complexity. Specifically, both light and nutrient limitations correlated with a decrease in SAV spatial complexity, especially in dense meadows. Despite the limits of the space‐for‐time substitution approach and the use of context‐dependent methods, this work represents a rare example of a remote sensing‐based application of the use of SAV as a fine scale ecological indicator. These results suggest that a systematic monitoring of SAV by remote sensing over long time periods could offer high‐value ecological data for both conservation and management.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"149 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148408834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Comparison of Mobile Laser Scanning Data Acquisition Methods in Closed Forest, Open Woodland and Sub‐Alpine Woodland Ecosystems","authors":"Johann Tiede, Karin Reinke, Trung H. Nguyen, Simon Jones","doi":"10.1002/rse2.70090","DOIUrl":"https://doi.org/10.1002/rse2.70090","url":null,"abstract":"Mobile laser scanning (MLS) provides an efficient and accurate method for measuring vegetation structure, increasingly providing new and important information for ecological research and landscape monitoring. However, the effects of varying MLS sampling densities on the characterisation of vegetation structure, particularly across ecosystems differing in structural complexity, remain underexplored. Here, we present the first direct assessment of how structural complexity influences the relationship between MLS sampling density and the derivation of structural metrics. A five‐level sampling framework was applied across open woodland, closed forest and sub‐alpine woodland ecosystems, enabling effects of structural complexity to be determined directly, rather than inferred across independent studies. We found that increasing scanning time by approximately 50%–100% (2–4 min) in 1225 m <jats:sup>2</jats:sup> study plots significantly improved data quality by increasing the diversity of observation angles and achieving a more even distribution of sensor positions within each plot, thereby mitigating occlusion. At the shortest sampling paths, stem detection was reduced by approximately 55%–80% relative to the longest paths, with large proportional reductions observed in all vegetation types. Mean canopy height differences between the shortest and longest paths reached 4.4 m in closed forest stands, compared to ~1–1.7 m in less complex vegetation. Furthermore, voxel occupancy analysis revealed that shorter paths tended to undersample key vegetation layers, such as the upper canopy and understory, while longer paths enabled improved horizontal penetration, particularly where structural complexity was high. Path length densities of approximately 0.18–0.25 m per m <jats:sup>2</jats:sup> of plot area (equivalent to 225–300 m of acquisition path in a 35 × 35 m plot) achieved using a structured gridded trajectory were generally required to obtain reliable estimates of vegetation structure. However, some metrics, particularly ground height, were less sensitive to reduced sampling density in open environments.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"145 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148365280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Passive Acoustic Identification of Social Groups in the Hainan Gibbon","authors":"Emmanuel Kabuga, Emmanuel Dufourq, Nonhlanhla L. Luphade, Samuel T. Turvey, Heidi Ma, Susan M. Cheyne, Hui Lui, Jessica V. Bryant, Qing Chen, Wenyong Li, Zhiwei Liu, Zhaoli Zhou, Stefan Britz, Bubacarr Bah, Ian Durbach","doi":"10.1002/rse2.70088","DOIUrl":"https://doi.org/10.1002/rse2.70088","url":null,"abstract":"Passive monitoring based on audio or camera recordings is a valuable tool for wildlife conservation and management. The Hainan gibbon ( <jats:styled-content style=\"fixed-case\"> <jats:italic>Nomascus hainanus</jats:italic> </jats:styled-content> ), with a global population of approximately 42 individuals, is one of the world's rarest mammals, and establishing effective monitoring approaches to understand the species' landscape use and population dynamics is a conservation priority. Hainan gibbons live in small social groups that share limited vocal characteristics. Although previous research has identified both species‐ and individual‐specific vocal signatures in gibbon calls, no studies have examined the identification of social groups from their vocalizations. We assessed the possibility of identifying gibbon social groups from their calls using deep learning, analyzing 98 8‐h recordings from three groups collected between 2015 and 2016. In a closed population with known groups, the best models recognized the calling gibbon groups with 95.24% average accuracy. When matching pairs of calls without knowledge of all groups, models identified pairs of calls with 90.70% average accuracy, falling to 64.89% for calls from unseen groups during training. Training on call sequences improved identification accuracy more than training on individual segments. Pooling votes from segment‐based predictions helped but was less effective than full sequence models. Deep learning outperformed random forests, especially on sequence‐based tasks. Analysis of confounding factors showed that gibbon acoustic signatures, not background noise, primarily influenced identification accuracy. These findings highlight the possibility of identifying gibbon social groups from their calls and the potential of deep learning to enhance acoustic passive monitoring efforts.