fixed outstanding citation issues

_book/append-birds.html

@@ -347,11 +347,11 @@
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@@ -516,7 +516,7 @@ <h3 data-number="F.4.2" class="anchored" data-anchor-id="radar-and-lidar"><span
 <section id="acoustics" class="level3" data-number="F.4.3">
 <h3 data-number="F.4.3" class="anchored" data-anchor-id="acoustics"><span class="header-section-number">F.4.3</span> Acoustics</h3>
 <p><strong>Acoustic surveys</strong> using acoustic detectors (a combination of microphones and recording devices) to record calls of birds are becoming increasingly common <span class="citation" data-cites="pérez-granados2021">(<a href="references.html#ref-pérez-granados2021" role="doc-biblioref">Pérez-Granados and Traba, 2021</a>)</span>, although they remain more frequently used for bats. This method of monitoring can provide information about migration phenology, species composition, acoustic soundscapes for communication, and, in some cases, numbers of passing individuals. Acoustic surveys for birds in the offshore environment are most commonly used for night migrants <span class="citation" data-cites="hill2008">(<a href="references.html#ref-hill2008" role="doc-biblioref">Hill and Hüppop, 2008</a>)</span>, and typically use passive, stationary detectors configured to sample primarily in the audible frequency range (e.g.&nbsp;1-12 kHz). Passive surveys offshore utilize stationary detectors deployed on ocean buoys, meteorological towers, offshore wind turbines, other offshore infrastructure (such as electrical service platforms [ESPs], also commonly referred to as offshore substations [OSSs]).</p>
-<p>Acoustic surveys are only effective when study animals are vocalizing. Ambient noise can interfere with detection of vocalizing animals and limit the distance over which calls will be recorded, an important factor to consider in deploying acoustic detectors on operating turbines.&nbsp; Challenges also remain in differentiating among flight calls of different species <span class="citation" data-cites="bioacous2020 priyadarshani2018">(<a href="references.html#ref-bioacous2020" role="doc-biblioref"><span>“Bioacoustics data analysis <span></span> a taxonomy, survey and open challenges,”</span> 2020</a>; <a href="references.html#ref-priyadarshani2018" role="doc-biblioref">Priyadarshani et al., 2018</a>)</span>. However, software for the detection, classification, and analysis of field-collected audio files continues to be improved <span class="citation" data-cites="vandoren">(<a href="references.html#ref-vandoren" role="doc-biblioref">Van Doren et al., n.d.a</a>)</span>. Some new software can address suboptimal signal-noise ratios and evaluate areas of masking interference to speed and to refine analyses <span class="citation" data-cites="vandoren2023">(<a href="references.html#ref-vandoren2023" role="doc-biblioref">Van Doren et al., 2023</a>)</span>. The extent to which acoustic survey technologies can be counted upon to operate continuously in harsh offshore conditions also requires further evaluation.</p>
+<p>Acoustic surveys are only effective when study animals are vocalizing. Ambient noise can interfere with detection of vocalizing animals and limit the distance over which calls will be recorded, an important factor to consider in deploying acoustic detectors on operating turbines.&nbsp; Challenges also remain in differentiating among flight calls of different species <span class="citation" data-cites="bioacous2020 priyadarshani2018">(<a href="references.html#ref-bioacous2020" role="doc-biblioref"><span>“Bioacoustics data analysis <span></span> a taxonomy, survey and open challenges,”</span> 2020</a>; <a href="references.html#ref-priyadarshani2018" role="doc-biblioref">Priyadarshani et al., 2018</a>)</span>. However, software for the detection, classification, and analysis of field-collected audio files continues to be improved <span class="citation" data-cites="vandoren">(<a href="references.html#ref-vandoren" role="doc-biblioref">Van Doren et al., 2023a</a>)</span>. Some new software can address suboptimal signal-noise ratios and evaluate areas of masking interference to speed and to refine analyses <span class="citation" data-cites="vandoren2023">(<a href="references.html#ref-vandoren2023" role="doc-biblioref">Van Doren et al., 2023b</a>)</span>. The extent to which acoustic survey technologies can be counted upon to operate continuously in harsh offshore conditions also requires further evaluation.</p>
 </section>
 <section id="banding-tagging-and-tracking" class="level3" data-number="F.4.4">
 <h3 data-number="F.4.4" class="anchored" data-anchor-id="banding-tagging-and-tracking"><span class="header-section-number">F.4.4</span> Banding, Tagging, and Tracking</h3>
