Vascular Plant and Vertebrate Inventory of Saguaro ... - USGS
Vascular Plant and Vertebrate Inventory of Saguaro ... - USGS
Vascular Plant and Vertebrate Inventory of Saguaro ... - USGS
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the relative abundance by repeat-visit transect <strong>and</strong><br />
year. Because relative abundance is the closest<br />
index to true population size that we employ (see<br />
Chapter 1 for more detailed discussion), we use it<br />
to note the “abundance” <strong>of</strong> species.<br />
Relative Frequency <strong>of</strong> Detection. Relative<br />
abundance is the least biased index to abundance<br />
because we control a number <strong>of</strong> variables that<br />
account for differences among transects (e.g.,<br />
the ability to see or hear a bird). However,<br />
we also wanted an index that accounted for all<br />
<strong>of</strong> the species observed within a transect (i.e.,<br />
including birds seen > 75 m, flyovers, <strong>and</strong> birds<br />
seen outside <strong>of</strong> the 8-minute count period) <strong>and</strong><br />
which also conveyed some relative abundance<br />
information. Relative frequency <strong>of</strong> detections<br />
incorporates these observations <strong>and</strong> differs from<br />
relative abundance in that it is clearly biased<br />
toward those species that are highly visible or<br />
vocal. Therefore, it can be thought <strong>of</strong> as an index<br />
<strong>of</strong> the number <strong>of</strong> birds that we saw <strong>and</strong> heard at<br />
typical stations on the transect (i.e., most similar<br />
to an observer’s “experience”). This method also<br />
enables us to convey other important information<br />
regarding species’ presence at the transect level.<br />
Community Classification. Using data from<br />
repeat-visit VCP transects, we sought to identify<br />
bird communities within the district <strong>and</strong> to<br />
compare bird characteristics among communities.<br />
We did not use the original stratification <strong>of</strong><br />
r<strong>and</strong>om transects for this analysis because we<br />
were more interested in identifying communities<br />
than drawing inference to a larger area. To group<br />
transects, we used Ward’s hierarchical cluster<br />
analysis using bird <strong>and</strong> vegetation data. Cluster<br />
analysis is a multivariate technique that groups<br />
like entities (in our case transects) that share<br />
similar values. We performed separate cluster<br />
analyses for the bird <strong>and</strong> vegetation data (see<br />
Chapter 3 for results <strong>of</strong> cluster analysis using<br />
vegetation data). To identify groups from the<br />
bird data we used mean relative abundance for<br />
each transect <strong>and</strong> all visits in both years. We<br />
attempted to include reconnaissance VCP surveys<br />
into this analysis but the results were inconsistent,<br />
most likely because we had no vegetation data for<br />
these transects <strong>and</strong> there was likely insufficient<br />
sampling effort for birds.<br />
50<br />
Comparing Communities. We compared<br />
species richness <strong>and</strong> relative abundance among<br />
community types. To compare species richness<br />
we used a subset <strong>of</strong> data from all transects so<br />
that each transect consisted <strong>of</strong> four visits to<br />
four stations (n = 16); the minimum number<br />
<strong>of</strong> visits <strong>and</strong> stations to repeated-visit transects<br />
(see Table 5.2). We used only those detections<br />
< 75 m from stations (n = 2,476 observations)<br />
<strong>and</strong> excluded flyovers <strong>and</strong> birds seen outside<br />
<strong>of</strong> the eight-minute count period. To compare<br />
relative abundance among communities, we<br />
used observations from all visits <strong>and</strong> stations<br />
<strong>and</strong> did not choose a subset <strong>of</strong> observations (as<br />
for species richness) because relative abundance<br />
is scaled by survey effort. We tested for<br />
differences among all communities using oneway<br />
analysis <strong>of</strong> variance (ANOVA) <strong>and</strong> searched<br />
for pairwise differences between communities<br />
using the Tukey-Kramer procedure. We logtransformed<br />
relative abundance data to better<br />
meet assumptions <strong>of</strong> normality.<br />
Line-transect Surveys<br />
Field Methods<br />
We used a modified line-transect method (Bibby<br />
et al. 2002) to survey for birds from November<br />
2002 to February 2003. Line transects differ<br />
from VCP transects in that an observer records<br />
birds seen or heard while the observer is walking<br />
an envisioned line rather than while st<strong>and</strong>ing at<br />
a series <strong>of</strong> stations. The line-transect method is<br />
more effective during the non-breeding season<br />
because bird vocalizations are less conspicuous<br />
<strong>and</strong> frequent <strong>and</strong> therefore birds tend to be more<br />
difficult to detect aurally (Bibby et al. 2002).<br />
We established three transects in the<br />
district (Fig. 5.2). Transects were broken into<br />
sections, each approximately 250 m in length. As<br />
with VCP transects, we alternated direction <strong>of</strong><br />
travel to reduce biases <strong>and</strong> did not survey during<br />
periods <strong>of</strong> excessive rain or wind (see VCP<br />
survey methods for details). We began surveys<br />
about 30 minutes after sunrise <strong>and</strong> continued until<br />
we completed the transect. As with VCP surveys,<br />
we recorded weather conditions at the beginning<br />
<strong>and</strong> end <strong>of</strong> each survey. We timed our travel so<br />
that we traversed each section in ten minutes,