Bowling for bees: optimal sample number for “bee bowl” sampling transects
Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the num...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Shapiro, Leo H. [verfasserIn] Tepedino, V. J. [verfasserIn] Minckley, Robert L. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Journal of insect conservation - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997, 18(2014), 6 vom: 18. Nov., Seite 1105-1113 |
|---|---|
| Übergeordnetes Werk: |
volume:18 ; year:2014 ; number:6 ; day:18 ; month:11 ; pages:1105-1113 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10841-014-9720-y |
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| Katalog-ID: |
SPR013655256 |
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| 520 | |a Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. | ||
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10.1007/s10841-014-9720-y doi (DE-627)SPR013655256 (SPR)s10841-014-9720-y-e DE-627 ger DE-627 rakwb eng 590 ASE 42.00 bkl Shapiro, Leo H. verfasserin aut Bowling for bees: optimal sample number for “bee bowl” sampling transects 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. Apiformes (dpeaa)DE-He213 Apoidea (dpeaa)DE-He213 Bee bowl (dpeaa)DE-He213 Bee inventory (dpeaa)DE-He213 Bee sampling (dpeaa)DE-He213 Bees (dpeaa)DE-He213 Pan trap (dpeaa)DE-He213 Tepedino, V. J. verfasserin aut Minckley, Robert L. verfasserin aut Enthalten in Journal of insect conservation Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 18(2014), 6 vom: 18. Nov., Seite 1105-1113 (DE-627)320575330 (DE-600)2016976-0 1572-9753 nnns volume:18 year:2014 number:6 day:18 month:11 pages:1105-1113 https://dx.doi.org/10.1007/s10841-014-9720-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 18 2014 6 18 11 1105-1113 |
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10.1007/s10841-014-9720-y doi (DE-627)SPR013655256 (SPR)s10841-014-9720-y-e DE-627 ger DE-627 rakwb eng 590 ASE 42.00 bkl Shapiro, Leo H. verfasserin aut Bowling for bees: optimal sample number for “bee bowl” sampling transects 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. Apiformes (dpeaa)DE-He213 Apoidea (dpeaa)DE-He213 Bee bowl (dpeaa)DE-He213 Bee inventory (dpeaa)DE-He213 Bee sampling (dpeaa)DE-He213 Bees (dpeaa)DE-He213 Pan trap (dpeaa)DE-He213 Tepedino, V. J. verfasserin aut Minckley, Robert L. verfasserin aut Enthalten in Journal of insect conservation Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 18(2014), 6 vom: 18. Nov., Seite 1105-1113 (DE-627)320575330 (DE-600)2016976-0 1572-9753 nnns volume:18 year:2014 number:6 day:18 month:11 pages:1105-1113 https://dx.doi.org/10.1007/s10841-014-9720-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 18 2014 6 18 11 1105-1113 |
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10.1007/s10841-014-9720-y doi (DE-627)SPR013655256 (SPR)s10841-014-9720-y-e DE-627 ger DE-627 rakwb eng 590 ASE 42.00 bkl Shapiro, Leo H. verfasserin aut Bowling for bees: optimal sample number for “bee bowl” sampling transects 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. Apiformes (dpeaa)DE-He213 Apoidea (dpeaa)DE-He213 Bee bowl (dpeaa)DE-He213 Bee inventory (dpeaa)DE-He213 Bee sampling (dpeaa)DE-He213 Bees (dpeaa)DE-He213 Pan trap (dpeaa)DE-He213 Tepedino, V. J. verfasserin aut Minckley, Robert L. verfasserin aut Enthalten in Journal of insect conservation Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 18(2014), 6 vom: 18. Nov., Seite 1105-1113 (DE-627)320575330 (DE-600)2016976-0 1572-9753 nnns volume:18 year:2014 number:6 day:18 month:11 pages:1105-1113 https://dx.doi.org/10.1007/s10841-014-9720-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 18 2014 6 18 11 1105-1113 |
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10.1007/s10841-014-9720-y doi (DE-627)SPR013655256 (SPR)s10841-014-9720-y-e DE-627 ger DE-627 rakwb eng 590 ASE 42.00 bkl Shapiro, Leo H. verfasserin aut Bowling for bees: optimal sample number for “bee bowl” sampling transects 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. Apiformes (dpeaa)DE-He213 Apoidea (dpeaa)DE-He213 Bee bowl (dpeaa)DE-He213 Bee inventory (dpeaa)DE-He213 Bee sampling (dpeaa)DE-He213 Bees (dpeaa)DE-He213 Pan trap (dpeaa)DE-He213 Tepedino, V. J. verfasserin aut Minckley, Robert L. verfasserin aut Enthalten in Journal of insect conservation Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 18(2014), 6 vom: 18. Nov., Seite 1105-1113 (DE-627)320575330 (DE-600)2016976-0 1572-9753 nnns volume:18 year:2014 number:6 day:18 month:11 pages:1105-1113 https://dx.doi.org/10.1007/s10841-014-9720-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 18 2014 6 18 11 1105-1113 |
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10.1007/s10841-014-9720-y doi (DE-627)SPR013655256 (SPR)s10841-014-9720-y-e DE-627 ger DE-627 rakwb eng 590 ASE 42.00 bkl Shapiro, Leo H. verfasserin aut Bowling for bees: optimal sample number for “bee bowl” sampling transects 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. Apiformes (dpeaa)DE-He213 Apoidea (dpeaa)DE-He213 Bee bowl (dpeaa)DE-He213 Bee inventory (dpeaa)DE-He213 Bee sampling (dpeaa)DE-He213 Bees (dpeaa)DE-He213 Pan trap (dpeaa)DE-He213 Tepedino, V. J. verfasserin aut Minckley, Robert L. verfasserin aut Enthalten in Journal of insect conservation Dordrecht [u.a.] : Springer Science + Business Media B.V, 1997 18(2014), 6 vom: 18. Nov., Seite 1105-1113 (DE-627)320575330 (DE-600)2016976-0 1572-9753 nnns volume:18 year:2014 number:6 day:18 month:11 pages:1105-1113 https://dx.doi.org/10.1007/s10841-014-9720-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2070 GBV_ILN_2086 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2116 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 42.00 ASE AR 18 2014 6 18 11 1105-1113 |
