DOI: 10.5061/dryad.vdncjsxrr
title: Best-practice forestry management delivers diminishing returns for coral reefs with increased land-clearing

description: Protection of coastal ecosystems from deforestation may be the best way to
 protect coral reefs from sediment runoff. However, given the importance of
 generating economic activities for coastal livelihoods, the prohibition of
 development is often not feasible. In light of this, logging
 codes-of-practice have been developed to mitigate the impacts of logging
 on downstream ecosystems. However, no studies have assessed whether
 managed land-clearing can occur in tandem with coral reef conservation
 goals. This study quantifies the impacts of current land use and the risk
 of potential logging activities on downstream coral reef condition and
 fisheries using a novel suite of linked land-sea models, using
 Kolombangara Island in the Solomon Islands as a case study. Further, we
 examine the ability of erosion reduction strategies stipulated in logging
 codes-of-practice to reduce these impacts as clearing extent increases. We
 found that with present-day land use, reductions in live and branching
 coral cover and increases in turf algae were associated with exposure to
 sediment runoff from catchments and log ponds. Critically, reductions in
 fish grazer abundance and biomass were associated with increasing sediment
 runoff, a functional group that accounts for ~25% of subsistence fishing.
 At low clearing extents, although best management practices minimises the
 exposure of coral reefs to increased runoff, it would still result in 32%
 of the reef experiencing an increase in sediment exposure. If clearing
 extent increased, best management practices would have no impact, with a
 staggering 89% of coral reef area at risk compared to logging with no
 management. Synthesis and applications: Assessing trade-offs between
 coastal development and protection of marine resources is a challenge for
 decision makers globally. Although development activities requiring
 clearing can be important for livelihoods, our results demonstrate that
 new logging in intact forest risks downstream resources important for both
 food and livelihood security. Importantly, our approach allows for
 spatially-explicit recommendations for where terrestrial management might
 best complement marine management. Finally, given the critical degradation
 feedback loops that increased sediment runoff can reinforce on coral
 reefs, minimising sediment runoff could play an important role in helping
 coral reefs recover from climate-related disturbances.
description: <strong>Bathymetry
 </strong> Bathymetry is a key driver of
 coral reef communities and sediment dispersal (Rude et al., 2015, Knudby
 et al., 2010), yet the freely-available bathymetry data [The General
 Bathymetric Chart of the Oceans (GEBCO)] was not suitable for our
 nearshore study region given how coarse-scale it is. We therefore
 developed a tool on Google Earth Engine (GEE) to calculate bathymetry from
 Sentinel-2 satellite imagery. While the GEBCO data spatial resolution is
 30 arc-seconds (roughly 930 x 930 m grid cells at our study site) the
 spatial resolution of the GEE generated bathymetry layer is 10 x 10 m grid
 cells. Since the region is frequently cloud covered, a composite approach
 had to be used into order to create a spatially complete output. All
 Sentinel-2 image from the study region with less than 50% scene cloud
 cover were included. For each image, top of atmosphere reflectance values
 were re-scaled from 0 to 1 then clouds and land were masked using the
 image QA bands and a simple normalized difference vegetation index (NDVI)
 threshold respectively. Areas of sunglint were identified as water pixels
 where red values were greater than 0.06 and red values were greater than
 0.15. Deglinting was carried out using a modified version of Hedley et al.
 (2005). We used a linear regression to find the slope between the NIR band
 and the blue, green, and red bands. The blue, green, red, and NIR bands
 were then deglinted on a pixel by pixel basis by subtracting the product
 of the band slope and the difference of the NIR value and NIR value of an
 open ocean pixel. The in-situ depth points (see Table S1) were used to
 extract the glint-corrected blue, green, red, and NIR pixels values for
 their locations. Depth for each image was then calculated using the
 Lyzenga method (Lyzenga et al., 2006). We ran a multiple linear regression
 between the in-situ depth and the glint corrected values of the four bands
 and calculated the first percentile values for the four glint-corrected
 bands and a composite bathymetry layer was created by taking the mean
 depth calculated for all available images. The accuracy was checked with a
 linear regression with r<sup>2</sup> = 0.59 and Root Mean
 Square Error = 1.8, with the Google Earth Engine tool overestimating
 depth. <strong>Wave exposure and
 sediment entrainment</strong> Wave exposure was determined by
 using the model Simulating WAves Nearshore (SWAN) 41.20 (Booij et al.,
 1999). This model was developed specifically for propagating deepwater
 waves to nearshore environments and has been used extensively in a variety
 of coastal settings, including coral reefs (e.g. Baldock et al. (2014)).
