LiDAR Surveys Research Articles

Long‐term shifts in feedbacks among glacier surface change, melt generation and runoff, McMurdo Dry Valleys, Antarctica

AbstractGlaciers of the McMurdo dry valleys (MDVs) Antarctica are the main source of streamflow in this polar desert. Because summer air temperatures hover near 0°C small changes in the energy balance strongly affect meltwater generation. Here we demonstrate that increased surface roughness, which alters the turbulent transfer of energy between the ice surface and atmosphere, yields a detectable increase in meltwater runoff. At low elevations on the glaciers, basin‐like topography became significantly rougher over 13 years between repeat lidar surveys, yielding greater melt. In contrast, the smoother ice at higher elevation exhibited no detectable change in roughness. We pose a conceptual model of the cycle of glacier surface change as a result of climate forcing whereby glacier surfaces transition from being dominated by sublimation to becoming increasingly melt‐dominated, which is reversible under prolonged cool periods. This research advances our understanding of warm season effects on polar glaciers.

UNHIDING FORESTED LANDSCAPES. THE ARCHAEOLOGICAL INDEX OF SOUTH-EASTERN CARPATHIANS

Starting with late 2018, a new archaeological research project has been unfolding in the framework funded by the Romanian Governmental Unit for Research and Development (UEFISCDI) dedicated to top fundamental research, as one of the few winners of 2016 edition (the single to date) of ‘Complex Projects for Frontier Research’ competition. The Project, whose aims and methods will be shortly presented further, is entitled ‘Hidden Landscapes: Exploratory Remote-sensing for the Archaeology of the Lost Roads, Borders and Battlefields of South-Eastern Carpathians’ (HiLands). It implements a systematic and diachronic investigation of the historic strategic circulation corridors crossing the South-Eastern part of the Carpathian Mountains – the main gate used along ages by people transiting between Transylvania and the Danube or the Black Sea. In order to achieve such aims we have been exploring, starting from large scale LiDAR surveys, the circulation corridors’ diachronic archaeological fingerprint, preserved in the shape of repeatedly fortified landscapes. LiDAR surveys have been carried on continuously since 2018, by airplane, but also with portable sensors based on SLAM technology. The results of the LiDAR explorations were enhanced by field surveys, geophysical prospections and pin-pointed excavations, in order to elucidate the nature of anomalies or better contextualize the significance and layout of the roads’ routes. The results of these activities are resumed in a constantly updated, open access, online data base of archaeological sites - The archaeological index of South-Eastern Carpathians (AISEC). The current contribution details the essentials of HiLands research (aims, concepts, methods), in order to introduce in the scientific circuit the AISEC’s functions and instruments, ready to be used as citable work.

Removing residual airborne sensor motion for measuring seismic signals from a drone

Acquiring seismic data using drones requires excellent knowledge of the drone’s motion since positional measurements made from an airborne sensor represent a combination of sensor and ground motion. Recent advancements in laser Doppler vibrometry and repeat lidar surveys show that the frequency and resolution of non-contact motion measurements is increasing to the point necessary for measuring seismic signals. We explore the conditions under which separation of sensor motion from ground motion can be accomplished in practice. We assume (i) that the translation and rotation of a stabilized airborne sensor follows an analytic form in time that is either known or can be estimated from the sensor’s measurements, (ii) that the seismic signal we observe has compact support contained within the measurement window, and (iii) that the ground motion can be described by a rigid translation. We analyze the effectiveness of our signal separation problem as a function of peak signal, sensor noise level, sensor rotation angle, and sensor point sampling density by defining a boundary where SNR = 0 dB for various combinations of these parameters. We find that under the set of assumptions, lower rotation angles, lower sensor noise, and denser point samplings on the ground provide better signal separation using our method.

