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7 results for “dune habitat”
Assessment of current and future invasive plants in protected dune habitats of the Atlantic coastal region for the LIFE DUNIAS project (LIFE20 NAT/BE/001442)
<p>This .csv file contains the raw data from the risk screening supplementing the LIFE DUNIAS horizon scan for (invasive) alien species in protected habitats of Atlantic coastal dune ecosystems (<a href="https://doi.org/10.21436/inbor.86703335">Adriaens et al. 2022</a>). We gladly refer to the annexes and methods section in this report for more explanation about the fields and their contained values.</p> <p>The file contains the following fields:</p> <p><em>TaxonName</em>: original taxonomic name of the considered alien species</p> <p><em>WorkName</em>: taxonomic name of the considered alien species after lumping of subspecies, closely related species of a complex, functionally similar species of the same genus (see chapter 3.1)</p> <p><em>hab_xxxx</em> (1110, 1130, 1140, 1210, 1230, 1310, 1320, 1330, 2110, 2120, 2130, 2140, 21A0, 2150, 2190, 2160, 2170, 2180): susceptibility of habitat for the alien species (4-digit code refering to the Annex I habitat under the Habitats Directive) </p> <p><em>occ_XX</em> (BE, FR, IE, NL, ES, UK, DK, DE, PT, ALL): occupancy of the alien species in different countries of the Atlantic European region (as the number of 10km<sup>2</sup> squares per country). Country codes: BE = Belgium, FR = France, IE = Ireland, NL = Netherlands, ES = Spain, UK = United Kingdom, DK = Denmark, DE = Germany, PT = Portugal, ALL = total for all countries.</p> <p><em>scor_XXX_xxxx</em>: score of the assessment per criterium (INT = introduction, EST = establishment, SPR = spread, IMP = ecological impact, ALL = overall score) and per habitat group (salt = salties, sand = sandies, shru = shrubbies) conf_<em>XXX_xxxx</em>: confidence on the scores of the assessment per criterium (INT = introduction, EST = establishment, SPR = spread, IMP = ecological impact, ALL = overall score) and per habitat group (salt = salties, sand = sandies, shru = shrubbies)</p> <p><em>scor_ALL_MAX</em>: maximum ecological impact score of the alien taxon across all habitats</p>
Patterns of island fox habitat use in sand dune habitat on San Clemente Island
<p>On San Clemente Island (SCI), the island fox subspecies (<em>Urocyon littoralis</em><em> clementae</em>) has been monitored annually since 1988 to track long-term population trends. Annual density estimates in most habitat types across the island range from 2–13 foxes/km<sup>2</sup>, yet unusually high estimates have repeatedly approached 50 foxes/km<sup>2 </sup>in a unique sand dune habitat area. Although sand dune habitat is restricted to one small area on the island, these estimates suggest sand dune habitat supports one of the highest population densities of any fox species in the world, and it may support > 5% of the SCI fox population. This finding prompted our investigation to determine if SCI foxes captured in the sand dunes habitat area maintained home ranges within this habitat type. Between January–July 2018, we used Global Positioning System collars to track the movements of 12 island foxes captured in the sand dune habitat area. Contrary to our initial predictions, we found that island foxes captured in the sand dune habitat area do maintain home ranges and core areas centralized in sand dune habitat. All 12 island fox home ranges estimated contained >50% sand dune habitat in either their 50% or 95% fixed kernel density estimate (KDE) home range, and island foxes were 3.14 times more likely to use active sand dune habitat when compared to the second most abundant habitat type, maritime desert scrub (Adjusted = 3.14, 95% CI = 3.07–3.12). We also found that island foxes in sand dune habitat maintained much smaller home ranges than reported estimates in other habitat types, with an average 95% KDE home range size of 0.42 km<sup>2</sup> (95% CI = 0.20–0.63 km<sup>2</sup>). Although sand dune habitat comprises just 2% of available habitat on SCI, our research highlights the importance of this unique habitat area for island foxes.</p>
Robotic Monitoring of Dunes: a dataset from the EU habitats 2110 and 2120 in Sardinia (Italy)
<p>Data collected between the 16th and the 19th of May 2022, in Platamona, 07037 (SS), Sardinia, Italy, within the Natura 2000 SAC ITB010003. The data acquisition has been conducted by a team composed of both robotic engineers and plant scientists. The platform used to collect the data is the ANYmal C quadrupedal robot. </p> <p>The dataset contains three different sets of data: <br> 1) species data - pictures and videos of three different typical species of the habitat 2110 and 2120 and one alien species.<br> 2) 3D mapping data - robot status and point cloud<br> 3) monitoring mission data - robot status and pictures and videos taken by the robot during the autonomous surveys.</p> <p>This dataset has a multidisciplinary scope and can be used by researchers in several fields. For instance, point clouds and information about the robot state could be used by robotic engineers to test or validate their own methods as well as benchmark the robot performance. On the other hand, plant videos and images recorded by the robot could be used by botanists to assess the quality of this information as well as the habitat's conditions, or by computer scientists interested in testing their AI algorithms for species detection and classification.</p>