 The wave boundary conditions for the model were determined from the
 average long-term deep water wave height from 1979-2014 from the National
 Oceanic and Atmospheric Administration (NOAA) Wave Watch 3. The bathymetry
 for the SWAN model was a merged global bathymetry layer (GEBCO)
 reprojected to 100 x 100 m grid cells for deep water environments and the
 10 x 10 m shallow water bathymetry derived from GEE used for the reef
 zones. Significant wave height
 (<i>H<sub>s</sub></i>) and wave period
 (<i>T</i>) were extracted from the SWAN model for the reef
 slopes of Kolombangara. Significant wave height from SWAN
 was used to produce a Rayleigh distributed histogram of wave heights that
 represent the likely wave climate at the river discharge sites (Svendsen,
 2006). The bin range of the histogram was every 0.01 m and between 0 to
 twice the maximum <i>H<sub>s </sub></i>modelled
 for the reef slope (i.e. an approximation of the largest individual waves,
 (Komar, 1998). This histogram represents the synthetic wave climate for
 the nearshore zones of Kolombangara reef. The near-bed wave orbital
 velocities from the synthetic wave climate was determined at 10 metres
 depth using linear wave theory (Komar, 1998). <strong>Sediment
 model</strong> Sediment transport routines were
 developed to determine the likely location of settlement of suspended
 sediment from the sediment load discharge. Annual sediment load discharges
 into the reef environment were derived from running InVEST SDR models for
 each river outlet on Kolombangara (Wenger et al. 2018). The transport,
 deposition, and resuspension of suspended sediment depends on several
 complex physical and bio-geochemical processes (Bainbridge et al., 2018,
 Soulsby, 1997). Given the data limitations, we were not able to account
 for all of these processes, including the role of freshwater in dispersing
 sediment particles, complex transport of sediment of different sizes, or
 flocculation of suspended particulate matter. However, we were able to
 account for the likely distribution of suspended sediment, shallow water
 bathymetry, ocean current speed and direction, and nearshore wave climate.
 This approach produced sediment transport maps that err on the side of
 longer transport distances of very fine sediment particles known to
 adversely impact coral reef organisms (Bainbridge et al., 2018). The
 percentage of sediment entrained on the coral reef slope was determined
 from the proportion of near-bed wave orbital velocities in the synthetic
 wave climate that were above the critical orbital velocity required to
 entrain mud (grain size 63 µm), as defined by methods in Soulsby (1997).
 That is, if 40% of the wave orbital velocities were above the critical
 entrainment velocity, 40% of the sediment load was transported from the
 location of river outflow. The transport direction of entrained sediment
 in suspension was determined from the average current speed and direction
 between 1993 – 2015 derived from the E.U. Copernicus Marine Service
 Information (GLORYS12V1 product). The current speed and fall velocity of
 fine muds was used to determine the transport distance of entrained
 sediment by multiplying current speed by the time taken for sediment to
 fall to 10 m depth (e.g. Rude et al. 2015, Soulsby 1997). If sediment
 moved to a location where sediment entrainment was still likely it was
 further transported until it settled in a lower energy zone. This process
 was applied for each logging scenario and the respective sediment load
 discharge into the reef environment. Since nearshore coral reefs have
 evolved in variable water quality conditions and may be adapted to turbid
 environments (Anthony and Fabricius, 2000), the difference in sediment
 load between no-logging (i.e. prior to human impact) and logging scenarios
 were also examined to understand the change in sediment load a reef can
 tolerate before an ecosystems shift occurs. No-logging sediment run-off
 was determined by artificially re-foresting the islands and examining what
 the natural runoff regimes were.
description: File name descriptions: 
 bathymetry.tif-the final bathymetry layer produced by the
 desribed methods sediment_pres.tif- A map of patterns
 of sediment runoff from present day landuse
 s1_10.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 10% area cleared
 s1_20.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 20% area cleared
 s1_30.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 30% area cleared
 s1_40.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 40% area cleared
 s6_10.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 10% area cleared
 s6_20.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 20% area cleared
 s6_30.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 30% area cleared
 s6_40.tif-A map of patterns of sediment runoff from logging
 activities with no management in place and 40% area cleared
 waves.tif-the final waves layer produced by the desribed
 methods