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"41 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148365281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Airborne Laser Scanning and Sentinel‐2 to Understand Subcanopy Light Regimes and Understory Diversity of Vascular Plants in Temperate Mountain Forests","authors":"Felix Wieland‐Glasmann, Cornelius Senf, Kristin H. Braziunas, Rupert Seidl, Peter Annighöfer","doi":"10.1002/rse2.70086","DOIUrl":"https://doi.org/10.1002/rse2.70086","url":null,"abstract":"Canopy cover modulates the subcanopy light regime in forests—variations in canopy cover alter both, the amount and spatial distribution of light, representing the source of energy for plants. Because plant species differ regarding their adaptations to light, canopy‐driven light regimes play a key role in structuring understory composition and diversity. Here, we evaluated if Airborne Laser Scanning (ALS) and Sentinel‐2 can map subcanopy light regimes across three study sites ( <jats:italic>n</jats:italic> = 244 plot locations) along the German Alps. We then examined how understory vascular plant species richness varies with subcanopy light regimes. We found light availability increases linearly (Adj. <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> 0.84/RMSE 0.09) with ALS‐derived gap proportion (i.e., inverse of canopy cover), whereas light variability (Adj. <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> 0.46/RMSE 0.05) follows a hump‐shaped pattern. The relationship between the subcanopy light regime and vascular plant species richness in the understory (Adj. <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> 0.39/RMSE 12.77), was equally well described by ALS‐derived gap proportion (Adj. <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> 0.40/RMSE 12.70). Canopy cover described by NDWI from Sentinel‐2 showed similar relationships and could be used to characterize light availability (Adj. <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> 0.43/RMSE 0.18), light variability (Adj. <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> 0.21/RMSE 0.06), and understory vascular plant species richness (Adj. <jats:italic>R</jats:italic> <jats:sup>2</jats:sup> 0.31/RMSE 13.70), albeit with lower variance explained. Understory vascular plant species richness increased with higher light availability and variability, indicating that canopy cover heterogeneity is an important driver of biodiversity next to overall canopy cover. Using spaceborne sensor systems might enable repeatable, large‐scale mapping of canopy cover and thus also understory diversity, as our results suggest such sensors provide similar insights as gold‐standard ALS data, which remain scarce. Understanding the links between canopy cover, the subcanopy light regime, and understory diversity is therefore essential for predicting vegetation dynamics and supporting biodiversity‐oriented forest management.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"17 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148289528","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Tracking Wintertime Behaviour of Emperor Penguins Using High‐Resolution Synthetic Aperture Radar Imagery","authors":"Michelle LaRue, Daniel Price, Sarah Wiki‐Bennett, Charles K. Lee, B. Jack Pan, Kyle McCloud, Heather Cruickshank, Alex Ponniah, Daniel Zitterbart, Alexander Winterl, Céline Le Bohec, Rose Foster‐Dyer, Peter Fretwell","doi":"10.1002/rse2.70083","DOIUrl":"https://doi.org/10.1002/rse2.70083","url":null,"abstract":"Gaining insight into population changes of species in remote areas of the world poses challenges, often resulting in opportunistic observations (convenience sampling) that limit scientific inference. Remote sensing resources, typically high‐resolution optical imagery, have revolutionised population ecology especially in polar regions like Antarctica and now many species have been censused. However, estimates based on remote sensing often remain limited to convenience sampling, rather than allowing observation at times of year that provide more information about the breeding population. Here we introduce a proof of concept using high‐resolution synthetic aperture radar (SAR) imagery to detect, enumerate and track behaviours of emperor penguins during the Antarctic winter. Using 25–30 cm Umbra SAR imagery, we gathered images at six colonies of emperor penguins during winter 2024 to determine phenology, to gain insight to the breeding population and advance a new method for breeding population observations. We found that emperor penguins are identifiable on fast ice and that SAR‐based observations match concurrent field observations (at Atka Bay). Total huddle area correlated with average colony size at emperor penguin colonies, and we found that larger colonies tended to use more space on the fast ice than smaller colonies. We demonstrate that the breeding population of emperor penguins during winter can be estimated using a combination of SAR imagery with phenological‐behavioural models. Given that models suggest emperor penguins may be quasi‐extinct before 2100, our work provides an important next step in understanding the approximate size and phenology of the breeding population, information that would be required for conservation of the species and for area‐based conservation such as evaluation of the Ross Sea Marine Protected Area (MPA), where ~33% of emperor penguins exist.