Rapid shrub expansion in a subarctic mountain basin revealed by repeat airborne LiDAR

As a consequence of increasing temperatures, a rapid increase in shrub vegetation has occurred throughout the circumpolar North and is expected to continue. Rates of shrub expansion are highly variable, both at the regional scale and within local study areas. This study uses repeat airborne LiDAR and field surveys to measure changes in shrub vegetation cover along with landscape-scale variations in a well-studied subarctic headwater catchment in Yukon Territory, Canada. Airborne LiDAR surveys were conducted in August 2007 and 2018, whereas vegetation surveys were conducted in summer 2019. Machine learning classification algorithms were used to predict shrub presence/absence in 2018 based on rasterized LiDAR metrics, with the best-performing model applied to the 2007 LiDAR to create binary shrub cover layers to compare between survey years. Results show a 63.3% total increase in detectable shrub cover >= 0.45 m in height between 2007 and 2018, with an average yearly expansion of 5.8%. These changes were compared across terrain derivatives to quantify the influence of topography on shrub expansion. Terrain comparisons show that shrubs are located in and are preferentially expanding into lower and flatter areas near stream networks, at lower slope positions and with a higher potential for topographic wetness. Overall, the findings from this research reinforce the documented increase in pan-Arctic shrub vegetation in recent years, quantify the variation in shrub expansion over terrain derivatives at the landscape scale, and demonstrate the feasibility of using LiDAR to compare changes in shrub properties over time.

Coastal Remote Sensing: Merging Physical, Chemical, and Biological Data as Tailings Drift onto Buffalo Reef, Lake Superior

On the Keweenaw Peninsula of Lake Superior, two stamp mills (Mohawk and Wolverine) discharged 22.7 million metric tonnes (MMT) of tailings (1901–1932) into the coastal zone off the town of Gay. Migrating along the shoreline, ca. 10 MMT of the tailings dammed stream and river outlets, encroached upon wetlands, and contaminated recreational beaches. A nearly equal amount of tailings moved across bay benthic environments into critical commercial fish spawning and rearing grounds. In the middle of the bay, Buffalo Reef is important for commercial and recreational lake trout and lake whitefish production (ca. 32% of the commercial catch in Keweenaw Bay, 22% along southern Lake Superior). Aerial photographs (1938–2016) and five LiDAR and multispectral over-flights (2008–2016) emphasize: (1) the enormous amounts of tailings moving along the beach; and (2) the bathymetric complexities of an equal amount migrating underwater across the shelf. However, remote sensing studies encounter numerous specific challenges in coastal environments. Here, we utilize a combination of elevation data (LiDAR digital elevation/bathymetry models) and in situ studies to generate a series of physical, chemical, and biological geospatial maps. The maps are designed to help assess the impacts of historical mining on Buffalo Reef. Underwater, sand mixtures have complicated multispectral bottom reflectance substrate classifications. An alternative approach, in situ simple particle classification, keying off distinct sand end members: (1) allows calculation of tailings (stamp sand) percentages; (2) aids indirect and direct assays of copper concentrations; and (3) permits determinations of density effects on benthic macro-invertebrates. The geospatial mapping shows how tailings are moving onto Buffalo Reef, the copper concentrations associated with the tailings, and how both strongly influence the density of benthic communities, providing an excellent example for the International Maritime Organization on how mining may influence coastal reefs. We demonstrate that when large amounts of mine tailings are discharged into coastal environments, temporal and spatial impacts are progressive, and strongly influence resident organisms. Next steps are to utilize a combination of hi-resolution LiDAR and sonar surveys, a fish-monitoring array, and neural network analysis to characterize the geometry of cobble fields where fish are successful or unsuccessful at producing young.

Hydrometeorological, glaciological and geospatial research data from the Peyto Glacier Research Basin in the Canadian Rockies

