Depredation Claim Behavior and Tolerance of...

Journal of Agricultural and Applied Economics, 32, l(April 2000): 175–188@ 2000 Southern Agricultural Economics Association

Depredation Claim Behavior and Toleranceof Wildlife in Wyoming

Larry W. Van Tassell, Bozheng Yang, and Clynn Phillips

ABSTRACT

Wyoming Game and Fish Department depredation payments were established to increaselandowner tolerance toward, and thus the supply of, certain types of wildlife. This studyexamined how socio-economic and demographic characteristics of farmers and ranchersin Wyoming relate to tolerance toward wildlife and depredation claim submission. Theseverity of depredation and landowner satisfaction with the depredation policy were eval-uated. The financial stability and economic intent of farmers and ranchers significantlyinfluenced tolerance toward wildlife. Landowners tended to be less tolerantof depredationensuing from elk. The complexity of the submission process was a deterrentto damageclaim submissions.

Key Words: depredation, probit model, wildlife.

Wildlife in Wyoming, as in other states, areheld in trust by the State. The Wyoming Gameand Fish Department (WGFD) along with theWyoming Game and Fish Commission estab-lishes big game population objectives. Popu-lation levels are both habitat and politicallydependent. Natural habitat, hunting access andlandowner tolerance of wildlife are includedin setting target population numbers (Van Tas-sell, Phillips and Hepworth).

Landowner tolerance has become a crucialfactor in determining the expanse of wildlifehabitat. Craven et al. suggest that tolerance,not habitat, may be the limiting factor that im-poses population bounds on big game. Publictolerance of wildlife damage is especially lowin many western states where public lands act

Larry Van Tassellis a professor and head of the De-partmentof AgriculturalEconomics and Rural Soci-ology, University of Idaho, Moscow, ID. BozhengYang is a former graduate student and Clynn Phillipsis a professor in the Department of Agricultural andApplied Economics, University of Wyoming, Laramie,WY.

as reservoirs from which big game move tofeed upon private resources (Davis, Parsonsand Randall; Conover). In a survey of south-western Montana landowners, Lacey et al. es-timated that big game consumed a yearly av-erage of511 animal unit months (AUMS) [ perlandowner at a cost of $5,616. While manylandowners are willing to tolerate some dam-age because of moral obligations or the aes-thetic, recreational and economic benefitswildlife provide, tolerance levels quickly di-minish as a landowner’s economic dependenceon the land increases (Lacey et al.).

Big game depredation also has been aproblem throughout the United States. Con-over reported that 89 percent of respondentsin a national survey alleged wildlife damageon their agricultural operations and 53 percentstated that the losses exceeded their tolerance.Fifty-five percent purposely provided habitatfor wildlife by including cover near fields,

1An AUM is the amount of forage required to feeda mature cow or equivalent for one month.

176 Journal of Agricultural and Applied Economics, April 2000

400000

350000

300000

250000

200000

150000

100000

50000

050 61 72 83 94

YEAR

Figure 1. Damage claim payments paid by Wyoming Game and Fish Department, 1950–1995

leaving crop residue, providing a water source,or leaving a portion of the crop unharvested.Yet, 38 percent stated that the damage was “sosevere that it reduced their willingness to pro-vide wildlife habitat on their property” (Con-over, p. 99).

To increase landowner tolerance, and thusthe supply of wildlife, the WGFD is autho-rized to compensate individuals for damagecaused by big or trophyz game animals andgame birds (Wyoming Game and Fish De-partment, 1993). The Wyoming Legislaturefirst authorized reimbursement for game ani-mal depredation in 1925 and the first wildlifedamage compensation law was adopted in1929. Claims were historically paid from thegeneral operating budget of the WGFD. In1980, the Wyoming Legislature authorized di-version of the $5.00 nonresident license ap-plication fee to develop a $500,000 depreda-tion fund. Once the $500,000 was collected,25 percent of the nonresident application feewas authorized for maintenance of the fund.In recent years, approved claim payments havebeen too large for the fund to be maintainedmerely with application fees. Money thatwould normally be used for other departmen-tal programs has been used to pay damage

2The WGFD defines big game to include deer, elk,antelope and moose. Trophy game includes black bear,grizzly bear and mountain lion.

claims because depredation remuneration lim-its are not tied to the solvency of the fund.

