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Palaeoenvironmental changes recorded at the Velika Vrbica loess-palaeosol sequence, Wallachian Basin, during MIS 3–MIS 1 瓦拉几亚盆地Velika Vrbica黄土-古土壤层序3 - 1期古环境变化记录
IF 2.9 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-05-13 DOI: 10.1111/bor.70009
Zoran M. Perić, Cathal S. Ryan, Warren Thompson, Milica G. Radaković, Petar Krsmanović, Helena Alexanderson, Slobodan B. Marković

This study presents a detailed investigation of the Velika Vrbica loess-palaeosol sequence, situated in the Wallachian Basin of northeastern Serbia, with the aim to reconstruct palaeoenvironmental changes spanning Marine Isotope Stages (MIS) 3 to 1. Using optically stimulated luminescence (OSL) dating, low field magnetic susceptibility (χlf), and mass accumulation rates (MARs), we have developed a robust geochronological framework and analysed sedimentary and environmental processes over the last glacial–interglacial cycle. The OSL chronology reveals consistent loess deposition from ~41 to 3 ka, with peak accumulation rates recorded during MIS 3 and late MIS 2. The MAR data challenge conventional models of loess formation, as higher deposition rates are observed during the interstadial MIS 3 compared to the Last Glacial Maximum. This finding suggests regional variations in aeolian activity and climate dynamics that differ from the widely accepted pattern of intensified dust deposition during colder glacial periods. The environmental magnetic record of the Velika Vrbica loess sequence presented here shows more similarities with equivalent sections in the Wallachian Basin than in the Vojvodina region. These findings contribute to the broader understanding of loess formation processes and palaeoenvironmental variability on a continental scale, reinforcing the importance of high-resolution chronological and sedimentological studies in disentangling global vs. regional influences on past dust deposition.

本文对位于塞尔维亚东北部瓦拉几亚盆地的Velika Vrbica黄土古土壤序列进行了详细的研究,旨在重建海洋同位素阶段(MIS) 3至1的古环境变化。利用光激发发光(OSL)测年、低磁场磁化率(χ f)和质量积累率(MARs),我们建立了一个强大的地质年代学框架,并分析了末次冰期-间冰期旋回的沉积和环境过程。OSL年代学显示~41 ~ 3ka的黄土沉积是一致的,在MIS 3和MIS 2后期记录了最大的积累速率。MAR数据挑战了传统的黄土形成模型,因为与末次盛冰期相比,在间冰期MIS 3观测到更高的沉积速率。这一发现表明,风沙活动和气候动力学的区域差异不同于广泛接受的在较冷的冰期加剧的沙尘沉积模式。本文提出的Velika Vrbica黄土层序的环境磁记录与瓦拉几亚盆地的等效剖面比伏伊伏丁那地区更相似。这些发现有助于在大陆尺度上更广泛地了解黄土形成过程和古环境变化,加强了高分辨率年代学和沉积学研究在解开全球与区域对过去粉尘沉积的影响方面的重要性。
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引用次数: 0
Comments on ‘Late Middle Pleistocene Wolstonian Stage (MIS 6) glaciation in lowland Britain and its North Sea regional equivalents – a review’ 英国低地和北海地区的“中更新世晚期沃尔斯通期(MIS 6)冰川作用”综述
IF 2.9 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-04-29 DOI: 10.1111/bor.70011
Harry E. Langford

Divergent views debated over the past 20 years on the Wolstonian depositional record of Fenland and the Peterborough area have centred on whether there is evidence of a single (middle or late) glaciation or of both a middle and a late glaciation. A recent review promoted a single late Wolstonian glaciation, despite there being incontrovertible evidence of extensive cold-stage gravels associated with glacially related drainage diversion both pre-dating and post-dating late Wolstonian interglacial deposits.

在过去的20年里,关于芬兰和彼得伯勒地区的沃尔斯通沉积记录,争论的不同观点集中在是否存在单一(中期或晚期)冰期或中期和晚期冰期的证据。尽管有无可争议的证据表明大量的冷期砾石与冰川相关的排水分流有关,但最近的一篇综述提出了一个单独的晚沃尔斯通期冰川作用,无论是在定年前还是定年后的晚沃尔斯通期间冰期沉积。
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引用次数: 0
Multiple indicators record human adaptations to climatic change during the Middle Holocene at the Wanbei site in the middle and lower Huai River valley, China 淮河中下游皖北遗址中全新世人类对气候变化的适应
IF 2.9 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-04-22 DOI: 10.1111/bor.70010
Weixin Tian, Wuhong Luo, Huiyuan Gan, Liugen Lin, Tianci Sun, Yajie Sun, Hanlin Xu, Caiwei Zhang, Xin Wang, Juzhong Zhang

The archaeological sediment successions from the Wanbei site provide an ideal case for reconstructing both natural and human-induced environmental changes in the middle and lower reaches of the Huai River valley located in the transitional zone of eastern China during the Middle Holocene. The findings of this work, in terms of phytoliths, pollen and spores, and chemical elemental analyses suggest that the climatic conditions that were recorded in the Wanbei profile responded well to broader climatic changes, with an overall warm and humid climate during 5700–5300 a BP, albeit with a cooling trend between 5600 and 5400 a BP. Rice (Oryza sativa) was always the main cereal crop in mixed rice-millet farming owing to warm and humid conditions, although the proportions of broomcorn millet (Panicum miliaceum) and foxtail millet (Setaria italica) significantly increased during the cooling period. The structural characteristics and adjustments of mixed farming over time show an adaptation strategy in response to the climatic changes at Wanbei. Furthermore, multiple indicators reveal that human activities at the Wanbei site would increase rather than decrease during the cooling period between 5600 and 5400 a BP. This study not only highlights the dynamic nature of early agricultural societies, but also enhances our understanding of their adaptation strategies in response to climatic changes in the middle and lower Huai River valley during the Middle Holocene.

