IDENTIFYING SEX OF FISHERS (MARTES PENNANTI) VISITING CAMERA STATIONS IN THE

SIERRA NATIONAL FOREST, CALIFORNIA Carrie J. O’Brien and Rick A. Sweitzer

College of Natural Resources Center for Forestry

University of California, Berkeley CA 94720

Figure 1. SNAMP fisher study area, Bass Lake Ranger District of

the Sierra National Forest, CA.

Introduction Automatic cameras are increasingly used to provide estimates of

population size or abundance for rare carnviores based on individual

variation in pelage patterns (Harihar et al. 2010; Janecka et al.

2011). Many species do not have individually distinct pelage

patterns but do vary in body size between sexes. Pacific fishers

(Martes pennanti) exhibit strong sexual dimorphism in body size;

adult males captured on the Sierra Nevada Adaptive Management

Project weighed approximately twice that of adult females (4.3 kg

vs. 2.1 kg, respectively). Our goal here is to develop a technique for

distinguishing the sex of individual fishers visiting camera stations

distributed over an approx. 1500 km2 region of the Sierra National

Forest (Figure 1). Each camera station was outfitted with a

rectangular wood slat affixed with narrow bands of infrared

reflective tape spaced every 20 cm to facilitate measuring fishers

that climbed bait trees to investigate or consume bait in a sock

nailed to the tree. In addition, bands of infrared reflective tape glued

to the antennas of radiocollars in specific/known patterns allowed us

to identify individual fishers visiting camera stations. By comparing

morphometric measurements taken during captures to those

obtained for known fishers at camera stations, we are able to

identify which variables are most useful for differentiating between

the sexes. Herein we will describe our use of discriminant function

analyses to select morphometric measurements, evaluate the

efficacy of sex determination using cameras, and discuss whether

our technique can be used to enumerate the minimum number of

fishers present in our study area..

Future Directions and Comments The discriminant function model for total body length measurements for known sex animals at camera

stations was applied to noncollared fishers. The model predicted that 99 of the noncollared animals were

males and 155 were females. Importantly, however, the same unknown fisher will often be detected

multiple times at the same survey station or at nearby stations. Because of this a simple scoring by sex

cannot be used to estimate the minimum number of males and females present in our population without

first attempting to discriminate individuals. It may be possible to use the full suite of measurements

obtained from images to identify individual animals, however, and some of our planned future analyses

will explore this idea further. Please contact the authors for further details on our methods and analyses.

Literature Cited Harihar, A., M. Ghosh, M. Fernandes, B. Pandav, and S. Goyal. 2010. Use of photographic capture-recapture sampling to estimate density of striped hyena

(Hyaena hyaena): implications for conservation. Mammalia 74: 83-87.

Janecka, J. E., B. Munkhtsog, R. M. Jackson, G. Naranbaatar, D. P. Mallon, and W. J. Murphy. 2011. Comparison of noninvasive genetic and camera-trapping

techniques for surveying snow leopards. Journal of Mammalogy: 92(4):771-783.

Svagelj, W. S. and F. Quintana. 2007. Sexual size dimorphism and sex determination by morphometric measurements in breeding imperial shags

(Phalacrocorax atriceps). Waterbirds 30(1): 97-102.

Results and Discussion All measured characteristics obtained from captures differed significantly between the sexes, with the ear measurements,

foot width, and head length showing the highest SSD (Table 2A). All measurements that were different between males

and females from capture measurements were also different for camera data with the exception of Ears front and Ears top

(Table 2). Although our initial analyses revealed that juvenile male fishers were smaller than subadult+adults for Head

length and Total length, juvenile males were still larger than any age female for those features. Because of this, and

because our primary interest was in discriminating between males and females at camera survey stations, all of the body

measures taken from camera images except Ears front, and Ears top will be useful for this purpose.

In general, the most difficult measurements to accurately record from camera images were Head length, Ears front, and

Foot length. Care must be taken when selecting appropriate images for measurements, and not all visits to cameras by

fishers included images appropriate for measurements.

The best discriminant function for camera measurements was total length which correctly classified 99% of fishers

(Table 3 and Figure 2A). The best model for assigning sex to known ID animals from measurements taken during

captures was Head Body + Tail, which correctly classified 95% of fishers (Figure 2B). Although many of our

preliminary DFA models were useful for discriminating sex (classification accuracy ≥ 85%), here we report details on

four different DFA models that correctly classified at least 90% of known sex fishers (Table 3). Experience gained from

measuring body features on images indicated that the most readily obtained measures were Total length, Head+Body, and

Tail. Although several DFA models identified ear measurements and foot measurements as being useful, these measures

had high CVs (Table 2), indicating difficulty in obtaining accurate values.

Logistical constraints for those interested in using our methods include reflective band loss from the radiocollar antennas

of known ID animals. We have attempted to minimize reflective band loss by using superglue to attach the bands to the

radiocollar antennas, but some band loss is expected and antenna breakage is frequent. Both band loss from radiocollars

and antenna breakage complicate efforts to use camera survey data for "mark-recapture" modeling.

Methods

Images of each fisher visit to camera stations were reviewed to identify those suitable for

obtaining morphological measurements with at least 2 reflective bands on the wood slat

visible. Whenever possible, we extracted ≥ 2 images from each fisher visit for measurement,

thereby allowing calculation of mean values.

Nine different morphological features were measured during captures and from images

(detailed in Table 1).

Images were processed and measured using ImageJ software

(http://imagej.nih.gov/ij/notes.html). We set the scale on the image by drawing a straight line

between reflective bands on the wood slat (Figure 2).

Patterns of reflective tape bands on the antennas of radiocollars fitted for fishers during

capture were used to assign identity to radiocollared fishers detected at camera stations.

Standard descriptive statistics (one-way ANOVAs) were used to investigate patterns in

sexual dimorphism in morphological features measured during captures and from camera

images.

We calculated an index of sexual size dimorphism (SSD) and a coefficient of variation

(CV) for each measured variable (Svagelj and Quintana 2007). Combined metrics on SSD

and CVs for each parameter were evaluated to identify those potentially useful for

discriminating sex.

Discriminant function analyses (DFA) were used to assess which morphological

measurements were most appropriate for assigning sex to known ID/sex fishers. A Pearson

correlation matrix aided in selecting variables to include in DFA models that minimized use

of highly correlated measurements.

Discriminant function analyses were used to assign sex to unknown ID fishers detected at

camera stations

All statistical analyses were completed using SYSTAT 13.0 (SYSTAT Software Inc.,

Chicago, IL)

Acknowledgments: USDA Forest Service, US Fish and Wildlife Services, California Dept of Fish and Game.

SNAMP Crew & Volunteers: M. Anderson, J. Ashling, J. Berg, J. Bridges, J. Busiek, M. Cancellare, A. Cellar, G. Cline, L. Cline, T. Day, Z. Eads, T.

Gorman, D. Hardeman, Jr., D. Jackson, R. Jensen, W. Lanier, J. Massarone, W. Mitchell, B. Neiles, , M. Ratchford, J. Ruthven, J. Schneiderman, W.

Sicard, T. Thein, S. Vogel, K. Wagner, T. Watson, R. Wise.

Figure 4. Classification results from the highest-ranking discriminant function model based on measurements from (A) camera

images and (B) capture events. The discriminant function in (A) is total length, and in (B) Head Body + Tail.

A. B.

Figure 2. Procedure for setting the scale for

images within the ImageJ program.

Figure 3. Examples of body measurements from captures (top row) and from camera images within the

ImageJ program (bottom row). From left to right, the measurements are head + body length, head length, and

ears top.