Wyoming’s depredation policy prohibitsthe WGFD from considering claims less than

$1003 or from landowners that do not permithunting on their private land. The damage law

also stipulates that landowners must notify the

Department no later than 15 days after thedamage is discovered and must present a ver-ified claim that specifies the damage andamount claimed no later than 60 days after thelast item of damage is discovered. A “verifiedclaim” is a claim that the claimant has signedand sworn to be accurate before a person au-thorized to administer oaths. Claims are to beinvestigated, processed and paid (if approved)by the Department within 90 days of submis-sion. If the Department fails to act within 90days, the claim, including interest, will be al-lowed. An appeals procedure has also been es-tablished if a claim is disallowed (WyomingGame and Fish Department, 1993).

Lacey et al. found that damage claim sub-missions in Montana increased with the se-verity of winter and the financial condition ofranchers. Current increases in depredationclaim payments (Figure 1) have been concern-ing to WGFD officials, especially when con-sidering what may transpire if all regions in

~Since this study was undertakenthe WGFDdroppedthe $100 minimumdamagerequirement.

Van Tassell, Yang, and Phillips: Depredation Claims and Wildhfe Tolerance 177

Wyoming experienced a severe winter coupledwith low farm income. Changing demographicand socio-economic characteristics of Wyo-ming farmers and ranchers also are discon-certing. It is unknown if current trends in dam-age claim submissions are due to increasedwildlife depredation, changing landowner tol-erance or a combination of factors.

Experience has shown that failure to con-sider and be responsive to landowner feelingsand attitudes in wildlife-related issues can leadto potential landowner resistance (Krucken-berg). Resistance can include political actions,hunting restrictions, land posting and disre-gard of laws designed to facilitate manage-ment. Given current trends of suburbanization,wildlife habitat losses will likely continue.There is little doubt that private lands willcontinue to be important to wildlife prosperity(Davis, Parsons and Randall). Understandingthe attitudes of landowners is one of the firststeps in gaining their cooperation in wildlifemanagement.

This study sought to identify landowner so-cio-economic and demographic characteristicsthat influence damage claim submission andwildlife tolerance. The severity of depredation,the tolerance level of landowners, and theirsatisfaction with the depredation policy ad-ministered by the WGFD also were evaluated.

where Mti is a vector of management/personalcharacteristics for individual j associated withalternative t and WU is a vector of wildlife/depredation conditions facing individual j giv-en alternative t.

Landowners evaluate the utility and obli-gations associated with the presence of wild-life and ascertain the level of wildlife thatmaximizes utility. Because wildlife are de-clared to be held in trust by each State, thelandowner holds no property right with respectto wildlife and has limited control on wildlifenumbers. When wildlife numbers are less thanor equal to those that maximize U,j, toleranceof wildlife (e.g., don’t submit depredationclaims) is expressed. The opposite occurswhen wildlife levels exceed those representedby U,r

Tolerance or depredation claim behaviorcan be represented by a yes or no response,i.e., the event in question is undertaken if thelandowner’s expected utility is “largeenough”. Large enough is assessed by an un-observable utility index variable, Z, and a crit-ical value Z~ associated with each landowner.When 1, > I: the event occurs and when I, sz~ the event does not occur. Given the as-

sumption of normality, the probability that Z~is less than or equal to 1, can be computedfrom the cumulative normal density functionas:

Model Specification(2) Pi = Pr(Z~ s 1,) = F(Z)

A landowner’s decision regarding wildlife tol-erance and depredation claim submission canbe considered within the conceptual frame-work of utility maximization. Consider a setof T wildlife tolerance alternatives (e.g., sub-mit depredation claims) facing J landowners,with each alternative t (t = 1, . . . . T) provid-ing utility to landowner j (j = 1, . . . . J). Inthe decision-making process, landowner jchooses an alternative t, which maximizes his/her utility. Maximum utility, Uti, attainable forlandowner j given each alternative t can beexpressed as:

(1) U. = u(h-o, w,,), t=l ,. ... z

j=l, . . ..J.