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"272 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148289745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inferring Brown Bear Hair Snare Interactions by Automatically Detecting Bipedalism on Camera Trap Images Using Pose Estimation and a Multilayer Perceptron","authors":"Arnau Campanera‐Moliné, Víctor Sazatornil, Lluís Brotons, Felipe Lumbreras Ruiz, Robert Benavente, Maguiña Ramilo‐Henry, Cristina Ramos, Santiago Palazón, Daniel Ponsa","doi":"10.1002/rse2.70081","DOIUrl":"https://doi.org/10.1002/rse2.70081","url":null,"abstract":"Hair snares, consisting of strands of barbed wire that collect tufts of fur, have long been used as a noninvasive sampling technique for DNA‐based monitoring of different species of bears. However, to prevent cross‐contamination by other animals or different bear individuals, frequent visits by technicians are required to collect samples and clean snares, a highly demanding process in terms of time and resources that hampers scalability. In the Catalan Pyrenees, only 24.6% of the visiting efforts come out positive, highlighting the need for automated, scalable solutions that can operate independently of cellular networks or human intervention. This study proposes a novel methodology to automatically infer hair snare interactions by detecting bipedalism in images acquired by camera traps. This is implemented by using a state‐of‐the‐art deep learning model for pose estimation, combined with a multilayer perceptron (MLP) to classify bipedalism or quadrupedy based on predicted keypoints. Due to the lack of annotated bear pose datasets, a custom dataset of 2373 images collected in the Catalan Pyrenees was manually annotated with 15 anatomical keypoints. Using YOLOv11, the trained pose estimation model achieved a keypoint inference precision of 93.2%, while the MLP reached an accuracy of 96.1% in distinguishing bipedalism from quadrupedy. Finally, to enable inference on the edge, several verification strategies are proposed using only the pose estimation output, including bear geometrical illustrations derived from the inferred keypoints. This innovative lightweight solution, designed for satellite‐based transmission, enables scalable deployment in low‐connectivity and remote areas, significantly reducing the need for frequent manual inspections.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"168 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148289928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying Migratory Bat Movements in Central Europe Across Seasons and Years Using a Vertical‐Looking Radar","authors":"Silvia Giuntini, Janine Aschwanden, Damiano G. Preatoni, Fabian Hertner, Birgen Haest, Baptiste Schmid","doi":"10.1002/rse2.70076","DOIUrl":"https://doi.org/10.1002/rse2.70076","url":null,"abstract":"Bat migration is an ecologically important yet poorly understood phenomenon. This is in part because monitoring these migrations is challenging, due to bats' nocturnal behaviors and their sometimes high‐altitude migratory flights. This study presents the first radar‐based examination of multi‐annual migratory bat phenology in Europe, utilizing vertical‐looking radar data collected on the Swabian Plateau in Germany between September 2019 and December 2022. Bat activity was consistently low in winter and increased gradually from March onwards to a peak between July and September. Across all years, pre‐maternity migration began between late February and mid‐March, while post‐maternity migration ended between late October and mid‐November. We estimated peak radar‐based migration traffic rates between 1159 and 2473 bats per km, with the highest peak recorded on 4 July 2022. Correlations between radar‐derived nightly bat numbers and simultaneously acquired acoustic recordings ranged from 0.47 to 0.70 for the pre‐maternity season, and from 0.14 to 0.71 during post‐maternity migration. Both monitoring techniques showed peak bat activity during the summer, with smaller surges in September and October. The radar, however, detected significantly more bats overall. These findings showcase how vertical‐looking radars can be used to quantify and characterize seasonal variability in high‐altitude bat movements. Through strategic future radar deployments and the analysis of available historical datasets, our current understanding of migratory bat seasonality, routes, and intensity could increase drastically, and underpin the development of effective protocols for biodiversity conservation.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"26 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147751682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ground‐based robotic remote sensing for standardized biodiversity monitoring in coastal habitats","authors":"Giovanni Di Lorenzo, Simonetta Bagella, Micaela del Valle Rasino, Maria Laura Carranza, Manolo Garabini, Franco Angelini","doi":"10.1002/rse2.70074","DOIUrl":"https://doi.org/10.1002/rse2.70074","url":null,"abstract":"Autonomous remote‐sensing technologies are increasingly contributing to biodiversity monitoring by enabling scalable, repeatable, and minimally invasive data collection. We present a ground‐based robotic remote‐sensing framework that integrates artificial intelligence and standardized quality assurance to support the derivation of decision‐ready ecological indicators. Using European coastal dunes as a case study, we deployed an AI‐enabled quadruped robot equipped with near‐ground imaging sensors to monitor the host–herbivore interaction between <jats:italic>Pancratium maritimum</jats:italic> and <jats:italic>Brithys crini</jats:italic> . In this citizen‐to‐robot pipeline, expert‐verified citizen‐science imagery was used to train lightweight detection models for on‐board inference and higher‐capacity models for offline auditing, ensuring reproducibility and transparency across missions. Field trials demonstrated that the system achieved consistent image quality, accurate detections, and low‐disturbance operation under natural conditions, capturing spatially explicit evidence of herbivory and host condition. By coupling standardized protocols with robotic autonomy, this approach implements a proximal remote‐sensing layer that complements aerial and satellite observations. The workflow is designed to support transferable quantification of species interactions and habitat condition across sites and seasons, contributing to the integration of robotics and ecological remote sensing for biodiversity assessment and conservation management.