Abstract. This paper presents hydrometeorological, glaciological and geospatial data from the Peyto Glacier Research Basin (PGRB) in the Canadian Rockies. Peyto Glacier has been of interest to glaciological and hydrological researchers since the 1960s, when it was chosen as one of five glacier basins in Canada for the study of mass and water balance during the International Hydrological Decade (IHD, 1965–1974). Intensive studies of the glacier and observations of the glacier mass balance continued after the IHD, when the initial seasonal meteorological stations were discontinued, then restarted as continuous stations in the late 1980s. The corresponding hydrometric observations were discontinued in 1977 and restarted in 2013. Datasets presented in this paper include high-resolution, co-registered digital elevation models (DEMs) derived from original air photos and lidar surveys; hourly off-glacier meteorological data recorded from 1987 to the present; precipitation data from the nearby Bow Summit weather station; and long-term hydrological and glaciological model forcing datasets derived from bias-corrected reanalysis products. These data are crucial for studying climate change and variability in the basin and understanding the hydrological responses of the basin to both glacier and climate change. The comprehensive dataset for the PGRB is a valuable and exceptionally long-standing testament to the impacts of climate change on the cryosphere in the high-mountain environment. The dataset is publicly available from Federated Research Data Repository at https://doi.org/10.20383/101.0259 (Pradhananga et al., 2020).

On the use of Sentinel-2 satellites and lidar surveys for the change detection of shallow bathymetry: The case study of North Carolina inlets

Mapping bathymetric change is a core task for a wide range of navigation, research, monitoring, and design applications. Satellite-derived bathymetry (SDB) can support this activity, particularly when using data from a platform, like the Sentinel-2A/B twin mission of the Copernicus programme, which provides routine and repetitive image acquisition at 10 m spatial resolution. As a result, SDB can expand on the temporal and spatial scope of more conventional mapping methods, such as lidar (or multi-beam). In this study, we use SDB, in comparison with high-resolution airborne lidar bathymetry (ALB), to quantify bathymetric changes at two inlets in North Carolina following the impacts of the devastating Hurricane Florence in September 2018. A recently developed multi-temporal SDB model that overcomes problems associated with turbidity and noise effects (whitecaps, ships, cloud shadows, etc.) is used with Sentinel-2 imagery. We identify bathymetric changes in shallow areas with navigation channels in two of the most dynamic inlets in the Outer Banks, Oregon and Hatteras. Multiple lidar surveys are used to validate the SDB method and for an assessment of accuracy and vertical uncertainty. The multi-temporal SDB products and ALB both show similar results in the erosion/accretion patterns. Comparing the change determined from the two methods, gives a median absolute error of ~0.5 m of SDB compared with ALB, with bias of ±0.2 m for depths ≤7 m; errors that are equivalent to those associated with the SDB estimated absolute depths. The composited SDB yields greater spatial coverage than lidar because it can retrieve data in areas where the lidar mission may have been constrained by turbidity or surf, and also because of the 300-km swath width. The Sentinel-2 constellation provides five-day revisit at the equator (more frequent at higher latitudes), allowing rapid construction of a bathymetric map as well as developing an archive for retrospective analysis. By implementing the multi-temporal turbidity correction, SDB based on Sentinel-2 may substantially enhance existing survey methods for change detection and support operational and recursive coastal monitoring on local to regional scales.

Beyond Newgrange: Brú na Bóinne in the later Neolithic

The Brú na Bóinne World Heritage Site, Ireland is best known for its megalithic monuments, in particular the great developed passage tombs of Knowth, Dowth, and Newgrange, and its abundance of megalithic art. However, our understanding of the wider Brú na Bóinne landscape has changed beyond all recognition in the last decade owing to the application of modern, non-invasive survey technologies – in particular LiDAR and large-scale geophysical survey – and most recently as a result of the hot, dry summer of 2018 which revealed a series of remarkable cropmarks between Newgrange and the River Boyne. Despite a lack of excavation it can be argued, based on their morphological characteristics, that many of the structures revealed belong within the corpus of late Neolithic ritual/ceremonial structures, including earthen henges, square-in-circle monuments, palisaded enclosures, and pit/post-alignments. These display both extraordinary diversity, yet also commonality of design and architecture, both as a group and with the passage tombs that preceded them. This paper provides an up-to-date survey of the late Neolithic and presumed late Neolithic landscape of Brú na Bóinne. It provides new evidence and new insights from ongoing survey campaigns, suggesting parallels within the British Neolithic but also insular development within some monument classes.