J/(

_—

- & -.‘-’2’2“

where, z is the standard normal density. Bydesign, P, will lie in the interval (O, 1). Aprobit mode14 based on utility theory as de-

4A popular alternative to the probit specification isthe logistic specification. The logit model is based onthe cumulative logistic probability function. The twodistributions are similar except the logistic is heavierin the tails. When the values of X‘(3 are intermediatein size (e.g., – 1,2 to + 1.2) the logit and probit spec-ifications provide similar results (Greene, 1993).Greene (1993, p. 638) states that “it is difficult to jus-tify the choice of one distribution or another on theo-retical grounds”. Amemiya expresses similar views.Both formulations have been used extensively in the


veloped by McFadden can specify the rela-tionship implied by equation (1). The probitmodel can be estimated by the maximum like-lihood method as:

where Y, is the observed decision by the land-

owner which is ordinal in nature, X, is a matrix

of explanatory variables, ~ is a vector of un-

known parameters, e, is an independently dis-

tributed disturbance term with zero mean and

unit variance, i.e., e, - N(O, 1), and If is thecritical value. Parameter estimates for the @

vector can be obtained from the statistical

package LIMDEP (Greene, 1989). For this

study, a significance level of ci s 0.10 was

used to determine the statistical significance ofthe p parameters.

The parameters of the probit model, likeother nonlinear regression models, are not nec-essarily the marginal effects generally ob-tained from linear regression models. In thebinary setting, marginal effects in a probitmodel can be calculated as:

Marginal effects are related to the values of X,which are generally calculated at the means ofthe regressors. This approach is appropriatefor continuous variables, but is not valid forevaluating the effects of dummy variables. Adummy variable is generally analyzed by com-paring the probabilities that result when thevariable takes on its two values with those thatoccur while other variables are held at theirsample means. The marginal effects of all var-iables in the specification should sum to zero

(Greene, 1993). A significance level of ~ s

literature. The binary response model regression wasused to construct the Lagrange multiplier test for theprob]t versus the logit model for data used in this study(Greene, 1993). The chi square (x’) values (P <0. 10)indicate that the probit and logit model estimates werenot statistically different. Because the probit and Iogitformulations yielded similar results, the probit speci-fication was arbitrarily chosen for this research.

0.10 was used to determine the statistical sig-nificance of the marginal probability parame-ters.

All models were tested for heteroscedastic-ity (Greene, 1993), with all likelihood ratiostatistics rejecting heteroscedasticity (a =O.10). A separate analysis also was conductedto test for multicollinearity using condition in-dices (Belsley), with all condition indices be-ing less than 19, indicating no collinearity.

The landowner’s utility was hypothesizedto be conditional upon his/her personal attri-butes or socioeconomic characteristics and onthe characteristics related to the wildlife spe-cies and depredation. To aid in the discussionof the independent variables included in theempirical models, variables were organized aslandowner characteristics, management char-acteristics, wildlife species, level of damageand landowner’s attitudes concerning wildlife.

Owner Characteristics

Experience managing a farm or ranch is hy-pothesized to have a positive influence onlandowner tolerance and a negative relation-ship with damage claim submissions. Years ofage, a measure of experience, has been shownto be positively associated with the adoptionof conservation practices and integrated pestmanagement practices (Ervin and Ervin;Korsching et al.; McNamara, Wetzstein andDeuce). With experience, a landowner maylearn to coexist with wildlife and should bemore aware of the importance of passing thisnatural heritage onto the next generation.

