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Best-practice forestry management delivers diminishing returns for coral reefs with increased land-clearing

Citation

Wenger, Amelia et al. (2020), Best-practice forestry management delivers diminishing returns for coral reefs with increased land-clearing, Dryad, Dataset, https://doi.org/10.5061/dryad.vdncjsxrr

Abstract

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.

Methods

Bathymetry

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 r2 = 0.59 and Root Mean Square Error = 1.8, with the Google Earth Engine tool overestimating depth.

Wave exposure and sediment entrainment

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 (Hs) and wave period (T) 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 Hs 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).

Sediment model

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.

Usage Notes

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

Funding

Australian Research Council, Award: LP150100934

National Science Foundation, Award: EF-1427453