皖北遗址的考古沉积物序列为重建中国东部过渡带淮河流域中下游中全新世的自然和人为环境变化提供了一个理想的案例。植物岩、花粉和孢子以及化学元素分析表明,皖北剖面记录的气候条件对更广泛的气候变化有很好的响应,在5700-5300 a BP期间总体气候温暖湿润,尽管在5600 - 5400 a BP之间有降温趋势。由于气候温暖湿润,水稻(Oryza sativa)一直是水稻-谷子混合耕作的主要谷类作物,但在降温时期,黍(Panicum miliaceum)和谷子(Setaria italica)的比例显著增加。皖北地区混合农业的结构特征及其随时间的调整显示出对气候变化的适应策略。此外,多项指标表明,在5600 ~ 5400 a BP的冷却期,皖北遗址的人类活动增加而不是减少。该研究不仅突出了早期农业社会的动态性质,而且有助于我们进一步了解全新世中期淮河中下游地区农业社会对气候变化的适应策略。
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引用次数: 0
Complex past ice flow from Norway to the North Sea Plateau during the Quaternary: evidence from Marstein Trough and earlier reconstructions using 3D seismic data sets 第四纪期间从挪威到北海高原的复杂过去冰流:来自Marstein海槽的证据和使用三维地震数据集的早期重建
IF 2.4 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-04-22 DOI: 10.1111/bor.70007
Dag Ottesen, James D. Kirkham, Julian A. Dowdeswell, Harald Brunstad, Morten Halvorsen

Based on a regional 3D seismic data set and a small high-resolution 3D seismic data set (~40 km2) we have mapped a buried glacially eroded trough on the North Sea Plateau, west of the Norwegian Channel (latitude 59°N, longitude 3°E). The trough, which we informally name Marstein Trough, is 60 km long, 30 km wide, 120 m deep, and trends NE–SW. Marstein Trough contains an extensive pattern of glacial lineations at its base, which follow the trough axis, and is infilled by two seismic units interpreted as tills. From its stratigraphical position, we infer that the trough was eroded by an ice stream that flowed from western Norway and crossed the Norwegian Channel in a southwesterly direction, probably during the penultimate, Saalian glaciation. Marstein Trough, and its diagnostic landforms, provide detailed evidence of complex, switching ice flow across the North Sea during the Quaternary. Westward ice flow from Norway took place during early Scandinavian Ice-Sheet build-up prior to the activation of the Norwegian Channel Ice Stream. In contrast, ice-flow patterns during full-glacial conditions caused ice flow to reorientate to a S–N direction when the Norwegian Channel Ice Stream with a huge catchment that included the Baltic was established. Our results highlight the complex patterns of ice flow experienced over this region of the North Sea, with implications for reconstructions of Quaternary history, modern renewable energy infrastructure installation, and glacial processes during the build-up phase of ice sheets.

基于区域三维地震数据集和小型高分辨率三维地震数据集(~40 km2),我们在挪威海峡以西的北海高原(北纬59°N,东经3°E)绘制了一个隐藏的冰川侵蚀槽。这个海槽,我们非正式地称之为马斯坦海槽,长60公里,宽30公里,深120米,向东北-西南方向移动。马斯坦海槽在其底部包含一个广泛的冰川线模式,它遵循海槽轴,并由两个地震单元填充,解释为斜坡。从它的地层位置,我们推断槽被一条冰流侵蚀,这条冰流从挪威西部流过,并向西南方向穿过挪威海峡,可能是在倒数第二个萨alian冰川时期。马斯坦海槽及其诊断地貌提供了第四纪期间北海复杂的、转换的冰流的详细证据。挪威向西的冰流发生在挪威海峡冰流激活之前的早期斯堪的纳维亚冰盖形成期间。相比之下,在全冰期条件下,当挪威海峡冰流与包括波罗的海在内的巨大集水区建立时,冰流模式导致冰流重新定向到南北向。我们的研究结果强调了北海这一地区经历的冰流的复杂模式,对第四纪历史的重建、现代可再生能源基础设施的安装以及冰盖形成阶段的冰川过程具有重要意义。
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引用次数: 0
The morphosedimentary record of glacial to postglacial environmental changes in West Wiyâshâkimî impact crater lake and adjacent areas, northern Québec, Canada 加拿大魁魁省北部Wiyâshâkimî陨石坑湖西部及邻近地区冰期至冰期后环境变化的形态沉积记录
IF 2.9 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-04-22 DOI: 10.1111/bor.70008
Etienne Brouard, Patrick Lajeunesse

Crater lakes in core regions of former ice sheets have the potential to preserve long-term sedimentary archives that are otherwise rare in glaciated landscapes due to pervasive glacial erosion. Lake Wiyâshâkimî, an impact crater lake located in the inner core of the Québec-Labrador Dome of the Laurentide Ice Sheet, provides a rare example of such a setting. The lake was therefore investigated along the region surrounding it through remotely sensed mapping and acoustic sub-bottom profiling to reconstruct its glacial to postglacial environmental evolution from its morphosedimentary record. Mapping of ice-flow landforms suggests three distinct glacial flowsets in the region, indicating a transition from external ice-stream influences to local topographical controls during deglaciation. Contrary to previous hypotheses, mapping evidence suggests that the Tyrrell Sea deglacial marine transgression did not reach Lake Wiyâshâkimî, with surrounding strandlines likely of glaciolacustrine origin. Five acoustic facies were identified from the analysis and interpretation of the acoustic sub-bottom profiles: AF1, bedrock, till and/or glacifluvial sands forming the acoustic basement; AF2, an acoustically transparent deposit filling the deeper basins of the lake, a fine-grained diamicton either associated with mass-movements or full glacial conditions (till); AF3A and AF3B, glaciolacustrine sediments deposited proximally and distally from the ice margin, respectively; and AF4, paraglacial and postglacial deposits that have been partly, at least in the upper tens of metres of the water column, remobilized by bottom currents induced by strong winds prevailing in the large lake. While our analysis shows it is unlikely that sediments pre-dating the last glaciation were preserved in the lake basin, the findings provide new insights into the lateglacial and deglacial history of the central Québec-Labrador region and highlight the role of postglacial processes in shaping the lake-bottom morphosedimentary archives.