The level of education is hypothesized tohave a positive relationship with landownertolerance and a negative relationship withdamage claim submissions. Kellert found thatindividuals with a Ph.D. ranked high on attri-butes showing an ecosystem emphasis and aninterest in the physical attributes and biologi-cal functioning of animals. These individualsalso ranked low on attributes portraying a pri-mary concern for the material values of ani-mals and the satisfaction derived from masteryand control over animals. Adams, Newgardand Thomas compared human wildlife orien-tations between high school and college stu-

Van Tassell, Yang, and Phillips: Depredation Claims and Wildll~e Tolerance 179

dents. Their study indicated that college stu-dents held a more positive orientation than didhigh school students concerning attitudes, per-ceptions and activities with regard to wildlife.As the education level of landowners increas-es, landowners may be less intimidated by thedamage claim submission process, but theirtolerance level of wildlife also should in-crease, causing their damage claim submis-sions to decrease.

An increasing number of ranch owners areobtaining their main source of income fromoff-farm activities, This lack of dependenceupon agriculture for their livelihood may im-pact landowners’ tolerance toward wildlife. Inthe current study, landowners whose mainsource of income is off-farm are hypothesizedto be more tolerant of wildlife and less in-clined to submit damage claims.

Residency of landowners is hypothesizedto have an effect on their tolerance towardwildlife and their damage claim submissionpractices. If the landowner does not reside onthe ranch, his or her tolerance level is hypoth-esized to be higher since exposure to wildlifewill be diminished. Likewise, damage claimsubmissions should be less frequent.

Decker and Brown found that tolerance ofwildlife damage varied with the ability towithstand economic consequences of damage.Hackett (p. 309) commented that, “to thefarmer, in the midst of a personal economicdisaster one deer may seem too many.” In thepresent study, a landowner’s assessment of fi-nancial stress is used as a measure of econom-ic tolerance. As financial stress increases,landowner tolerance towards wildlife is ex-pected to decrease while damage claim sub-missions are expected to be more common.

A landowner’s exposure to wildlife mayberelated to the size of the operation (i.e., thetotal forage base)5. Thus, as the total foragebase increases, wildlife exposure should in-

5To provide an overall ranch size measurement, thevalue of the forage base was created using a weightedsum of acreage values based on 1992 Wyoming realestate prices (Bastian, Foulke, and Hewlett). Individualvalues were $493/acre for hayland, $66 l/acre for crop-Iand, $59/acre for rsmgeland, and $43/AUM for federalpermits.

crease and negatively impact the tolerance lev-el of the landowner while increasing damageclaim submissions. Using this reasoning, theassumption is made that all resources are fullyemployed regardless of the size of operationso that depredation should not have a greaterimpact on a landowner with a smaller foragebase.

Management Characteristics

Reason for purchasing or maintaining owner-ship in a farm or ranch is another factor thatmay influence a landowner’s tolerance of wild-life and damage claim submission behavior. Alandowner may purchase a ranch for economicreasons, such as to provide a source of incomeor as an investment. Ownership could be fornoneconomic motives, such as obtaining rec-reation benefits or to provide a good environ-ment in which to raise a family. If the reasonsfor owning a ranch are economic, wildlife tol-erance should decrease and damage claim be-havior increase. The opposite relationship ishypothesized if the ranch is purchased for non-economic reasons.

Wildll~e Species and Level of Damage

Preference for certain species and the type ofdamage created by a particular species mayaffect individual attitudes toward big and tro-phy game depredation. Previous studies showthat human preferences toward wildlife varywith each species (Kellert; More). Wildlifesentiment is generally directed at species thathave prominent anthropomorphic qualities(Killert) and are relatively less abundant(More). Certain big game, such as elk, candamage fences and consume more forage be-cause of their size. Elk are often viewed asintruders because they are more nomadic anddo not continually reside on a landowner’sproperty. It is hypothesized that tolerance willdecrease and landowners will be more likelyto submit damage claims when depredation iscaused by elk rather than by deer, antelope ormore novel species such as moose. Thereshould also be a negative relationship betweentolerance and damage caused by trophy game.