Patterns of island fox habitat use in sand dune habitat on San Clemente Island
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Habitat mapping of coastal dunes with deep learning - Scripts & Data
<p><strong>Authors</strong>: Eva M. Lansu, Valérie C. Reijers, Freek Daniëls, Rebecca James, Marjolijn J. A. Christianen, Tjisse van der Heide</p> <p> </p> <p><strong>Abstract</strong></p> <p><span lang="EN-GB">About one-third of the world's shoreline is defined by sandy coasts with developed dune ecosystems</span><span lang="EN-GB">. </span><span lang="EN-GB">These ecosystems </span><span lang="EN-GB">drastically degraded them due to anthropogenic pressures. </span><span lang="EN-GB">To develop strategic management that counteracts this degradation, it is essential to closely monitor ongoing habitat changes.</span><span lang="EN-GB"> Traditionally, coastal dune monitoring is based on field observations, which are labour intensive and costly. While automated analyses of aerial imagery could reduce monitoring efforts and enhance spatial coverage, t</span><span lang="EN-GB">o date, its application </span><span><span lang="EN-GB">has </span></span><span><span lang="EN-GB">remained limited to a single small-scale trial (<2 km</span></span><span><sup><span lang="EN-GB">2</span></sup></span><span><span lang="EN-GB">). </span></span><span><span lang="EN-GB">Here, we trained a Convolutional Neural Network to map the Dutch coastal dunes </span></span><span><span lang="EN-GB">(562 km<sup>2</sup>) </span></span><span><span lang="EN-GB">at 25 cm resolution using six habitat classes: bare sand, shrubs, fresh water, grass, broadleaf trees, and needleleaf trees. </span></span><span lang="EN-GB">Training the network on only RGB imagery resulted in predictions with 92% accuracy, 80% average recall and 70% precision. Model performance increased when the network was trained on all available data - RGB imagery, near-infrared, distance to sea, digital surface model, and canopy height - resulting in 95% accuracy, 88% averaged recall and 80% precision. Finally, we compared the predictions with 499 in-field observations across the Dutch coastal dunes and found 88% accuracy, 74% averaged recall and 62% precision. We used this model to create a map of the entire Dutch coastal dunes, which enables </span><span lang="EN-GB">rapid and precise </span><span lang="EN-GB">assessments of habitat diversity and extent</span><span lang="EN-GB">. As habitat and species diversity are intrinsically linked, our results showcase how automated image analysis can enable biodiversity monitoring on a national scale. </span></p> <p>==============================================</p> <p><strong>Methods</strong></p> <p>The analyses rely on the following datasets:</p> <ul> <li>Orthophoto mosaics including a near-infrared band (from <u><a href="http://geotiles.nl/">http://geotiles.nl/</a></u>)</li> <li>Digital surface model and a digital terrain model (from <a href="https://www.ahn.nl/">https://www.ahn.nl/</a>)</li> <li>A land-use map (from <u><a href="https://lgn.nl/basiskaart">https://lgn.nl/basiskaart)</a></u></li> </ul>
Relaxed predation selection on rare morphs of Ensatina salamanders (Caudata: Plethodontidae) promotes a polymorphic population in a novel dune sand habitat
<p>The Ensatina ring species represents a classic example of locally adapted lineages. The Monterey Ensatina (Ensatina eschscholtzii eschscholtzii) is a cryptic subspecies with brown coloration, however, a recently discovered polymorphic population within a wind-blown sand region also contains leucistic (pink) and xanthistic (orange) morphs. Leucism/xanthism frequency was mapped across the subspecies' range revealing that these morphs are generally rare or absent except within regions containing light-colored substrate. Attack rates were estimated using clay models of the three morphs, deployed only at the crepuscular period and during the night, on both light and dark substrates at a site within the dune sand region. Model selection found that the interaction between morph and substrate color best predicted attack rates. Typical morphs had equal attack rates on both substrates while xanthistic and leucistic morphs incurred significantly fewer attacks on light versus dark substrate, and there was no significant difference in attack rates among morphs on light substrates. These results support the idea that xanthistic and leucistic morphs are poorly adapted for dark substrates compared to typical morphs, but they are more or less equally adapted for light substrates. We suggest that this microgeographic island of relaxed selection on light-colored morphs helps explain the existence of this polymorphic population.</p>
Relaxed predation selection on rare morphs of Ensatina salamanders (Caudata: Plethodontidae) promotes a polymorphic population in a novel dune sand habitat
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