以前冰盖核心区域的火山口湖有可能保存长期的沉积档案,否则由于普遍的冰川侵蚀,这些档案在冰川景观中是罕见的。Wiyâshâkimî湖是一个陨石坑湖,位于劳伦泰德冰原的qu -拉布拉多圆顶的内核,提供了这样一个罕见的例子。因此,通过遥感测绘和声学底剖面研究了该湖泊周围区域,根据其形态沉积记录重建了其冰川至冰期后的环境演化。冰流地貌的测绘表明,该地区有三种不同的冰川流,表明在消冰期间,从外部冰流影响到局部地形控制的转变。与先前的假设相反,制图证据表明,Tyrrell海冰川消融海侵没有到达Wiyâshâkimî湖,周围的海岸线可能是冰川湖的起源。通过对声学亚底剖面的分析和解释,确定了5种声学相:AF1、基岩、农田和/或形成声学基底的冰川河流砂;AF2,一种声音透明的沉积物,填充在湖泊较深的盆地中,一种细粒度的直径,要么与物质运动有关,要么与完全的冰川条件(till)有关;AF3A和AF3B分别为冰缘近端和远端沉积的冰川湖相沉积物;AF4是准冰期和冰期后的沉积物,至少在水柱的上几十米,被大湖盛行的强风引起的底流重新移动。虽然我们的分析表明,末次冰期之前的沉积物不太可能在湖盆中保存下来,但这些发现为研究中部曲萨梅克-拉布拉多地区的冰期和去冰期历史提供了新的见解,并突出了冰期后过程在形成湖底形态沉积档案中的作用。
{"title":"The morphosedimentary record of glacial to postglacial environmental changes in West Wiyâshâkimî impact crater lake and adjacent areas, northern Québec, Canada","authors":"Etienne Brouard,&nbsp;Patrick Lajeunesse","doi":"10.1111/bor.70008","DOIUrl":"https://doi.org/10.1111/bor.70008","url":null,"abstract":"<p>Crater lakes in core regions of former ice sheets have the potential to preserve long-term sedimentary archives that are otherwise rare in glaciated landscapes due to pervasive glacial erosion. Lake Wiyâshâkimî, an impact crater lake located in the inner core of the Québec-Labrador Dome of the Laurentide Ice Sheet, provides a rare example of such a setting. The lake was therefore investigated along the region surrounding it through remotely sensed mapping and acoustic sub-bottom profiling to reconstruct its glacial to postglacial environmental evolution from its morphosedimentary record. Mapping of ice-flow landforms suggests three distinct glacial flowsets in the region, indicating a transition from external ice-stream influences to local topographical controls during deglaciation. Contrary to previous hypotheses, mapping evidence suggests that the Tyrrell Sea deglacial marine transgression did not reach Lake Wiyâshâkimî, with surrounding strandlines likely of glaciolacustrine origin. Five acoustic facies were identified from the analysis and interpretation of the acoustic sub-bottom profiles: AF1, bedrock, till and/or glacifluvial sands forming the acoustic basement; AF2, an acoustically transparent deposit filling the deeper basins of the lake, a fine-grained diamicton either associated with mass-movements or full glacial conditions (till); AF3A and AF3B, glaciolacustrine sediments deposited proximally and distally from the ice margin, respectively; and AF4, paraglacial and postglacial deposits that have been partly, at least in the upper tens of metres of the water column, remobilized by bottom currents induced by strong winds prevailing in the large lake. While our analysis shows it is unlikely that sediments pre-dating the last glaciation were preserved in the lake basin, the findings provide new insights into the lateglacial and deglacial history of the central Québec-Labrador region and highlight the role of postglacial processes in shaping the lake-bottom morphosedimentary archives.</p>","PeriodicalId":9184,"journal":{"name":"Boreas","volume":"55 1","pages":"110-133"},"PeriodicalIF":2.9,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bor.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146154867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Automated delineation and morphometry of unclassified subglacial bedforms 未分类冰下河床的自动描绘和形态测量
IF 2.9 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-04-01 DOI: 10.1111/bor.70003
Sofyane Hesni, Paul Bessin, Edouard Ravier, Olivier Bourgeois, Jean Vérité, Jean-François Buoncristiani

We designed an automated tool to delineate and analyse the shape of subglacial bedforms using a recently defined land surface parameter, the volumetric obscurance. The tool is based on the assumption that the diversity of subglacial bedform shapes reflects a continuum; therefore, unlike traditional methods, no pre- or post-mapping classification of bedforms is performed. It uses digital elevation models and optical satellite images to generate regional morphological maps (bedform outlines and crestlines) and regional morphometric maps (spatialized statistical analysis of bedform morphometrics). We tested the tool on the ArcticDEM, over a portion of the former Laurentide Ice Sheet bed that displays a wide diversity of bedform shapes (Keewatin Ice Dome, northern Canada). The produced morphological maps are consistent, with a correspondence of approximately 75% on individual bedform outlines, with two reference maps digitized manually by two different glacial geomorphologists. Despite the 25% difference between individual bedform outlines generated automatically and manually, the derived morphometric maps are similar. They can be interpreted in the context of subglacial deformation and hydrology, providing a new potential for palaeoglaciological reconstructions at the ice-sheet scale. The tool was developed in Python and is freely accessible.

我们设计了一个自动化工具来描述和分析冰下床的形状,使用最近定义的陆地表面参数,体积遮挡。该工具基于这样一种假设:冰下河床形状的多样性反映了一个连续体;因此,与传统方法不同的是,该方法不进行测绘前或测绘后的地层分类。它使用数字高程模型和光学卫星图像生成区域形态图(河床轮廓和峰顶线)和区域形态测量图(河床形态测量的空间化统计分析)。我们在ArcticDEM上测试了这个工具,在前Laurentide冰原床的一部分上,显示了各种各样的床形形状(加拿大北部的Keewatin冰穹)。生成的形态图与两张参考图是一致的,在单个床型轮廓上的对应度约为75%,这两张参考图是由两位不同的冰川地貌学家手工数字化的。尽管自动和手动生成的单个床型轮廓之间存在25%的差异,但导出的形态测量图是相似的。它们可以在冰下变形和水文的背景下解释,为冰盖尺度上的古冰川学重建提供了新的潜力。该工具是用Python开发的,可以免费访问。
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引用次数: 0
Relative sea-level trends in southern Norway during the last millennium 挪威南部在过去一千年的相对海平面趋势
IF 2.4 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-03-25 DOI: 10.1111/bor.70006
Max Holthuis, F. Chantel Nixon, Malin E. Kylander, Willem G. M. van der Bilt, Isabel Hong, Kristen M. Joyse, Thomas R. Lakeman, Jake Martin, Maria Peter, Simon Solheim Holme, Benjamin P. Horton