Previous studies show that tolerance de-creased as the perceived amount of damage orseverity of damage increased (Brown, Deckerand Huston; Decker and Brown; Stoll andMountz). In this study, the perceived amountof damage is hypothesized to have a negativerelationship with landowner tolerance of wild-life and a positive relationship with damageclaim submissions.

Attitudes

Two attitudinal variables are included to test

how landowners’ attitudes influence their tol-

erance towards wildlife and their damage

claim behavior. First, landowners who feel a

moral obligation to care for big game should

have increased tolerance levels and be less

likely to submit damage claims. Second, eco-

nomic disincentives ensuing from the “general

inconvenience” of big game should decrease

landowner tolerance and increase damage

claim submissions. General inconveniences

may include demands associated with hunters

or recreationists, the possibility of disease be-

ing transmitted from wildlife, or the inconve-

nience of using preventative measures to re-

duce big game damage.

Data

A split sample designed mail survey was con-ducted during 1995 to obtain ranchers’ per-spectives concerning depredation. The surveypopulation consisted of 505 individuals whohad submitted damage claims to the WGFDduring the previous five years and 2913 Wy-oming Farm Bureau Association members en-gaged in agriculture. From these two popula-tions, a sample of 300 individuals who hadsubmitted damage claims and 300 individualswho had not submitted damage claims wasdrawn. Of those who had submitted damageclaims, 133 were Farm Bureau members. Sta-tistical tests were conducted to examine thedifference between non-Farm Bureau mem-bers and Farm Bureau members. Chi-square(xz) tests were used to examine differences be-tween categorical variables, while paired t-

tests were used for continuous variables. No

significant differences were detected betweenFarm Bureau members and non-Farm Bureaumembers or Farm Bureau claimants and non-Farm Bureau claimants at the 0.05 level for alldescriptive variables.

Identical questionnaires were sent to all in-dividuals in the sample. A reminder postcardwas sent two weeks after the initial mailing.If the returned questionnaire was not receivedafter three weeks, a second survey was sent.A response rate of 59 percent was obtained,including 182 respondents who had submitteddamage claims and 170 who had not submit-ted damage claims. Of those submitting dam-age claims, 90 were Farm Bureau membersand 92 were not.

Results and Discussion

The majority of respondents permanently re-

sided on the ranch (89 percent) and obtained

their main income from ranching (76 percent).

Average management experience was 25

years. Most respondents had a high school ed-

ucation or more. Over half had received some

education above the high school level and 12

percent had graduate or professional training.

Respondents were asked to rate the finan-

cial stress they were currently experiencing in

their ranching operation. Slightly over half of

the respondents described their financial stress

as “average”, whereas 23 percent indicated

they were experiencing “above average” fi-

nancial stress.

When asked to indicate their reasons for

keeping or purchasing their ranch, 73 percent

of respondents stated they did so to provide a

source of income or as an investment. Outdoor

recreation benefits appear to be subsidiary to

economic benefits for most respondents, as 28

percent ranked recreation as a major reason,

and 36 percent ranked life style as an argu-

ment for purchasing or maintaining ownership

of their ranch.

The typical ranching operation had 402

acres of hay, 178 acres of crops, 5912 acres

of rangeland, and 866 federal animal unit

months (AUMS). For livestock, an average of

231 head of mother cows, 154 head of year-

lings and 250 head of ewes existed in the sam-

Van Tassell, Yang, and Phillips: Depredation Claims and Wildl@e Tolerance 181

Table 1. Damage Losses ($) and Maximum Tolerable Losses ($) by Big and Trophy GameSpecies Reported by Respondents, by Type of Loss

