Item talk:Q272327
From geokb
{
"USGS Publications Warehouse": { "@context": "https://schema.org", "@type": "Article", "additionalType": "Journal Article", "name": "Ecological neighborhoods as a framework for umbrella species selection", "identifier": [ { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse IndexID", "value": "70197081", "url": "https://pubs.usgs.gov/publication/70197081" }, { "@type": "PropertyValue", "propertyID": "USGS Publications Warehouse Internal ID", "value": 70197081 }, { "@type": "PropertyValue", "propertyID": "DOI", "value": "10.1016/j.biocon.2018.04.026", "url": "https://doi.org/10.1016/j.biocon.2018.04.026" } ], "journal": { "@type": "Periodical", "name": "Biological Conservation", "volumeNumber": "223", "issueNumber": null }, "inLanguage": "en", "isPartOf": [ { "@type": "CreativeWorkSeries", "name": "Biological Conservation" } ], "datePublished": "2018", "dateModified": "2018-05-17", "abstract": "Umbrella species are typically chosen because they are expected to confer protection for other species assumed to have similar ecological requirements. Despite its popularity and substantial history, the value of the umbrella species concept has come into question because umbrella species chosen using heuristic methods, such as body or home range size, are not acting as adequate proxies for the metrics of interest: species richness or population abundance in a multi-species community for which protection is sought. How species associate with habitat across ecological scales has important implications for understanding population size and species richness, and therefore may be a better proxy for choosing an umbrella species. We determined the spatial scales of ecological neighborhoods important for predicting abundance of 8 potential umbrella species breeding in Nebraska using Bayesian latent indicator scale selection in N-mixture models accounting for imperfect detection. We compare the conservation value measured as collective avian abundance under different umbrella species selected following commonly used criteria and selected based on identifying spatial land cover characteristics within ecological neighborhoods that maximize collective abundance. Using traditional criteria to select an umbrella species resulted in sub-maximal expected collective abundance in 86% of cases compared to selecting an umbrella species based on land cover characteristics that maximized collective abundance directly. We conclude that directly assessing the expected quantitative outcomes, rather than ecological proxies, is likely the most efficient method to maximize the potential for conservation success under the umbrella species concept.", "description": "8 p.", "publisher": { "@type": "Organization", "name": "Elsevier" }, "author": [ { "@type": "Person", "name": "Fontaine, Joseph J. jfontaine@usgs.gov", "givenName": "Joseph J.", "familyName": "Fontaine", "email": "jfontaine@usgs.gov", "identifier": { "@type": "PropertyValue", "propertyID": "ORCID", "value": "0000-0002-7639-9156", "url": "https://orcid.org/0000-0002-7639-9156" }, "affiliation": [ { "@type": "Organization", "name": "Coop Res Unit Atlanta", "url": "https://www1.usgs.gov/coopunits/unit/Georgia" }, { "@type": "Organization", "name": "Coop Res Unit Seattle", "url": "https://www1.usgs.gov/coopunits/unit/Washington" } ] }, { "@type": "Person", "name": "Stuber, Erica F.", "givenName": "Erica F.", "familyName": "Stuber" } ], "funder": [ { "@type": "Organization", "name": "Coop Res Unit