Geological reconstructions of relative sea level (RSL) from southern Norway show falling RSL during the last 7000 cal. a BP, but tide gauge measurements document a slow RSL rise since at least 1960 CE. With an age gap of c. 1400 years between the youngest geologically reconstructed sea-level index point (SLIP) and the installation of the Tregde tide gauge in southernmost Norway, the exact nature and timing of the onset of RSL rise in southern Norway remain unknown. To fill this gap, we collected peat cores from a salt marsh to reconstruct RSL trends over the past 1000 years using a multiproxy approach, including 210Pb and 14C dating, grain-size analysis, loss-on-ignition (LOI), geochemistry (stable carbon isotopes, carbon to nitrogen ratios and XRF) and diatoms. Our data suggest decreasing tidal current strength and salinity over most of the last millennium, suggesting falling RSL. Sediment geochemistry also appears to vary with wetter and drier climatic periods. An increase in marine-brackish diatoms in combination with an acceleration in sedimentation rates after 1930 CE (1899–1954 CE) suggest that the onset of RSL rise began around this time in southernmost Norway. While most of the proxy data appear to have delayed sensitivity to RSL changes and may be linked to other causal processes, they, nonetheless, provide valuable insight into the environmental response of high-latitude temperate salt marshes to slow rates of RSL change.

