scholarly journals Pollen sleuthing for terrestrial plant surveys: Locating plant populations by exploiting pollen movement

2018 ◽  
Vol 6 (1) ◽  
pp. e1020
Author(s):  
Lesley G. Campbell ◽  
Stephanie J. Melles ◽  
Eric Vaz ◽  
Rebecca J. Parker ◽  
Kevin S. Burgess
Genetics ◽  
2002 ◽  
Vol 161 (1) ◽  
pp. 355-363
Author(s):  
Frédéric Austerlitz ◽  
Peter E Smouse

Abstract The distance of pollen movement is an important determinant of the neighborhood area of plant populations. In earlier studies, we designed a method for estimating the distance of pollen dispersal, on the basis of the analysis of the differentiation among the pollen clouds of a sample of females, spaced across the landscape. The method was based solely on an estimate of the global level of differentiation among the pollen clouds of the total array of sampled females. Here, we develop novel estimators, on the basis of the divergence of pollen clouds for all pairs of females, assuming that an independent estimate of adult population density is available. A simulation study shows that the estimators are all slightly biased, but that most have enough precision to be useful, at least with adequate sample sizes. We show that one of the novel pairwise methods provides estimates that are slightly better than the best global estimate, especially when the markers used have low exclusion probability. The new method can also be generalized to the case where there is no prior information on the density of reproductive adults. In that case, we can jointly estimate the density itself and the pollen dispersal distance, given sufficient sample sizes. The bias of this last estimator is larger and the precision is lower than for those estimates based on independent estimates of density, but the estimate is of some interest, because a meaningful independent estimate of the density of reproducing individuals is difficult to obtain in most cases.


2013 ◽  
Vol 7 (1) ◽  
pp. 123-139 ◽  
Author(s):  
Steven J. Franks ◽  
Jennifer J. Weber ◽  
Sally N. Aitken

Crop Science ◽  
1978 ◽  
Vol 18 (3) ◽  
pp. 359-362 ◽  
Author(s):  
R. J. Martin ◽  
J. R. Wilcox ◽  
F. A. Laviolette

2021 ◽  
Vol 687 (1) ◽  
pp. 012200
Author(s):  
Jialin Li ◽  
Jiao Yang ◽  
XueWei Sun ◽  
Jincheng Luo ◽  
Hongbin Qiu ◽  
...  

Author(s):  
M. Patrick Griffith ◽  
Falon Cartwright ◽  
Michael Dosmann ◽  
Jeremie Fant ◽  
Ethan Freid ◽  
...  

Diversity ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 255
Author(s):  
Diana L. Soteropoulos ◽  
Caitlin R. De Bellis ◽  
Theo Witsell

Biodiversity data support conservation research and inform conservation decisions addressing the wicked problem of biodiversity loss. However, these data often need processing and compilation before use, which exceed the time availability of professional scientists. Nevertheless, scientists can recruit, train, and support a network of citizen scientists to prepare these data using online platforms. Here, we describe three citizen science projects sponsored by the Arkansas Natural Heritage Commission to transcribe and georeference historic herbarium specimens and document current biodiversity through iNaturalist for two highly biodiverse and rapidly developing counties in Northwest Arkansas, USA. Citizen science-generated data will be used in a county natural heritage inventory (CNHI) report, including a comprehensive list of taxa tied to voucher specimens and records for rare plant populations. Since the CNHI project started in 2018, citizen scientists have transcribed 8,855 and georeferenced 2,636 specimen records. From iNaturalist observations, 125 rare plant populations of 39 taxa have been documented. This CNHI report will determine the most critical taxa, habitats, and sites for conservation action in the region and will inform conservation stakeholders at the local, state, and federal levels as they engage in land acquisition, ecological restoration, natural resource management, planning of growth and development, and environmental review/regulation.


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