A multimethod approach to the study of Classic Maya houselots and land tenure: Preliminary results from the Three Rivers Region, Belize

Results of a recent lidar survey of northwestern Belize revealed a heavily modified anthropogenic landscape populated by dense ancient Maya settlement. Most surprising was the detection of an extensive network of landesque capital in form of linear stone features, with 87.8 linear km identified to date. While likely multifunctional, many of these features appear to delineate residential space and are similar in appearance to contemporary Maya houselots. This paper presents the results of a pilot project designed to collect preliminary data on houselots utilizing multiple research methods. Despite differences in land use and vegetation among the study loci, ground truthing results suggest the lidar data are high fidelity. Excavations produced mixed results, with architectural excavations providing the broadest array of data, including evidence that two of the houselots were occupied during the Late Classic (AD 600 – 850) period. Qualitative soil tests for available phosphorus detected elevated levels in areas that are consistent with middens and kitchen gardens. In addition, microtopographic anomalies were identified that may have represented an important household resource. A synthesis of the available data results in a view of large houselots with broad agricultural resource bases. Finally, settlement density and the ubiquity of demarcated houselots may signal the existence of a restricted-use land tenure system.

The impact of logging on vertical canopy structure across a gradient of tropical forest degradation intensity in Borneo

Abstract Forest degradation through logging is pervasive throughout the world's tropical forests, leading to changes in the three‐dimensional canopy structure that have profound consequences for wildlife, microclimate and ecosystem functioning. Quantifying these structural changes is fundamental to understanding the impact of degradation, but is challenging in dense, structurally complex forest canopies. We exploited discrete‐return airborne LiDAR surveys across a gradient of logging intensity in Sabah, Malaysian Borneo, and assessed how selective logging had affected canopy structure (Plant Area Index, PAI, and its vertical distribution within the canopy). LiDAR products compared well to independent, analogue models of canopy structure produced from detailed ground‐based inventories undertaken in forest plots, demonstrating the potential for airborne LiDAR to quantify the structural impacts of forest degradation at landscape scale, even in some of the world's tallest and most structurally complex tropical forests. Plant Area Index estimates across the plot network exhibited a strong linear relationship with stem basal area (R2 = 0.95). After at least 11–14 years of recovery, PAI was ~28% lower in moderately logged plots and ~52% lower in heavily logged plots than that in old‐growth forest plots. These reductions in PAI were associated with near‐complete lack of trees >30‐m tall, which had not been fully compensated for by increasing plant area lower in the canopy. This structural change drives a marked reduction in the diversity of canopy environments, with the deep, dark understorey conditions characteristic of old‐growth forests far less prevalent in logged sites. Full canopy recovery is likely to take decades. Synthesis and applications. Effective management and restoration of tropical forests requires detailed monitoring of the forest and its environment. We demonstrate that airborne LiDAR can effectively map the canopy architecture of the complex tropical forests of Borneo, capturing the three‐dimensional impact of degradation on canopy structure at landscape scales, therefore facilitating efforts to restore and conserve these ecosystems.

Robotic embankment

Automating earth-moving tasks has the potential to resolve labour-shortage, allow for unseen designs and foster sustainability through using on-site materials. In this interdisciplinary project involving robotics and landscape architecture, we combine our previous work on autonomous excavation of free-form shapes, dynamic landscape design and terrain modelling tools into a robotic landscape system. It tightly connects survey, design and fabrication to exchange information in real-time during fabrication. We purposely built a LiDAR survey drone for tight integration. The design environment contains terrain modelling tools to balance cut and fill volumes for material-neutral, on-site construction. Its parametric nature allows it to adapt the geometry to changing site conditions during fabrication. Our autonomous walking excavator is used to create these free-form shapes in natural granular material. We propose an excavation planner for free-form embankments that computes the next excavation location and subsequently the location where the excavated soil should be dumped. This robotic excavation system achieves the world’s first autonomous completion of free-form embankments with high accuracy. A 20hbox { m} long S-shaped and a two-faced embankment with a corner with roughly 0.03–0.05 m average error were created.