挪威南部相对海平面(RSL)的地质重建显示,在过去的7000年里,相对海平面(RSL)下降。一个BP,但潮汐计的测量结果显示,至少从公元1960年开始,RSL就在缓慢上升。最年轻的地质重建海平面指数点(SLIP)与挪威最南端的Tregde潮汐计的安装之间存在约1400年的年龄差距,因此挪威南部RSL上升的确切性质和时间仍然未知。为了填补这一空白,我们收集了来自盐沼的泥炭岩芯,使用多代理方法重建了过去1000年的RSL趋势,包括210Pb和14C测年、粒度分析、着火损失(LOI)、地球化学(稳定碳同位素、碳氮比和XRF)和硅藻。我们的数据表明,在过去一千年的大部分时间里,潮流强度和盐度都在下降,这表明RSL在下降。沉积物地球化学也随着湿润和干燥的气候期而变化。海洋半咸淡硅藻的增加,加上沉积速率的加速,表明RSL的上升大约在这个时候开始在挪威最南端。虽然大多数代理数据似乎延迟了对RSL变化的敏感性,并且可能与其他因果过程有关,但它们仍然为高纬度温带盐沼对RSL缓慢变化速率的环境响应提供了有价值的见解。
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引用次数: 0
Response to Comment on ‘Automatic identification of streamlined subglacial bedforms using machine learning: an open-source Python approach’ 对“使用机器学习自动识别冰下流线型河床:一种开源的Python方法”评论的回应
IF 2.4 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-03-23 DOI: 10.1111/bor.70004
Marion McKenzie, Ellianna Abrahams, Fernando Pérez, Ryan Venturelli
<p>Li <i>et al</i>. (<span>2025</span> this issue) state that they identify areas for improvement to our development of bedfinder through including more data sets at training, evaluating our filtering methods, and exploring modular approaches of the tool. Here we respond to these Comments by highlighting where we have already addressed each of these areas within our work and notably, our supporting information (Abrahams <i>et al</i>. <span>2024</span>). In our paper, we describe that bedfinder is an inherently modular tool, allowing a user to choose which components of the pipeline might be useful to them. Furthermore, bedfinder already allows a user to customize the choice to over- or under-predict a glacially derived bedform assignment. In Abrahams <i>et al</i>. (<span>2024</span>) we previously justified why we made the choice to over-predict, emphasizing the need for manual post-processing, which we reiterate here. Finally, we reshare statements from the ‘Model limitations’ section of Abrahams <i>et al</i>. (<span>2024</span>) where we also recommend incorporating additional data in future tool creation to strengthen our approach.</p><p>The objective of Abrahams <i>et al</i>. (<span>2024</span>) was to build an open-source tool that would allow for the automatic detection of glacially derived streamlined subglacial bedforms, based on the previous successes of manual approaches (e.g. Clark <span>1993</span>; Greenwood & Clark <span>2008</span>; Spagnolo <i>et al</i>. <span>2014</span>; Ely <i>et al</i>. <span>2016</span>; Principato <i>et al</i>. <span>2016</span>; Clark <i>et al</i>. <span>2018</span>). To develop this tool, we used Random Forest (Breiman <span>2001</span>), XGBoost (Chen & Guestrin <span>2016</span>), and an ensemble average of these two model fits on a publicly available training data set of nearly 600 000 data points across the deglaciated Northern Hemisphere (McKenzie <i>et al</i>. <span>2022</span>). Li <i>et al</i>. (<span>2025</span>) suggest a constructive critique to our approach stating our work should include more data sets at training, further evaluate our filtering methods, and explore better modularizing bedfinder. However, these suggestions have either already been implemented as existing features of bedfinder (i.e. modularity of pipeline components and tunability of bedform predictions to the needs of the user) or we have already named them in our study as known limitations of the tool that will require wider community participation (the creation of larger, more nuanced machine learning data sets for model training).</p><p>Abrahams <i>et al</i>. (<span>2024</span>) outlined the limitations of the presented approach in the section ‘Model limitations’. There, we state that the ‘TPI tool used to compile our training set performs most poorly in regions with highly elongate bedforms with low surface relief (McKenzie <i>et al</i>. <span>2022</span>)’ (i.e. bedforms across crystalline bedrock surfaces) (Abrah
Li等人(2025年本刊)指出,他们通过在训练中纳入更多数据集,评估我们的过滤方法,以及探索工具的模块化方法,确定了我们在床寻床器开发中需要改进的领域。在这里,我们通过强调我们在工作中已经解决的每个领域,特别是我们的支持信息来回应这些评论(亚伯拉罕等人,2024)。在我们的论文中,我们描述了寻床器是一个固有的模块化工具,允许用户选择哪些管道组件可能对他们有用。此外,寻床器已经允许用户自定义选择,以高估或低估冰川衍生的床型分配。在亚伯拉罕等人(2024)中,我们之前证明了为什么我们选择过度预测,强调需要手动后处理,我们在这里重申。最后,我们重新分享了Abrahams等人(2024)的“模型限制”部分的陈述,我们还建议在未来的工具创建中加入额外的数据,以加强我们的方法。亚伯拉罕等人(2024)的目标是建立一个开源工具,该工具将允许自动检测冰川衍生的流线型冰下河床,基于先前的成功的人工方法(例如Clark 1993;格林伍德,克拉克2008年;Spagnolo et al. 2014;Ely et al. 2016;Principato et al. 2016;Clark et al. 2018)。为了开发这个工具,我们使用了Random Forest (Breiman 2001), XGBoost (Chen &amp;Guestrin 2016),这两个模型的集合平均值可以在一个公开可用的训练数据集上进行拟合,该数据集包含北半球冰川消融的近60万个数据点(McKenzie et al. 2022)。Li等人(2025)对我们的方法提出了建设性的批评,指出我们的工作应该包括更多的训练数据集,进一步评估我们的过滤方法,并探索更好的模块化寻床器。然而,这些建议要么已经作为bedfinder的现有功能(即管道组件的模块化和对用户需求的床型预测的可调性)实现,要么我们已经在我们的研究中将它们命名为需要更广泛社区参与的工具的已知限制(创建更大,更细致的机器学习数据集用于模型训练)。亚伯拉罕等人(2024)在“模型限制”一节中概述了所提出方法的局限性。在这里,我们声明“用于编译我们的训练集的TPI工具在具有低表面起伏的高度细长的床型区域(McKenzie等人,2022)(即跨越结晶基岩表面的床型)(Abrahams等人,2024)中表现最差”,Li等人(2025)也在他们的评论中指出了这一点。Li等人(2025)的进一步评论反映了TPI工具的性能和优势,这不是Abrahams等人(2024)的重点,而是McKenzie等人(2022)的重点。即便如此,选择对数据进行二元分类的理由在亚伯拉罕等人(2024)的“模型限制”部分得到了解释。Li等人(2025)提出的克服训练数据集限制的解决方案在Abrahams等人(2024)的“工具进步的未来方向”一节中明确概述。与Li et al.(2025)提出的解决方案几乎相同,我们在原始工作中表示,“未来纳入额外的训练数据,增加低地形和多向冰流的代表性”将有助于克服bedfinder的这些缺陷(Abrahams et al. 2024)。在他们的评论中,Li等人(2025)声称,鉴于训练数据中固有的类不平衡,Abrahams等人(2024)使用的性能指标混淆了真实的性能,尽管事实上这种关注正是支持信息数据S2的主要焦点。在那里,我们强调了我们对F1分数的关注,将其作为类别不平衡情况下模型选择的首选指标,因为它的使用“防止了过度乐观的评估”,并且“平衡了低假阳性和假阴性率”(Abrahams等人,2024)。我们建议感兴趣的读者阅读He和Garcia(2009),以了解更多关于F1分数在阶级失衡情况下的有用性(Flach &amp;库尔2015是另一个很好的资源)。我们想强调的是,应该含蓄地理解,Abrahams等人(2024)的表2中的性能指标只能在训练集分布内的测试中实现。为了研究潜在的分布转移,我们在分布外(OOD)样本上验证了寻床器,详见“通过Green Bay Lobe地层子集进行模型验证”一节,发现寻床器在论文中进行调整后,在那里恢复了79%的真阳性。Li等人。 (2025)建议保留个别地区作为测试数据,我们确信他们会很高兴看到亚伯拉罕等人(2024)的那一部分已经完成了这一分析。