東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Cartograph-Bee: Mapping Data-Limited...

Buckner, Mark Andrew,

Linked to FindBook

Google Book

Amazon

博客來

Cartograph-Bee: Mapping Data-Limited Native Bee Diversity and Distributions to Inform Conservation Action /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Cartograph-Bee: Mapping Data-Limited Native Bee Diversity and Distributions to Inform Conservation Action // Mark Andrew Buckner.
Author:	Buckner, Mark Andrew,
Description:	1 electronic resource (162 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
Contained By:	Dissertations Abstracts International86-03B.
Subject:	Macroecology. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31332892
ISBN:	9798384049760

Cartograph-Bee: Mapping Data-Limited Native Bee Diversity and Distributions to Inform Conservation Action /
Buckner, Mark Andrew,

Cartograph-Bee: Mapping Data-Limited Native Bee Diversity and Distributions to Inform Conservation Action /Mark Andrew Buckner. - 1 electronic resource (162 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: B.

Multiple co-occurring drivers of global change are poised to cause global biodiversity loss and the deterioration of ecosystem services and resilience. In both agricultural and wild ecosystems, bees supply essential pollination services. However, the conservation of bees faces challenges due to the scarcity of occurrence data, which is often biased spatially and taxonomically. Despite bee monitoring initiatives gaining public and political support in recent years, they lag current data needs for facilitating the inclusion of bee diversity in contemporary biodiversity conservation decisions. By leveraging existing collection records and community science data through single-, joint, and stacked species distribution models, I predicted current and future bee distributions and species richness. I found that bee species' responses to global change vary based on their life history traits and environmental preferences. In the desert southwest, a global hotspot for bee diversity, the relative threats of urbanization, utility-scale solar energy development and climate change vary across an elevational gradient. Despite extensive sampling in this region, many bee species, especially those at the greatest risk of decline, lack sufficient data to be included in models. I show that distribution models offer a valuable tool to address these data limitations. For example, using a specialist oil bee, Macropis nuda, I exhibit the utility of species distribution models for informing targeted collection of rare species. In both temperate North America and the Desert Southwest, my models predict that bee distributions are likely to shift to track their climate niches, although the extent of predicted redistribution is variable. I demonstrate that with careful data cleaning, correction for spatial bias, and models robust to presence-only data with small sample sizes, it is feasible to generate estimates of bee distributions and diversity using currently available data. Continued refinement of modeling methods for data-limited species and additional data collection are needed to ensure ecologically important pollinators are included in contemporary biodiversity conservation initiatives and land use decisions, including renewable energy development.

English

ISBN: 9798384049760Subjects--Topical Terms:

3188544
Macroecology.
Subjects--Index Terms:

Bees

Cartograph-Bee: Mapping Data-Limited Native Bee Diversity and Distributions to Inform Conservation Action /
LDR:03763nmm a22004453i 4500 001 2432403
005 20250707081456.5
006 m o d
007 cr|nu||||||||
008 261011s2024 miu||||||m |||||||eng d
020 $a 9798384049760
035 $a (MiAaPQD)AAI31332892
035 $a AAI31332892
040 $a MiAaPQD $b eng $c MiAaPQD $e rda
100 1 $a Buckner, Mark Andrew, $e author. $0 (orcid)0000-0002-9692-7454 $3 3821607
245 1 0 $a Cartograph-Bee: Mapping Data-Limited Native Bee Diversity and Distributions to Inform Conservation Action / $c Mark Andrew Buckner.
264 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2024
300 $a 1 electronic resource (162 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
500 $a Advisors: Danforth, Bryan Committee members: Fuller, Angela; Guinness, Joseph; Grodsky, Steven.
502 $b Ph.D. $c Cornell University $d 2024.
520 $a Multiple co-occurring drivers of global change are poised to cause global biodiversity loss and the deterioration of ecosystem services and resilience. In both agricultural and wild ecosystems, bees supply essential pollination services. However, the conservation of bees faces challenges due to the scarcity of occurrence data, which is often biased spatially and taxonomically. Despite bee monitoring initiatives gaining public and political support in recent years, they lag current data needs for facilitating the inclusion of bee diversity in contemporary biodiversity conservation decisions. By leveraging existing collection records and community science data through single-, joint, and stacked species distribution models, I predicted current and future bee distributions and species richness. I found that bee species' responses to global change vary based on their life history traits and environmental preferences. In the desert southwest, a global hotspot for bee diversity, the relative threats of urbanization, utility-scale solar energy development and climate change vary across an elevational gradient. Despite extensive sampling in this region, many bee species, especially those at the greatest risk of decline, lack sufficient data to be included in models. I show that distribution models offer a valuable tool to address these data limitations. For example, using a specialist oil bee, Macropis nuda, I exhibit the utility of species distribution models for informing targeted collection of rare species. In both temperate North America and the Desert Southwest, my models predict that bee distributions are likely to shift to track their climate niches, although the extent of predicted redistribution is variable. I demonstrate that with careful data cleaning, correction for spatial bias, and models robust to presence-only data with small sample sizes, it is feasible to generate estimates of bee distributions and diversity using currently available data. Continued refinement of modeling methods for data-limited species and additional data collection are needed to ensure ecologically important pollinators are included in contemporary biodiversity conservation initiatives and land use decisions, including renewable energy development.
546 $a English
590 $a School code: 0058
650 4 $a Macroecology. $3 3188544
650 4 $a Entomology. $3 615844
650 4 $a Conservation biology. $3 535736
650 4 $a Climate change. $2 bicssc $3 2079509
653 $a Bees
653 $a Biodiversity
653 $a Conservation
653 $a Global change biology
653 $a Species distribution modeling
690 $a 0420
690 $a 0353
690 $a 0408
690 $a 0404
710 2 $a Cornell University. $b Entomology. $e degree granting institution. $3 3821608
720 1 $a Danforth, Bryan $e degree supervisor.
773 0 $t Dissertations Abstracts International $g 86-03B.
790 $a 0058
791 $a Ph.D.
792 $a 2024
856 4 0 $u https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31332892