THREE-DIMENSIONAL TOPOGRAPHIC MAPPING OF VERTICAL AND OVERHANGING SURFACES OF COASTAL CLIFFS USING UAV-BASED LIDAR DATASET

The availability of high-density LiDAR datasets, enabled by UAV-based airborne laser scanning, has allowed topographic mapping surveyors to see unprecedented details on the earth’s surface. One of the problems faced in large-scale topographic mapping is generating proper three-dimensional contour lines for vertical cliffs, recesses, and overhangs, especially when the surface is covered by vegetation, which is quite common in the tropical area. This paper showcases the practical application of the LiDAR survey using an unmanned aerial vehicle and ground point classification process using the Simple Morphological Filter (SMRF) algorithm to produce high-fidelity, three-dimensional digital contour maps of coastal cliffs. By rotating the LiDAR dataset before the classification process to minimize overlapping surfaces, the entire dataset can be simulated as a 2.5-D surface. Therefore, the SMRF algorithm can be executed to classify all ground points on the cliff surface, including the overhangs and recesses. The resulting ground surface derived from this classification process provided a sufficient approximation of the real-world surface in overhanging cliffs and recesses while maintaining the conventional way to convey local landscape topography through three-dimensional contour lines.

Comprehensive bathymetry and intertidal topography of the Amazon estuary

Abstract. The characterization of estuarine hydrodynamics primarily depends on knowledge of the bathymetry and topography. Here, we present the first comprehensive, high-resolution dataset of the topography and bathymetry of the Amazon River estuary, the world's largest estuary. Our product is based on an innovative approach combining spaceborne remote sensing data, an extensive and processed river depth dataset, and auxiliary data. Our goal with this mapping is to promote the database usage in studies that require this information, such as hydrodynamic modeling or geomorphological assessments. Our twofold approach considered 500 000 sounding points digitized from 19 nautical charts for bathymetry estimation, in conjunction with a state-of-the-art topographic dataset based on remote sensing, encompassing intertidal flats, riverbanks, and adjacent floodplains. Finally, our estimate can be accessed in a unified 30 m resolution regular grid referenced to the Earth Gravitational Model 2008 (EGM08), complemented both landward and seaward by land (Multi-Error-Removed Improved-Terrain digital elevation model, MERIT DEM) and ocean (General Bathymetric Chart of the Oceans version 2020, GEBCO_2020) topographic data. Extensive validation against independent and spatially distributed data, from an airborne lidar survey, from ICESat-2 altimetric satellite data, and from various in situ surveys, shows a typical vertical accuracy of 7.2 m (riverbed) and 1.2 m (non-vegetated intertidal floodplains). The dataset is available at https://doi.org/10.17632/3g6b5ynrdb.2 (Fassoni-Andrade et al., 2021).

Tree Detection with a Mobile Laser Scanner

Tree detection has been considered in a number of forest-related applications, mostly related to the need of determining the presence and position of trees, and, in certain cases, the associated biomass. Most of the tree detection methods are typically based on the use of LiDAR surveys, and they often aim either at determining tree crowns or stems. This paper proposes the use of a low cost hand held device to acquire a good spatial description of the area close to the track reachable by the operator holding the acquisition device. Then, a tree detection method based on the local application of the Hough trasform is presented. The performance of the system is checked in an area hit by the Vaia storm in 2018.

Morphodynamic modeling of a low-lying barrier subject to hurricane forcing: The role of backbarrier wetlands