在本文中,我们分享了新区域的ROC曲线和我们公开提供的随附材料(abraham &amp;麦肯齐2024)我们分享了召回率、准确率和F1分数。我们借此机会重申,训练数据集的地点选择限制了模型将结果外推到具有地形约束或基岩类型不在分布范围(OOD)的新区域的能力。本文中工具对OOD数据的任何应用在统计上都是不可靠的,但仍将为分析冰川消融景观中流线型冰下河床的存在提供一个起点”(Abrahams et al. 2024)。如上所述,寻床仪并不是唯一的解决方案,而是科学实践者希望在冰川消退的景观中自动化描述地形的一些过程的起点。在声称Abrahams等人(2024)歪曲了将我们的模型方法调整为高估假阳性(导致包含错误检测)而不是调整为高估假阴性(导致排除分布边缘的确定形态)的含义时,Li等人(2025)似乎暗示用户会不加选择地应用此工具而不仔细评估其结果。这显然违背了我们的论文和文档中概述的使用建议。我们的论文不仅明确了模型对过度预测的调整,我们还建议读者从所有三个模型拟合中进行推断,并在任何新数据上比较论文中的结果,以帮助手动后处理。此外,在公开可用的工具文档中,我们指出了读者如何使用我们的工具来调整他们希望高估的假阴性(亚伯拉罕和;麦肯齐2024)。在进一步的声明中,Li等人(2025)指出,亚伯拉罕等人(2024)没有“充分探索”假阳性和假阴性之间的权衡。我们不同意这种观点,因为F1分数可以很好地描述这种权衡,F1分数通常用于评估班级不平衡情况下的表现(He &amp;加西亚2009;Flach,如上所述,并在支持信息数据S2中共享,其中我们声明“出于这个原因,我们在整个工作中主要关注F1分数”。此外,图4A所示的ROC曲线(Abrahams et al. 2024)探讨了这一论点。Li等人(2025)还建议,在进行模型选择时,我们应该使用精度-召回率曲线(精度vs召回率)而不是ROC曲线(真阳性率vs假阳性率);然而,正如Flach &amp;Kull(2015)和其他地方,在类别不平衡的情况下,精确召回率曲线可能会产生误导,相反,已经广泛建立的ROC曲线对类别比例不敏感(Fawcett 2006),因此是一种更稳定的方法。最近,McDermott等人(2024)证明,精确召回率曲线下的面积是模型选择的一个明确的偏见和歧视指标,并建议在最小化假阴性比最小化假阳性更重要的情况下依赖ROC曲线下的面积,这是我们论文所陈述的需求。Li等人(2025)不同意我们将模型拟合偏向假阳性的选择;然而,在任何ML模型中,都有一个调整选择,将模型偏向于过度预测(更多假阳性)或低估(更多假阴性),这在不平衡数据集中是固有的冲突(Chawla 2005)。因为我们知道后处理对任何用户来说都是一个可行的选择,事实上,我们向任何实现我们工具的从业者推荐这一点,为了
{"title":"Response to Comment on ‘Automatic identification of streamlined subglacial bedforms using machine learning: an open-source Python approach’","authors":"Marion McKenzie,&nbsp;Ellianna Abrahams,&nbsp;Fernando Pérez,&nbsp;Ryan Venturelli","doi":"10.1111/bor.70004","DOIUrl":"https://doi.org/10.1111/bor.70004","url":null,"abstract":"&lt;p&gt;Li &lt;i&gt;et al&lt;/i&gt;. (&lt;span&gt;2025&lt;/span&gt; this issue) state that they identify areas for improvement to our development of bedfinder through including more data sets at training, evaluating our filtering methods, and exploring modular approaches of the tool. Here we respond to these Comments by highlighting where we have already addressed each of these areas within our work and notably, our supporting information (Abrahams &lt;i&gt;et al&lt;/i&gt;. &lt;span&gt;2024&lt;/span&gt;). In our paper, we describe that bedfinder is an inherently modular tool, allowing a user to choose which components of the pipeline might be useful to them. Furthermore, bedfinder already allows a user to customize the choice to over- or under-predict a glacially derived bedform assignment. In Abrahams &lt;i&gt;et al&lt;/i&gt;. (&lt;span&gt;2024&lt;/span&gt;) we previously justified why we made the choice to over-predict, emphasizing the need for manual post-processing, which we reiterate here. Finally, we reshare statements from the ‘Model limitations’ section of Abrahams &lt;i&gt;et al&lt;/i&gt;. (&lt;span&gt;2024&lt;/span&gt;) where we also recommend incorporating additional data in future tool creation to strengthen our approach.&lt;/p&gt;&lt;p&gt;The objective of Abrahams &lt;i&gt;et al&lt;/i&gt;. (&lt;span&gt;2024&lt;/span&gt;) was to build an open-source tool that would allow for the automatic detection of glacially derived streamlined subglacial bedforms, based on the previous successes of manual approaches (e.g. Clark &lt;span&gt;1993&lt;/span&gt;; Greenwood &amp; Clark &lt;span&gt;2008&lt;/span&gt;; Spagnolo &lt;i&gt;et al&lt;/i&gt;. &lt;span&gt;2014&lt;/span&gt;; Ely &lt;i&gt;et al&lt;/i&gt;. &lt;span&gt;2016&lt;/span&gt;; Principato &lt;i&gt;et al&lt;/i&gt;. &lt;span&gt;2016&lt;/span&gt;; Clark &lt;i&gt;et al&lt;/i&gt;. &lt;span&gt;2018&lt;/span&gt;). To develop this tool, we used Random Forest (Breiman &lt;span&gt;2001&lt;/span&gt;), XGBoost (Chen &amp; Guestrin &lt;span&gt;2016&lt;/span&gt;), and an ensemble average of these two model fits on a publicly available training data set of nearly 600 000 data points across the deglaciated Northern Hemisphere (McKenzie &lt;i&gt;et al&lt;/i&gt;. &lt;span&gt;2022&lt;/span&gt;). Li &lt;i&gt;et al&lt;/i&gt;. (&lt;span&gt;2025&lt;/span&gt;) suggest a constructive critique to our approach stating our work should include more data sets at training, further evaluate our filtering methods, and explore better modularizing bedfinder. However, these suggestions have either already been implemented as existing features of bedfinder (i.e. modularity of pipeline components and tunability of bedform predictions to the needs of the user) or we have already named them in our study as known limitations of the tool that will require wider community participation (the creation of larger, more nuanced machine learning data sets for model training).&lt;/p&gt;&lt;p&gt;Abrahams &lt;i&gt;et al&lt;/i&gt;. (&lt;span&gt;2024&lt;/span&gt;) outlined the limitations of the presented approach in the section ‘Model limitations’. There, we state that the ‘TPI tool used to compile our training set performs most poorly in regions with highly elongate bedforms with low surface relief (McKenzie &lt;i&gt;et al&lt;/i&gt;. &lt;span&gt;2022&lt;/span&gt;)’ (i.e. bedforms across crystalline bedrock surfaces) (Abrah","PeriodicalId":9184,"journal":{"name":"Boreas","volume":"54 2","pages":"277-280"},"PeriodicalIF":2.4,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bor.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809968","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Subglacial landscape formation and sediment discharge: relating basal conditions to bedform dimensions and properties at Rutford Ice Stream, West Antarctica 冰下景观的形成和沉积物的排出:南极洲西部Rutford冰流的基底条件与河床尺寸和性质的关系
IF 2.9 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-03-20 DOI: 10.1111/bor.70002
Rebecca Schlegel, Lucas K. Zoet, Adam D. Booth, Andrew M. Smith, Roger A. Clark, Alex M. Brisbourne

