Pawlak Camille

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  • Article
    Automated satellite remote sensing of giant kelp at the Falkland Islands (Islas Malvinas)
    (Public Library of Science, 2022-01-06) Houskeeper, Henry F. ; Rosenthal, Isaac S. ; Cavanaugh, Katherine C. ; Pawlak, Camille ; Trouille, Laura ; Byrnes, Jarrett E. K. ; Bell, Tom W. ; Cavanaugh, Kyle C.
    Giant kelp populations that support productive and diverse coastal ecosystems at temperate and subpolar latitudes of both hemispheres are vulnerable to changing climate conditions as well as direct human impacts. Observations of giant kelp forests are spatially and temporally uneven, with disproportionate coverage in the northern hemisphere, despite the size and comparable density of southern hemisphere kelp forests. Satellite imagery enables the mapping of existing and historical giant kelp populations in understudied regions, but automating the detection of giant kelp using satellite imagery requires approaches that are robust to the optical complexity of the shallow, nearshore environment. We present and compare two approaches for automating the detection of giant kelp in satellite datasets: one based on crowd sourcing of satellite imagery classifications and another based on a decision tree paired with a spectral unmixing algorithm (automated using Google Earth Engine). Both approaches are applied to satellite imagery (Landsat) of the Falkland Islands or Islas Malvinas (FLK), an archipelago in the southern Atlantic Ocean that supports expansive giant kelp ecosystems. The performance of each method is evaluated by comparing the automated classifications with a subset of expert-annotated imagery (8 images spanning the majority of our continuous timeseries, cumulatively covering over 2,700 km of coastline, and including all relevant sensors). Using the remote sensing approaches evaluated herein, we present the first continuous timeseries of giant kelp observations in the FLK region using Landsat imagery spanning over three decades. We do not detect evidence of long-term change in the FLK region, although we observe a recent decline in total canopy area from 2017–2021. Using a nitrate model based on nearby ocean state measurements obtained from ships and incorporating satellite sea surface temperature products, we find that the area of giant kelp forests in the FLK region is positively correlated with the nitrate content observed during the prior year. Our results indicate that giant kelp classifications using citizen science are approximately consistent with classifications based on a state-of-the-art automated spectral approach. Despite differences in accuracy and sensitivity, both approaches find high interannual variability that impedes the detection of potential long-term changes in giant kelp canopy area, although recent canopy area declines are notable and should continue to be monitored carefully.
  • Article
    Using unoccupied aerial vehicles to map and monitor changes in emergent kelp canopy after an ecological regime shift
    (Wiley Open Access, 2022-09-21) Saccomanno, Vienna R. ; Bell, Tom W. ; Pawlak, Camille ; Stanley, Charlotte K. ; Cavanaugh, Katherine C. ; Hohman, Rietta ; Klausmeyer, Kirk R. ; Cavanaugh, Kyle ; Nickels, Abby ; Hewerdine, Waz ; Garza, Corey ; Fleener, Gary ; Gleason, Mary
    Kelp forests are complex underwater habitats that form the foundation of many nearshore marine environments and provide valuable services for coastal communities. Despite their ecological and economic importance, increasingly severe stressors have resulted in declines in kelp abundance in many regions over the past few decades, including the North Coast of California, USA. Given the significant and sustained loss of kelp in this region, management intervention is likely a necessary tool to reset the ecosystem and geospatial data on kelp dynamics are needed to strategically implement restoration projects. Because canopy‐forming kelp forests are distinguishable in aerial imagery, remote sensing is an important tool for documenting changes in canopy area and abundance to meet these data needs. We used small unoccupied aerial vehicles (UAVs) to survey emergent kelp canopy in priority sites along the North Coast in 2019 and 2020 to fill a key data gap for kelp restoration practitioners working at local scales. With over 4,300 hectares surveyed between 2019 and 2020, these surveys represent the two largest marine resource‐focused UAV surveys conducted in California to our knowledge. We present remote sensing methods using UAVs and a repeatable workflow for conducting consistent surveys, creating orthomosaics, georeferencing data, classifying emergent kelp and creating kelp canopy maps that can be used to assess trends in kelp canopy dynamics over space and time. We illustrate the impacts of spatial resolution on emergent kelp canopy classification between different sensors to help practitioners decide which data stream to select when asking restoration and management questions at varying spatial scales. Our results suggest that high spatial resolution data of emergent kelp canopy from UAVs have the potential to advance strategic kelp restoration and adaptive management.Despite their ecological and economic importance, kelp forest abundance has declined in many regions around the world including the North Coast of California. Given the significant loss of kelp in this region, management intervention is likely necessary and remotely sensed data on kelp dynamics can help inform strategic restoration projects. We used unoccupied aerial vehicles (UAVs) to survey emergent kelp canopy along the North Coast in 2019 and 2020 and present remote‐sensing based kelp survey methods using UAVs. Our results suggest that high spatial resolution data on local‐scale spatiotemporal patterns of emergent kelp canopy from UAVs have the potential to advance strategic kelp restoration and adaptive management.
  • Article
    CubeSats show persistence of bull kelp refugia amidst a regional collapse in California
    (Elsevier, 2023-03-11) Cavanaugh, Katherine C. ; Cavanaugh, Kyle C. ; Pawlak, Camille C. ; Bell, Tom W. ; Saccomanno, Vienna R.
    Bull kelp populations in northern California declined drastically in response to the 2014–2016 marine heatwave, sea star wasting disease, and subsequently large increases in herbivorous purple urchin populations. Despite the regional kelp forest collapse, there were small, remnant populations where bull kelp was able to survive. Moderate resolution satellites (i.e., Landsat) have been important for creating long-term, large-scale time series of bull kelp forests, however, these have been shown to underestimate or entirely exclude refugia due to their low densities and proximity to the coastline. While measurements from Unoccupied Aerial Vehicles (UAV) are spatially detailed, they are temporally limited and difficult to collect over regional scales. The development of CubeSat constellations has enabled a workaround for these tradeoffs, with global imagery available near-daily at meter-scale.We developed a method for mapping bull kelp canopy across the different sensor cohorts in the PlanetScope constellation. This required correcting surface reflectance measurements to account for differences in the spectral response functions among the sensors and leveraging the temporal frequency of PlanetScope data to increase the automation of classifying kelp canopy in imagery with increased noise. Using the PlanetScope derived kelp canopy extents, we identified locations where bull kelp refugia have persisted in northern California. We found that bull kelp refugia occupied about 2% of the total available habitat in the region and about 9.4% of the average canopy area observed prior to 2014. These areas may be critical to the success of kelp forest re-establishment in northern California, which increases their importance for ongoing monitoring, conservation, and restoration efforts.•Developed the first bull kelp canopy time series from high resolution CubeSat data.•CubeSats can effectively detect kelp canopy at low population abundance and density.•Refugia persisted during historically low kelp abundance in northern California.