@@ -963,7 +963,7 @@ <h5 data-number="F.6.3.2.3" class="anchored" data-anchor-id="bird-turbine-intera
 <h5 data-number="F.6.3.2.4" class="anchored" data-anchor-id="artificial-intelligence-for-species-identification"><span class="header-section-number">F.6.3.2.4</span> Artificial Intelligence for Species Identification</h5>
 <p>Use of artificial intelligence to identify visual or acoustic detections of birds can significantly speed up processing time, reduce costs, and potentially increase accuracy for field-collected data. It can also allow for real-time identification of birds captured in video or acoustic recordings.</p>
 <p>USFWS and USGS are working on development of <a href="https://eros.usgs.gov/doi-remote-sensing-activities/2021/usgs/automated-detection-wildlife-targets-aerial-imagery">AI software</a> for use in identifying species detected in aerial surveys, including seabirds and waterfowl. Initial machine learning algorithm development has achieved the extraction of targets (individual birds and other wildlife) from imagery; current algorithm development is focused on classifying detected targets to the species level. This project has involved the development of an online feature annotation tool (based on the open-source annotation tool Computer Vision Annotation Tool - CVAT) for easy, streamlined labeling of training data by biologists and to serve as an imagery and annotation database for online data archiving and sharing.</p>
-<p>Auto-classification software for the identification of bird calls in acoustic data are also being developed and improved <span class="citation" data-cites="kahl2021 vandorena">(<a href="references.html#ref-kahl2021" role="doc-biblioref">Kahl et al., 2021</a>; <a href="references.html#ref-vandorena" role="doc-biblioref">Van Doren et al., n.d.b</a>)</span>.</p>
+<p>Auto-classification software for the identification of bird calls in acoustic data are also being developed and improved <span class="citation" data-cites="kahl2021 vandoren">(<a href="references.html#ref-kahl2021" role="doc-biblioref">Kahl et al., 2021</a>; <a href="references.html#ref-vandoren" role="doc-biblioref">Van Doren et al., 2023a</a>)</span>.</p>
 <p>For tracking of new technologies, see the Tethys <a href="https://tethys.pnnl.gov/wind-energy-monitoring-mitigation-technologies-tool">database of monitoring technologies</a>.</p>
 </section>
 </section>
@@ -1185,13 +1185,10 @@ <h4 data-number="F.6.4.2" class="anchored" data-anchor-id="current-and-recent-ef
 USFWS, 2003. <a href="https://www.fws.gov/sites/default/files/documents/endangered-species-act-accessible.pdf">Endangered species act</a>.
 </div>
 <div id="ref-vandoren" class="csl-entry" role="listitem">
-Van Doren, B., Farnsworth, A., Stone, K., Osterhaus, D., Drucker, J., Van Horn, G., n.d.a. Nighthawk: Acoustic monitoring of nocturnal bird migration in the americas. https://doi.org/<a href="https://doi.org/10.1101/2023.05.22.541336">https://doi.org/10.1101/2023.05.22.541336</a>
-</div>
-<div id="ref-vandorena" class="csl-entry" role="listitem">
-Van Doren, B., Farnsworth, A., Stone, K., Osterhaus, D., Drucker, J., Van Horn, G., n.d.b. Nighthawk: Acoustic monitoring of nocturnal bird migration in the americas. https://doi.org/<a href="https://doi.org/10.1101/2023.05.22.541336">https://doi.org/10.1101/2023.05.22.541336</a>
+Van Doren, B., Farnsworth, A., Stone, K., Osterhaus, D., Drucker, J., Van Horn, G., 2023a. Nighthawk: Acoustic monitoring of nocturnal bird migration in the americas. <a href="https://doi.org/10.1101/2023.05.22.541336">https://doi.org/10.1101/2023.05.22.541336</a>
 </div>
 <div id="ref-vandoren2023" class="csl-entry" role="listitem">
-Van Doren, B., Lostanlen, V., Cramer, A., Salamon, J., Dokter, A., Kelling, S., Bello, J.P., Farnsworth, A., 2023. Automated acoustic monitoring captures timing and intensity of bird migration. Applied Ecology 60. https://doi.org/<a href="https://doi.org/10.1111/1365-2664.14342">https://doi.org/10.1111/1365-2664.14342</a>
+Van Doren, B., Lostanlen, V., Cramer, A., Salamon, J., Dokter, A., Kelling, S., Bello, J.P., Farnsworth, A., 2023b. Automated acoustic monitoring captures timing and intensity of bird migration. Applied Ecology 60. <a href="https://doi.org/10.1111/1365-2664.14342">https://doi.org/10.1111/1365-2664.14342</a>
 </div>
 <div id="ref-willmott2023" class="csl-entry" role="listitem">
 Willmott, J.R., Forcey, G., Vukovich, M., 2023. New insights into the influence of turbines on the behaviour of migrant birds: implications for predicting impacts of offshore wind developments on wildlife. Journal of Physics: Conference Series 2507, 012006. <a href="https://doi.org/10.1088/1742-6596/2507/1/012006">https://doi.org/10.1088/1742-6596/2507/1/012006</a>