Atlanta", "url": "https://www1.usgs.gov/coopunits/unit/Georgia" } ] }, "OpenAlex": { "_id": "https://openalex.org/w2802162863", "abstract_inverted_index": { "Umbrella": [ 0 ], "species": [ 1, 14, 32, 40, 63, 78, 93, 123, 153, 182, 198, 238 ], "are": [ 2, 7, 52 ], "typically": [ 3 ], "chosen": [ 4, 41 ], "because": [ 5, 38 ], "they": [ 6 ], "expected": [ 8, 186, 215 ], "to": [ 9, 16, 178, 194, 228 ], "confer": [ 10 ], "protection": [ 11, 74 ], "for": [ 12, 58, 72, 88, 102, 116, 137, 232 ], "other": [ 13 ], "assumed": [ 15 ], "have": [ 17 ], "similar": [ 18 ], "ecological": [ 19, 83, 113, 169, 220 ], "requirements.": [ 20 ], "Despite": [ 21 ], "its": [ 22 ], "popularity": [ 23 ], "and": [ 24, 92, 95, 159 ], "substantial": [ 25 ], "history,": [ 26 ], "the": [ 27, 30, 59, 109, 142, 214, 224, 230, 236 ], "value": [ 28, 144 ], "of": [ 29, 61, 112, 119, 191 ], "umbrella": [ 31, 39, 105, 122, 152, 181, 197, 237 ], "concept": [ 33 ], "has": [ 34, 85 ], "come": [ 35 ], "into": [ 36 ], "question": [ 37 ], "using": [ 42, 127 ], "heuristic": [ 43 ], "methods,": [ 44 ], "such": [ 45 ], "as": [ 46, 55, 146 ], "body": [ 47 ], "or": [ 48, 65 ], "home": [ 49 ], "range": [ 50 ], "size,": [ 51 ], "not": [ 53 ], "acting": [ 54 ], "adequate": [ 56 ], "proxies": [ 57 ], "metrics": [ 60 ], "interest:": [ 62 ], "richness": [ 64 ], "population": [ 66, 90 ], "abundance": [ 67, 118, 149, 188, 207 ], "in": [ 68, 125, 133, 184, 189 ], "a": [ 69, 99 ], "multi-species": [ 70 ], "community": [ 71 ], "which": [ 73 ], "is": [ 75, 222 ], "sought.": [ 76 ], "How": [ 77 ], "associate": [ 79 ], "with": [ 80 ], "habitat": [ 81 ], "across": [ 82 ], "scales": [ 84, 111 ], "important": [ 86, 115 ], "implications": [ 87 ], "understanding": [ 89 ], "size": [ 91 ], "richness,": [ 94 ], "therefore": [ 96 ], "may": [ 97 ], "be": [ 98 ], "better": [ 100 ], "proxy": [ 101 ], "choosing": [ 103 ], "an": [ 104, 180, 196 ], "species.": [ 106 ], "We": [ 107, 140, 209 ], "determined": [ 108 ], "spatial": [ 110, 164 ], "neighborhoods": [ 114, 170 ], "predicting": [ 117 ], "8": [ 120 ], "potential": [ 121, 231 ], "breeding": [ 124 ], "Nebraska": [ 126 ], "Bayesian": [ 128 ], "latent": [ 129 ], "indicator": [ 130 ], "scale": [ 131 ], "selection": [ 132 ], "N-mixture": [ 134 ], "models": [ 135 ], "accounting": [ 136 ], "imperfect": [ 138 ], "detection.": [ 139 ], "compare": [ 141 ], "conservation": [ 143, 233 ], "measured": [ 145 ], "collective": [ 147, 173, 187, 206 ], "avian": [ 148 ], "under": [ 150, 235 ], "different": [ 151 ], "selected": [ 154, 160 ], "following": [ 155 ], "commonly": [ 156 ], "used": [ 157 ], "criteria": [ 158, 177 ], "based": [ 161, 199 ], "on": [ 162, 200 ], "identifying": [ 163 ], "land": [ 165, 201 ], "cover": [ 166, 202 ], "characteristics": [ 167, 203 ], "within": [ 168 ], "that": [ 171, 204, 211 ], "maximize": [ 172, 229 ], "abundance.": [ 174 ], "Using": [ 175 ], "traditional": [ 176 ], "select": [ 179 ], "resulted": [ 183 ], "sub-maximal": [ 185 ], "86%": [ 190 ], "cases": [ 192 ], "compared": [ 193 ], "selecting": [ 195 ], "maximized": [ 205 ], "directly.": [ 208 ], "conclude": [ 210 ], "directly": [ 212 ], "assessing": [ 213 ], "quantitative": [ 216 ], "outcomes,": [ 217 ], "rather": [ 218 ], "than": [ 219 ], "proxies,": [ 221 ], "likely": [ 223 ], "most": [ 225 ], "efficient": [ 226 ], "method": [ 227 ], "success": [ 234 ], "concept.": [ 239 ] }, "apc_list": { "value": 3570, "currency": "USD", "value_usd": 3570, "provenance": "doaj" }, "apc_paid": null, "authorships": [ { "author_position": "first", "author": { "id": "https://openalex.org/A5035766091", "display_name": "Erica F. 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