Three-dimensional digital mapping of ecosystems: a new era in spatial ecology

Jackson, Timmie Okchumpulla; Williams, Gareth J.; Walker-Springett, Guy; Davies, Andrew J.

doi:10.1098/rspb.2019.2383

Cited by 59 publications

(39 citation statements)

References 78 publications

(112 reference statements)

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“…These technologies greatly expanded scales of observation and enabled practical implications of landscape ecology to be used in ecosystem management (Lee et al 2008, De Knegt et al 2011, Jones et al 2013). Progression of theory within the marine environment has been slower due to logistical constraints of collecting comparable data across scales (Kenny et al 2003, Hinchey et al 2008, D'Urban Jackson et al 2020), but has nonetheless emerged to form the discipline of ‘seascape ecology' (Pittman et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Spatial scaling properties of coral reef benthic communities

et al. 2020

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The spatial structure of ecological communities on tropical coral reefs across seascapes and geographies have historically been poorly understood. Here we addressed this for the first time using spatially expansive and thematically resolved benthic community data collected around five uninhabited central Pacific oceanic islands, spanning 6° latitude and 17° longitude. Using towed‐diver digital image surveys over ~140 linear km of shallow (8–20 m depth) tropical reef, we highlight the autocorrelated nature of coral reef seascapes. Benthic functional groups and hard coral morphologies displayed significant spatial clustering (positive autocorrelation) up to kilometre‐scales around all islands, in some instances dominating entire sections of coastline. The scale and strength of these autocorrelation patterns showed differences across geographies, but patterns were more similar between islands in closer proximity and of a similar size. For example, crustose coralline algae (CCA) were clustered up to scales of 0.3 km at neighbouring Howland and Baker Islands and macroalgae were spatially clustered at scales up to ~3 km at both neighbouring Kingman Reef and Palmyra Atoll. Of all the functional groups, macroalgae had the highest levels of spatial clustering across geographies at the finest resolution of our data (100 m). There were several cases where the upper scale at which benthic community members showed evidence of spatial clustering correlated highly with the upper scales at which concurrent gradients in physical environmental drivers were spatially clustered. These correlations were stronger for surface wave energy than subsurface temperature (regardless of benthic group) and turf algae and CCA had the closest alignments in scale with wave energy across functional groups and geographies. Our findings suggest such physical drivers not only limit or promote the abundance of various benthic competitors on coral reefs, but also play a key role in governing their spatial scaling properties across seascapes.

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Section: Introductionmentioning

confidence: 99%

Spatial scaling properties of coral reef benthic communities

et al. 2020

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“…Therefore, to investigate spatial and temporal patterns in S. alveolata reef structure at a habitat scale (~35 000 m 2 ), we used structure-from-motion photogrammetry derived from drone aerial imagery, in April 2018 and April 2019. Drone-derived structure-frommotion photogrammetry generates continuous 3D information across large extents, with comparable accuracy to terrestrial laser scanning in complex habitats like S. alveolata reef (D'Urban Jackson et al, 2020). We used a Phantom 4 Pro (DJI) with a 20 MP camera flying at 46 m altitude to capture images with 14-mm XY ground resolution, covering c. 150 000 m 2 of the coastline.…”

Section: Plot-scale (2500 M 2 ) 3d Mappingmentioning

confidence: 99%

Three‐dimensional mapping reveals scale‐dependent dynamics in biogenic reef habitat structure

Jackson-Bué

Williams

Walker-Springett

et al. 2021

Remote Sens Ecol Conserv

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Habitat structure influences a broad range of ecological interactions and ecosystem functions across biomes. To understand and effectively manage dynamic ecosystems, we need detailed information about habitat properties and how they vary across spatial and temporal scales. Measuring and monitoring variation in three-dimensional (3D) habitat structure has traditionally been challenging, despite recognition of its importance to ecological processes. Modern 3D mapping technologies present opportunities to characterize spatial and temporal variation in habitat structure at a range of ecologically relevant scales. Biogenic reefs are structurally complex and dynamic habitats, in which structure has a pivotal influence on ecosystem biodiversity, function and resilience. For the first time, we characterized spatial and temporal dynamics in the 3D structure of intertidal Sabellaria alveolata biogenic reef across scales. We used drone-derived structure-from-motion photogrammetry and terrestrial laser scanning to characterize reef structural variation at mm-to-cm resolutions at a habitat scale (~35 000 m 2 ) over 1 year, and at a plot scale (2500 m 2 ) over 5 years (2014-2019, 6-month intervals). We found that most of the variation in reef emergence above the substrate, accretion rate and erosion rate was explained by a combination of systematic trends with shore height and positive spatial autocorrelation up to the scale of colonies (1.5 m) or small patches (up to 4 m). We identified previously undocumented temporal patterns in intertidal S. alveolata reef accretion and erosion, specifically groups of rapidly accreting, shortlived colonies and slow-accreting, long-lived colonies. We showed that these highly dynamic colony-scale structural changes compensate for each other, resulting in seemingly stable reef habitat structure over larger spatial and temporal scales. These patterns could only be detected with the use of modern 3D mapping technologies, demonstrating their potential to enhance our understanding of ecosystem dynamics across scales.

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“…Official ISO data collection standards are however still being developed for this technique (Kresse, 2010); therefore, the level of consistency/comparability across outputs from varying cameras, operators and conditions is still to be fully explored. Finally, the size of current individual surveys is generally restricted to hundreds of square metres, primarily due to computer processing power limitations and time constraints (Bayley, Mogg, Koldewey, et al, 2019; D'Urban Jackson, Williams, Walker‐Springett, & Davies, 2020).…”

Section: Limitationsmentioning

confidence: 99%