Basal conditions that facilitate fast ice flow are still poorly understood and their parameterization in ice-flow models results in high uncertainties in ice-flow and consequent sea-level rise projections. Direct observations of basal conditions beneath modern ice streams are limited due to the inaccessibility of the bed. One approach to understanding basal conditions is through investigating the basal landscape of ice streams and glaciers, which has been shaped by ice flow over the underlying substrate. Bedform variation together with observations of ice-flow properties can reveal glaciological and geological conditions present during bedform formation. Here we map the subglacial landscape and identify basal conditions of Rutford Ice Stream (West Antarctica) using different visualization techniques on novel high-resolution 3D radar data. This novel approach highlights small-scale features and details of bedforms that would otherwise be invisible in conventional radar grids. Our data reveal bedforms of <300 m in length, surrounded by bedforms of >10 km in length. We correlate variations in bedform dimensions and spacing to different glaciological and geological factors. We find no significant correlation between local (<3 × 3 km) variations in bedform dimensions and variations in ice-flow speed and (surface or basal) topography. We present a new model of subglacial sediment discharge, which proposes that variations in bedform dimensions are primarily driven by spatial variation in sediment properties and effective pressure. This work highlights the small-scale spatial variability of basal conditions and its implications for basal slip. This is critical for more reliable parameterization of basal friction of ice streams in numerical models.

