Location biases in ecological research on Australian terrestrial reptiles

被引:13
作者
Piccolo, Renee Louise [1 ]
Warnken, Jan [1 ,3 ]
Chauvenet, Alienor Louise Marie [1 ,2 ]
Castley, James Guy [1 ,2 ]
机构
[1] Griffith Univ, Sch Environm & Sci, Gold Coast Campus, Gold Coast, Qld 4222, Australia
[2] Griffith Univ, Environm Futures Res Inst, Gold Coast Campus, Gold Coast, Qld 4222, Australia
[3] Griffith Univ, Australian Rivers Inst, Gold Coast Campus, Gold Coast, Qld 4222, Australia
关键词
CONSERVATION PRIORITIES; SAMPLING BIAS; PREDICTION; RICHNESS; MODELS; GAPS;
D O I
10.1038/s41598-020-66719-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Understanding geographical biases in ecological research is important for conservation, planning, prioritisation and management. However, conservation efforts may be limited by data availability and poor understanding of the nature of potential spatial bias. We conduct the first continent-wide analysis of spatial bias associated with Australian terrestrial reptile ecological research. To evaluate potential research deficiencies, we used Maxent modelling to predict the distributions of 646 reptile studies published from 1972 to 2017. Based on existing distributions of 1631 individual reptile study locations, reptile species richness, proximity to universities, human footprint and location of protected areas, we found the strongest predictor of reptile research locations was proximity to universities (40.8%). This was followed by species richness (22.9%) and human footprint (20.1%), while protected areas were the weakest predictor (16.2%). These results highlight that research effort is driven largely by accessibility and we consequently identify potential target areas for future research that can be optimised to ensure adequate representation of reptile communities.
引用
收藏
页数:10
相关论文
共 47 条
[21]   Drones for Conservation in Protected Areas: Present and Future [J].
Jimenez Lopez, Jesus ;
Mulero-Pazmany, Margarita .
DRONES, 2019, 3 (01) :1-23
[22]   Aerial survey of waterbirds on wetlands as a measure of river and floodplain health [J].
Kingsford, RT .
FRESHWATER BIOLOGY, 1999, 41 (02) :425-438
[23]   Not all data are equal: Influence of data type and amount in spatial conservation prioritisation [J].
Kujala, Heini ;
Lahoz-Monfort, Jose Joaquin ;
Elith, Jane ;
Moilanen, Atte .
METHODS IN ECOLOGY AND EVOLUTION, 2018, 9 (11) :2249-2261
[24]   Restoration priorities to achieve the global protected area target [J].
Mappin, Bonnie ;
Chauvenet, Alienor L. M. ;
Adams, Vanessa M. ;
Di Marco, Moreno ;
Beyer, Hawthorne L. ;
Venter, Oscar ;
Halpern, Benjamin S. ;
Possingham, Hugh P. ;
Watson, James E. M. .
CONSERVATION LETTERS, 2019, 12 (04)
[25]   BIOLOGICAL MODELS FOR MONITORING SPECIES DECLINE - CONSTRUCTION AND USE OF DATA-BASES [J].
MARGULES, CR ;
AUSTIN, MP ;
MOLLISON, D ;
SMITH, F .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES, 1994, 344 (1307) :69-75
[26]   Biases in the current knowledge of threat status in lizards, and bridging the 'assessment gap' [J].
Meiri, Shai ;
Chapple, David G. .
BIOLOGICAL CONSERVATION, 2016, 204 :6-15
[27]   Multidimensional biases, gaps and uncertainties in global plant occurrence information [J].
Meyer, Carsten ;
Weigelt, Patrick ;
Kreft, Holger .
ECOLOGY LETTERS, 2016, 19 (08) :992-1006
[28]   Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement (Reprinted from Annals of Internal Medicine) [J].
Moher, David ;
Liberati, Alessandro ;
Tetzlaff, Jennifer ;
Altman, Douglas G. .
PHYSICAL THERAPY, 2009, 89 (09) :873-880
[29]   Maximum entropy modeling of species geographic distributions [J].
Phillips, SJ ;
Anderson, RP ;
Schapire, RE .
ECOLOGICAL MODELLING, 2006, 190 (3-4) :231-259
[30]  
Phillips SJ, Maxent software for modeling species niches and distributions