Along much of the world's coastline, coastal barriers serve as the first line of defense against oceanic and meteorological forces. Extreme storms cause large morphological changes on coastal barriers through high sediment transport rates, which may degrade their defensive capabilities. The understanding of morphological impacts is therefore important for coastal resiliency, but is often challenged by site-specific characteristics, such as land cover and sediment availability, and their poorly understood impacts on the governing physical processes. The Caminada Headlands, Louisiana, USA presents unique considerations for morphodynamic modeling with regard to its low-lying topography, variable land cover, nearshore muddy substrate and sand deficiency. This study investigates the effects of land cover and limited sediment supply on low-lying barrier island morphology under storm conditions by using physics-based numerical models. A high-resolution, local-scale sediment transport/morphodynamic model (XBeach) of the Caminada Headlands is verified for Hurricane Gustav's (2008) impact using pre- and post-storm LIDAR surveys. When accurate input data are used to create physics-based numerical models these tools are robust in hindcasting storm impacts and provide a wealth of information as to the governing processes, which is otherwise difficult to obtain observationally. The simulation results show that a short-duration overwash regime dominates the morphological change in this low-lying barrier and is influenced by backbarrier wetland deterioration. The morphological response to overwash is modulated by backbarrier land cover and topography, as reduced accommodation space limits landward transport during the subsequent inundation regime. An intact backbarrier marsh reduces landward washover sediment transport distances and promotes deposition at supratidal elevations. In light of these findings, simultaneous restoration/creation of backbarrier wetlands in conjunction with subaerial beach renourishment may be an effective form of increasing the resiliency of low-lying barriers subject to frequent overwashing.

Lidar survey of ancient Maya settlement in the Puuc region of Yucatan, Mexico.

The application of lidar remote-sensing technology has revolutionized the practice of settlement and landscape archaeology, perhaps nowhere more so than in the Maya lowlands. This contribution presents a substantial lidar dataset from the Puuc region of Yucatan, Mexico, a cultural subregion of the ancient Maya and a distinct physiographic zone within the Yucatan peninsula. Despite the high density of known sites, no large site has been fully surveyed, and little is known about intersite demography. Lidar technology allows determination of settlement distribution for the first time, showing that population was elevated but nucleated, although without any evidence of defensive features. Population estimates suggest a region among the most densely settled within the Maya lowlands, though hinterland levels are modest. Lacking natural bodies of surface water, the ancient Puuc inhabitants relied upon various storage technologies, primarily chultuns (cisterns) and aguadas (natural or modified reservoirs for potable water). Both are visible in the lidar imagery, allowing calculation of aguada capacities by means of GIS software. The imagery also demonstrates an intensive and widespread stone working industry. Ovens visible in the imagery were probably used for the production of lime, used for construction purposes and perhaps also as a softening agent for maize. Quarries can also be discerned, including in some cases substantial portions of entire hills. With respect to agriculture, terrain classification permits identification of patches of prime cultivable land and calculation of their extents. Lidar imagery also provides the first unequivocal evidence for terracing in the Puuc, indeed in all northern Yucatan. Finally, several types of civic architecture and architectural complexes are visible, including four large acropolises probably dating to the Middle Formative period (700–450 B.C.). Later instances of civic architecture include numerous Early Puuc Civic Complexes, suggesting a common form of civic organization at the beginning of the Late Classic demographic surge, (A.D. 600–750).

Maximizing Impacts of Remote Sensing Surveys in Slope Stability—A Novel Method to Incorporate Discontinuities into Machine Learning Landslide Prediction

This paper proposes a novel method to incorporate unfavorable orientations of discontinuities into machine learning (ML) landslide prediction by using GIS-based kinematic analysis. Discontinuities, detected from photogrammetric and aerial LiDAR surveys, were included in the assessment of potential rock slope instability through GIS-based kinematic analysis. Results from the kinematic analysis, coupled with several commonly used landslide influencing factors, were adopted as input variables in ML models to predict landslides. In this paper, various ML models, such as random forest (RF), support vector machine (SVM), multilayer perceptron (MLP) and deep learning neural network (DLNN) models were evaluated. Results of two validation methods (confusion matrix and ROC curve) show that the involvement of discontinuity-related variables significantly improved the landslide predictive capability of these four models. Their addition demonstrated a minimum of 6% and 4% increase in the overall prediction accuracy and the area under curve (AUC), respectively. In addition, frequency ratio (FR) analysis showed good consistency between landslide probability that was characterized by FR values and discontinuity-related variables, indicating a high correlation. Both results of model validation and FR analysis highlight that inclusion of discontinuities into ML models can improve landslide prediction accuracy.