促进快速冰流的基本条件仍然知之甚少,它们在冰流模式中的参数化导致冰流和随之而来的海平面上升预测的高度不确定性。由于河床难以接近,对现代冰流下的基本条件的直接观测是有限的。了解基础条件的一种方法是通过调查冰流和冰川的基础景观,这些景观是由下面的基材上的冰流形成的。河床变化与冰流特性的观测可以揭示河床形成过程中存在的冰川和地质条件。在这里,我们绘制了冰下景观,并利用不同的可视化技术在新的高分辨率三维雷达数据上确定了Rutford冰流(西南极洲)的基本条件。这种新颖的方法突出了传统雷达网格中不可见的小尺度特征和地形细节。我们的数据显示,长300米的地层被长10公里的地层包围。我们将河床尺寸和间距的变化与不同的冰川和地质因素联系起来。我们发现,局部(3 × 3公里)的地形尺寸变化与冰流速度和(表面或基底)地形变化之间没有显著的相关性。我们提出了一个新的冰下沉积物流量模型,该模型提出了沉积物性质和有效压力的空间变化主要驱动了河床尺寸的变化。这项工作强调了基础条件的小尺度空间变异性及其对基础滑移的影响。这对于在数值模型中更可靠地参数化冰流的基础摩擦是至关重要的。
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引用次数: 0
Reassessing the predictive power of bedfinder: insights into machine learning for subglacial bedform detection – Comments on ‘Automatic identification of streamlined subglacial bedforms using machine learning: an open-source Python approach’ 重新评估寻床器的预测能力:对冰下床形态检测的机器学习的见解-对“使用机器学习自动识别流线型冰下床形态:开源Python方法”的评论
IF 2.4 3区 地球科学 Q2 GEOGRAPHY, PHYSICAL Pub Date : 2025-03-17 DOI: 10.1111/bor.70005
Ming Li, Huanyu Zhao, Tianfei Yu
<p>The integration of machine learning (ML) into geomorphological research presents significant opportunities for automating the identification of streamlined subglacial bedforms. In their study, Abrahams <i>et al</i>. (<span>2024</span>) introduce bedfinder, an open-source Python tool designed to detect subglacial features with high efficiency. While the tool demonstrates promise, this discussion highlights critical challenges and areas for refinement. The representativeness of the training data set, dominated by sedimentary bed conditions, limits the model's generalizability to regions with diverse bedrock compositions. Additionally, the reliance on binary classifications oversimplifies complex geomorphic settings, reducing the model's adaptability. Performance metrics such as F1 scores, though favourable, warrant cautious interpretation due to class imbalances that may skew predictions. Furthermore, the integration of filtering techniques, while enhancing precision, raises concerns about potential biases from manual data curation. To enhance scientific rigour, future efforts should incorporate diverse data sets, conduct comprehensive evaluations of filtering methods, and explore modular approaches for greater applicability. Addressing these challenges will not only strengthen bedfinder but also contribute to the evolving role of ML in advancing glacial and geomorphological research. This contribution provides a constructive critique to guide future improvements and interdisciplinary applications of this innovative tool.</p><p>Abrahams <i>et al</i>. (<span>2024</span>) present a cutting-edge approach to the identification of streamlined subglacial bedforms, which are crucial in understanding past glacial dynamics and their impact on geomorphology. The authors have developed an open-source Python tool, bedfinder, that employs supervised ML algorithms – Random Forest and XGBoost – to automate the identification of these features across deglaciated landscapes. This tool is an ambitious attempt to enhance efficiency and accuracy in a domain traditionally burdened by labour-intensive, subjective, and time-consuming manual processes. The authors also provide a thorough validation of the model using an extensive data set of known subglacial bedforms from various regions in the Northern Hemisphere.</p><p>While the study contributes valuable insights into how ML can automate the mapping of complex glacial features, several critical issues arise from the selection of data, the application of ML methods, and the interpretation of results. Here, we will highlight some of these issues and offer suggestions to enhance the scientific robustness of the study and its potential applications. The concerns outlined here include the representativeness of the training data, the challenges in interpreting the performance metrics, and the potential over-simplifications in model design and validation.</p><p>A central issue in Abrahams <i>et al</i>. (<span>2024</span>)
将机器学习(ML)集成到地貌学研究中,为自动识别流线型冰下河床提供了重要的机会。在他们的研究中,Abrahams等人(2024)介绍了bedfinder,这是一种开源的Python工具,旨在高效地探测冰下特征。虽然该工具展示了前景,但本次讨论强调了关键的挑战和需要改进的领域。训练数据集的代表性以沉积层条件为主,限制了模型在基岩成分不同地区的推广能力。此外,对二元分类的依赖过度简化了复杂的地貌设置,降低了模型的适应性。F1成绩等表现指标虽然有利,但由于等级不平衡可能会影响预测,因此需要谨慎解读。此外,过滤技术的集成在提高精度的同时,也引起了对人工数据管理潜在偏见的担忧。为了提高科学的严谨性,未来的工作应该纳入不同的数据集,对过滤方法进行全面的评估,并探索模块化方法以获得更大的适用性。解决这些挑战不仅将加强寻床者,而且有助于ML在推进冰川和地貌学研究中的作用不断发展。这一贡献提供了一个建设性的批评,以指导未来的改进和跨学科的应用这一创新的工具。亚伯拉罕等人(2024)提出了一种识别流线型冰下河床的前沿方法,这对于理解过去的冰川动力学及其对地貌的影响至关重要。作者已经开发了一个开源的Python工具,bedfinder,它使用监督机器学习算法——随机森林和XGBoost——来自动识别冰川消退景观中的这些特征。该工具是一个雄心勃勃的尝试,旨在提高传统上由劳动密集型、主观和耗时的手动过程负担的领域的效率和准确性。作者还利用来自北半球不同地区的已知冰下地层的大量数据集,对该模型进行了彻底的验证。虽然这项研究为机器学习如何自动绘制复杂冰川特征提供了有价值的见解,但从数据的选择、机器学习方法的应用和结果的解释中出现了几个关键问题。在这里,我们将重点介绍其中的一些问题,并提出建议,以提高研究的科学稳健性及其潜在的应用。这里概述的关注点包括训练数据的代表性,解释性能度量的挑战,以及模型设计和验证中潜在的过度简化。Abrahams等人(2024)的核心问题在于训练数据的选择。作者使用的数据集主要来自沉积层条件,这在模型的预测能力中引入了固有的偏差。冰下床型,如流线型山脊和沟槽,深受多种因素的影响,包括下伏基岩组成、地形和冰川动力学。因此,这些特征所在景观的多样性在决定模型在不同冰川环境中推广的能力方面起着至关重要的作用。然而,本研究中使用的数据集严重偏重于沉积层,只有有限的结晶层条件的代表。这种不平衡限制了模型在主要以结晶或混合基岩为特征的地区的适用性,从而潜在地降低了模型在这些条件普遍存在的环境中的准确性。因此,在这些代表性不足的地区,该模型可能难以准确地检测和分类冰下河床,这可能导致对潜在地貌过程的误解。训练数据中的沉积优势表明,该模型适用于冰川侵蚀更明显的环境,以及河床可能表现出更大的起伏对比的环境。然而,这样的条件可能不能准确地反映在其他冰川地形中发现的床型特征的范围。例如,在结晶基岩上形成的冰川特征在地形表达方面往往更为柔和,并且它们可能表现出现有数据集未充分代表的独特形式(Skyttä等人。2023;Courtney-Davies et al. 2024)。因此,该模型可能难以以高精度检测这些特征,从而导致对非沉积地形的冰下河床的少报或错误分类。此外,将地层条件简化为沉积型和结晶型,地形划分为约束型和约束型。 不受约束的分类,过度简化了冰川景观固有的复杂性。现实世界的地貌系统通常表现为基岩和地形类型的连续统一体,并在这些类别之间逐渐过渡(Tani 2013;斯图尔特,Jamieson 2018)。对床层条件进行严格分类的选择忽略了更复杂的混合环境的可能性,例如基岩特征和地形限制以微妙或过渡形式存在的区域。因此,这种方法限制了模型处理不完全适合这些预定义类别的区域的灵活性。事实上,混合基岩或过渡基岩地区的冰川床型在相同的气候条件下可能表现不同(Oetting et al. 2022;Olesen et al. 2023)。例如,沉积基岩和结晶基岩共存的地区可能表现出冰流、侵蚀和沉积之间的相互作用,这与在均质环境中观察到的典型模式不相符(Xie et al. 2022;Huang et al. 2023)。这些区域可能对模型构成挑战,因为有限的训练数据集无法捕捉到地质和地形因素之间独特的相互作用。这个问题的解决方案在于扩展训练数据集,以更好地代表冰川环境的多样性。该模型的未来迭代应纳入来自显示更多种基岩类型(包括火山、变质岩和混合成分)的区域的数据集,以及跨越从受约束到无约束设置的整个光谱的地形特征。通过整合来自北极、南极和其他高纬度冰川地区的数据,该模型将更广泛地了解不同条件下冰下河床的表现。此外,分类系统可以被改进,以捕捉存在于不同基岩和地形类型中的细微变化。与其依赖于二元分类,作者可以开发一个多层系统,其中包括混合或过渡环境的子类别。这将允许在各种地质和地形因素的相互作用至关重要的地区进行更精确的模型预测。此外,结合特定区域的元数据和环境变量,如冰川流动动力学、沉积物输运特征和冰盖厚度变化,可以提高模型的预测能力。这些变量将为解释不同地区特定的冰川历史和河床特征提供必要的背景,从而使模型能够根据每个地点独特的环境条件调整其预测。Abrahams等人(2024)报告了令人印象深刻的性能指标,随机森林和集成模型的F1分数都超过了94%。然而,这些数字必须根据训练数据中存在的明显的阶级不平衡来看待。该数据集包含超过60万个正地形特征,但其中只有一小部分被确定为真正的冰下河床。这在感兴趣的类别(冰川床型)和非冰川特征(如岩石露头、沉积异常等)之间造成了固有的不平衡,这有可能扭曲模型的性能。在涉及类别不平衡的机器学习任务中,像准确率这样的标准评估指标可能会产生误导,因为模型可以通过预测主要类别(在这种情况下,“非床型”特征)来实现高精度,而无需识别真正的床型。为了解释这一点,作者使用了额外的指标,如精度、召回率和F1分数,这些指标更好地反映了模型检测真阳性的能力,同时最大限度地减少假阳性和假阴性。虽然这些指标表明了强大的模型性能,但作者没有充分解决类不平衡对这些结果的影响。作者正确地指出,该模型倾向于过度预测假阳性(特别是在OOD区域)是优先检测形态而不是避免假阳性的结果。虽然这种方法对于缺少一个行为形式比错误分类一个非行为形式更有问题的应用程序来说是可以接受的,但是完全理解这种决策的含义仍然是必要的。误报——非冰川特征被错误地分类为河床——可能会显著改变对景观的解释,导致对过去冰流动力学和冰川行为的错误假设。此外,假阴性率虽然通过模型强调恢复更多的床型隐含地解决了问题,但没有得到充分的探讨。在某些情况下,较高的假阳性率可能是可取的,但与假阴性的权衡需要仔细评估。 例如,在地貌复杂的地区,非冰川特征的存在可能导致大量的假阳性检测,这可能会破坏模型预测的科学价值。为了提高结果的稳健性,对假阳性和假阴性之间的权衡进行更全面的评估将是有益的。作者可以采用精确召回曲线(Saito &amp;Rehmsmeier 2017;Fu et al. 2019;Williams 2021)来更详细地评估模型的性能。这将有助于更好地理解不同的分类阈值如何影响准确率和召回率之间的平衡,最终为模型在各种环境中的实际效用提
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