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English |
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Enthalten in Journal of insect conservation 18(2014), 6 vom: 18. Nov., Seite 1105-1113 volume:18 year:2014 number:6 day:18 month:11 pages:1105-1113 |
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Enthalten in Journal of insect conservation 18(2014), 6 vom: 18. Nov., Seite 1105-1113 volume:18 year:2014 number:6 day:18 month:11 pages:1105-1113 |
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Apiformes Apoidea Bee bowl Bee inventory Bee sampling Bees Pan trap |
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Journal of insect conservation |
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Shapiro, Leo H. @@aut@@ Tepedino, V. J. @@aut@@ Minckley, Robert L. @@aut@@ |
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2014-11-18T00:00:00Z |
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To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. 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Shapiro, Leo H. |
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Shapiro, Leo H. ddc 590 bkl 42.00 misc Apiformes misc Apoidea misc Bee bowl misc Bee inventory misc Bee sampling misc Bees misc Pan trap Bowling for bees: optimal sample number for “bee bowl” sampling transects |
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590 ASE 42.00 bkl Bowling for bees: optimal sample number for “bee bowl” sampling transects Apiformes (dpeaa)DE-He213 Apoidea (dpeaa)DE-He213 Bee bowl (dpeaa)DE-He213 Bee inventory (dpeaa)DE-He213 Bee sampling (dpeaa)DE-He213 Bees (dpeaa)DE-He213 Pan trap (dpeaa)DE-He213 |
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ddc 590 bkl 42.00 misc Apiformes misc Apoidea misc Bee bowl misc Bee inventory misc Bee sampling misc Bees misc Pan trap |
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ddc 590 bkl 42.00 misc Apiformes misc Apoidea misc Bee bowl misc Bee inventory misc Bee sampling misc Bees misc Pan trap |
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bowling for bees: optimal sample number for “bee bowl” sampling transects |
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Bowling for bees: optimal sample number for “bee bowl” sampling transects |
| abstract |
Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. |
| abstractGer |
Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. |
| abstract_unstemmed |
Abstract The use of bowl traps to sample bee diversity has become common in recent years. To provide guidance in optimizing bee bowl sampling effort, we used several independent datasets from North America (Pacific Northwest golf courses, suburban Maryland, and Chihuahuan Desert) to estimate the number of bowls in a sampling event at which additional bowls added little to estimates of species richness or to cumulative species lists. We examined changes in the value of a nonparametric richness estimator (Chao2) as a function of bowl number by randomly resampling (without replacement) the data for each sampled transect. We also carried out rarefaction (interpolation of expected species richness for all numbers of bowls up to the actual number). Using as our criterion of “optimal” number of bowl samples per transect the number of samples at which five additional bowls added <1 additional species to the Chao2 estimate, we find that 30-bowl transects would have met this standard for nearly three quarters or more of the sampling events in any of our three datasets (for the suburban Maryland and Chihuahuan Desert data sets, at least three quarters of sampling events met this criterion with just 20 and 25 bowls, respectively). Results from rarefaction analysis for all sampling events indicate that 30-bowl transects would have met our “five additional bowls” standard for more than 80 % of our suburban Maryland and Chihuahuan Desert sampling events, but for only about 61 % of our Pacific Northwest sampling events. For the Pacific Northwest sampling events, there was notable among-site heterogeneity in required sampling intensity. Thus, although 30-bowl transects appear to be adequate for assessing local bee species richness in most instances, investigators may wish to increase (or decrease) this number based on their particular goals and specific knowledge about local bee diversity. |
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| container_issue |
6 |
| title_short |
Bowling for bees: optimal sample number for “bee bowl” sampling transects |
| url |
https://dx.doi.org/10.1007/s10841-014-9720-y |
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| author2 |
Tepedino, V. J. Minckley, Robert L. |
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Tepedino, V. J. Minckley, Robert L. |
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| doi_str |
10.1007/s10841-014-9720-y |
| up_date |
2024-07-03T21:15:49.979Z |
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| score |
7.400985 |