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"83 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147681802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling forest dynamics using integral projection models and repeat lidar","authors":"Alice Rosen, Robin Battison, Christina M. Hernández, Oliver G. Spacey, Jessica McLean, Suzanne M. Prober, Samuel J. L. Gascoigne, Sean McMahon, Tommaso Jucker, Roberto Salguero‐Gómez","doi":"10.1002/rse2.70050","DOIUrl":"https://doi.org/10.1002/rse2.70050","url":null,"abstract":"Estimating tree life histories and population dynamics is key to predicting how forests respond to climate change and disturbance. However, linking individual tree trajectories to whole‐forest outcomes (e.g. structural, compositional, and functional health) remains challenging. Stage‐structured demographic models offer a promising solution, but they typically require extensive field data on individual‐level vital rates (e.g. survival and growth), limiting their application at scale. Here, we demonstrate an approach that integrates repeat airborne lidar data with a structured demographic model (an integral projection model, IPM) to examine forest‐wide demography in response to environmental drivers. Using Australia's Great Western Woodlands as a case study, we model the survival, growth, and life expectancy of ~40 000 eucalypt trees over a decade. Vital rates were modelled using height for small trees and crown area for large trees, reflecting a shift in growth strategy with size. Our results indicate distinct responses of small and large trees to proxies for competition and soil moisture (local canopy density and topographic wetness index, respectively). A reduction in topographic wetness index—reflecting drier conditions—led to lower life expectancy, particularly for larger trees, which may be more vulnerable to drought. This framework enables demographic analysis at scale, using widely available lidar data, offering a scalable tool for forest monitoring, modelling, and management. We identify three priorities for broader application, including (1) mixed species stands and multilayered canopies, (2) full life cycle modelling including reproduction and early life stages, and (3) long‐term or comparative studies using high‐quality repeat lidar. By combining remote sensing data with detailed insights from field‐based studies, our study provides a scalable approach for guiding forest management and conservation decisions.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"33 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147655661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable low‐cost seabed landers: the missing link for sustained, integrated, long‐term observations in dynamic shallow seas","authors":"Arienne Calonge, Roeland Develter, Carlota Muñiz, Clea Parcerisas, Jan Reubens, Wieter Boone, Klaas Deneudt, Elisabeth Debusschere","doi":"10.1002/rse2.70072","DOIUrl":"https://doi.org/10.1002/rse2.70072","url":null,"abstract":"Shallow coastal seas are increasingly affected by accelerating climate change and widespread anthropogenic pressures, yet consistent, long‐term monitoring data remain scarce and fragmented. Many existing observations are restricted to project‐specific objectives, limiting their potential contribution to broader‐scale assessments. Seabed landers, when equipped with a range of biotic and abiotic sensors, offer a non‐invasive and cost‐effective solution for ecosystem‐scale monitoring of Essential Biodiversity Variables (EBVs) and Essential Ocean Variables (EOVs). Examples of EBVs and EOVs include marine mammal distribution, fish movement, underwater sound, plankton biomass and diversity, sea surface height, currents, and temperature. The integration of datasets improves our ability to address ecological questions across larger spatial and temporal scales. Incorporating biodiversity monitoring data into the Digital Twin of the Ocean, a high‐resolution multi‐dimensional virtual representation of the ocean, marks a critical step toward large‐scale, standardized ecosystem‐based assessments of ocean health. Strengthening infrastructure, data management capabilities, and protocols will further unlock the potential of seabed observatories to inform conservation efforts and policy development, particularly through the application of artificial intelligence. In this article, a perspective on the capacity of subsea observatories is presented, specifically on multi‐purpose seabed landers, to deliver scalable, sustained, and high‐resolution observations of EOVs and EBVs over large areas.","PeriodicalId":21132,"journal":{"name":"Remote Sensing in Ecology and Conservation","volume":"18 1","pages":""},"PeriodicalIF":5.5,"publicationDate":"2026-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147586192","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}