What Factors Shape Spatial Distribution of Biomass in Riparian Forests? Insights from a LiDAR Survey over a Large Area

Riparian ecosystems are home to a remarkable biodiversity, but have been degraded in many regions of the world. Vegetation biomass is central to several key functions of riparian systems. It is influenced by multiple factors, such as soil waterlogging, sediment input, flood, and human disturbance. However, knowledge is lacking on how these factors interact to shape spatial distribution of biomass in riparian forests. In this study, LiDAR data were used in an individual tree approach to map the aboveground biomass in riparian forests along 200 km of rivers in the Meuse catchment, in southern Belgium (Western Europe). Two approaches were tested, relying either on a LiDAR Canopy Height Model alone or in conjunction with a LiDAR point cloud. Cross-validated biomass relative mean square error for 0.3 ha plots were, respectively, 27% and 22% for the two approaches. Spatial distribution of biomass patterns were driven by parcel history (and particularly vegetation age), followed by land use and topographical or geomorphological variables. Overall, anthropogenic factors were dominant over natural factors. However, vegetation patches located in the lower parts of the riparian zone exhibited a lower biomass than those in higher locations at the same age, presumably due to a combination of a more intense disturbance regime and more limiting growing conditions in the lower parts of the riparian zone. Similar approaches to ours could be deployed in other regions in order to better understand how biomass distribution patterns vary according to the climatic, geological or cultural contexts.

Recovery of logged forest fragments in a human-modified tropical landscape during the 2015-16 El Ni\xf1o

The past 40 years in Southeast Asia have seen about 50% of lowland rainforests converted to oil palm and other plantations, and much of the remaining forest heavily logged. Little is known about how fragmentation influences recovery and whether climate change will hamper restoration. Here, we use repeat airborne LiDAR surveys spanning the hot and dry 2015-16 El Niño Southern Oscillation event to measure canopy height growth across 3,300 ha of regenerating tropical forests spanning a logging intensity gradient in Malaysian Borneo. We show that the drought led to increased leaf shedding and branch fall. Short forest, regenerating after heavy logging, continued to grow despite higher evaporative demand, except when it was located close to oil palm plantations. Edge effects from the plantations extended over 300 metres into the forests. Forest growth on hilltops and slopes was particularly impacted by the combination of fragmentation and drought, but even riparian forests located within 40 m of oil palm plantations lost canopy height during the drought. Our results suggest that small patches of logged forest within plantation landscapes will be slow to recover, particularly as ENSO events are becoming more frequent.

Disentangling the effect of topography and microtopography on near-ground growing-season frosts at the boreal-temperate forest ecotone (Québec, Canada)

Permanent landscape attributes such as topography (elevation [m]) and microtopography (local variation in elevation [cm]) can increase the risk of cold air drainage down-slopes and in microtopographic depressions, causing important temperature gradients that generate localized growing-season frosts. Since most studies on growing-season frosts are restricted to the northern parts of the boreal forest or to mountainous areas, their negative consequences on tree productivity at the boreal-temperate forest ecotone is often ignored. We quantified the intensity and probability of growing-season frosts at the boreal-temperate forest ecotone in regard to topographic and microtopographic landscape attributes, which were extracted from airborne LiDAR surveys. In situ air temperature was measured for two summers (2016–2017) with 252 temperature loggers installed in two 18-years-old spruce plantations established in both temperate and boreal mixedwood forests. Growing-season frosts were more intense and probable at the boreal mixedwood forest site compared to the temperate forest site. Still, at both sites, when growing-season frost occurred, air temperature could vary by 4 °C along the elevation gradient of 15 m, often reaching sub-zero values at low elevation while reaching above-freezing values at high elevation. The importance of microtopography on the risk of sub-zero temperatures increased where frost events were less likely to occur such as at the temperate forest and at high elevation. Considering that growing-season frosts can considerably reduce tree productivity, the effects of both topography and planting microsite should be considered when determining where to establish plantations in the landscape and to determine suitable frost-free planting microsites within a plantation.