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Description:
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Ground -based lek surveys have traditionally been used to index trends in prairie
grouse populations (Centrocercus and Tympanuchus spp . ) . However , indices of
abundance or density can be fundamentally flawed and techniques that account for
incomplete detection should be used . Distance sampling is a common technique used to
estimate the density and abundance of animal populations and has been used with aerial
surveys to monitor avian populations . With an increase in renewable energy
development in native prairies and sagebrush steppe , there is a greater need to effectively
monitor prairie grouse populations . One such species , the lesser prairie -chicken (LPC ; T .
pallidicinctus ) , has faced significant population declines and is thus , a species of
conservation concern . In addition , much of the current and proposed wind energy
development in the Great Plains overlaps some of the extant LPC distribution and few
peer -reviewed studies have been conducted to investigate this potential threat to LPCs .
Hierarchical distance sampling models can relate LPC lek density to landscape features
and help predict the potential impact from wind and other energy development on lek
density . Thus , the main objectives of our study were to estimate lek density in the LPC
range in Texas and model anthropogenic and landscape features associated with lek
density . We accomplished this by flying helicopter lek surveys for 2 field seasons and
employing a line -transect method developed at Texas Tech University .
We inventoried 208 , 7 .2 km × 7 .2 km survey blocks and detected 71 new leks , 25
known leks , and observed 5 detections outside the current LPC range . We estimated 2 .0
leks /100 km2 (90 % CI = 1 .5–2 .8 leks /100 km2 ) and 12 .3 LPCs /100 km2 (90 % CI = 8 .5–
17 .9 LPCs /100 km2 ) for our sampling frame . Our state -wide abundance estimates were
Texas Tech University , Jennifer M . Timmer , May 2012
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301 .9 leks (90 % CI = 219 .4–415 .4 leks ) and 1 ,822 .4 LPCs (90 % CI = 1 ,253 .7–2 ,649 .1
LPCs ) . Our best model indicated lek size and lek type (wi = 0 .360 ) influenced lek
detectability . Lek detectability was greater for larger leks and natural leks rather than
man -made leks . We used hierarchical distance sampling to build spatially -explicit
models of lek density and landscape features . The 2 most competitive models included
percent shrubland + transmission line ( >69kv ) density and only percent shrubland (AIC=
943 .817 , wi = 0 .486 ; AIC = 945 .098 , wi = 0 .256 , respectively ) . We model -averaged our
most competitive models and estimated the number of leks in our sampling frame at
245 .7 leks (cv = 0 .137 ) . Lek density peaked at lower levels of transmission line density
and where ≈60 % of the landscape was composed of shrubland patches (shrubs <5 m tall
comprising ≥20 % of the total vegetation ) . Our state -wide survey efforts provide wildlife
managers and biologists with population estimates , new lek locations , and identified
spatially -explicit predictions of lek density . Our spatially -explicit models predicted lek
density based on percent shrubland and transmission line density , which can be used to
predict how lek density may change in response to transmission line development and
changes in habitat conditions . |