Mean S.D. Min Max

Fence damage 304 489 0 4,000Stacked hay loss 331 1,287 0 20,000Standing forage crop loss 1,279 5,323 0 54,000Grain crop loss 223 1,273 0 17,500Loss of rangeland forage 1,234 5,138 0 72,000Other 565 4,483 0 75,000Total without range forage loss 2,769 7,259 0 75,100Total with range forage loss 4,044 10,000 0 95,000Amount of damage respondent would tolerate before

submitting a damage claim 1,422 2,427 0 20,000

pie. Almost 44 percent of respondents wereinvolved in farming crops other than hay, andover 76 percent were involved in some typeof livestock enterprise. Approximately 34 per-cent of respondents had some combination ofcrop (other than hay) and livestock enterprises.Average value of the forage base was

$830,539 with a standard deviation of$1,015,514.

Ranking Damage Sources by Wildlife Species

Respondents were asked to rank species thatcaused the most damage to their deeded lands.Mule deer (68 percent), antelope (54 percent),elk (35 percent) and white-tailed deer (34 per-cent) were the species most frequently citedby respondents as the major perpetrators ofdamage. Trophy species were mentioned by 10percent of respondents and “other” speciessuch as moose and waterfowl were also listedby 10 percent of respondents as originators ofdepredation. Survey results mirrored the ex-perience of the WGFD. According to WGFDrecords from 1970 to 1989, the majority ofdepredation submissions were due to largeherbivores, Mule deer were involved in 37percent of all damage claims and were moreoften cited in claims than any other species.Elk were linked with 26 percent of damageclaims, though the average value of an indi-vidual elk claim was smaller than for deer orantelope. Antelope were involved in almost 15percent of claims and white-tailed deer wereinvolved in 10 percent.

Depredation Magnitudes

Respondents were asked to assess the averageamount of damage per year that big game an-imals caused to their property (Table 1).Standing crop forage incurred the greatestamount of damage ($1279), followed closelyby rangeland forage ($1234). Current regula-tions do not allow the WGFD to compensatefor forage Ioss on private rangelands unlessthe damage meets the standard of ‘ ‘extraordi-naryy damage to grass” as defined by Wyo-ming Game and Fish Commission regulations.Based on the 1995 average rate for grazingcattle on private, non-irrigated land in Wyo-ming of $11.30 per AUM (Wyoming Agricul-tural Statistics Service), rangeland forage “dep-redation loss reduced the average cow herdsize by 109 AUMS or approximately ninecows. Fence damage, grain crop losses andstacked hay loss were considerable lower thanstanding forage loss in hay field or on range-Iands. Other types of damage listed by re-spondents averaged $565 per operation and in-cluded tree, vegetable, silage, seed, salt andbuilding damage, along with human injuries.Total damage averaged $4,044 per operationincluding rangeland forage losses and $2,769when these losses were excluded. Lacey et al.

sampled seven southwestern Montana countiesduring 1989–1990 and found that consump-tion and damage to forage crops by big game,along with damage to stored hay and fences,amounted to $6185 per rancher, almost one-third more than found in this sample.

182 Journal of Agricultural and Applied Economics, Apri12000

Respondents were asked to state theamount of wildlife damage they would incurbefore submitting a damage claim. The aver-age maximum tolerance of wildlife damagewas $1422, making the average reported dam-age almost two-fold the respondents’ tolerancelevel. When arranged according to respon-dents who had submitted damage claims andthose who had not, the average difference be-tween reported damage and the amount theywould tolerate before submitting a damageclaim was $1558 for respondents who hadsubmitted damage claims. For respondentswho had not submitted a damage claim, theamount they would tolerate before submittinga damage claim exceeded the reported damageby $523. Apparently, most landowners whosereported damage exceeded their tolerance lev-el were getting some consolation from theWGFD.

Tolerance Towards Wildl#e

Almost 95 percent of respondents reportedthat game or trophy wildlife species used theirprivate land. Respondents who had wildlifeusing their land were asked whether they con-sidered the use of their private lands by biggame or trophy wildlife species to be tolerableor intolerable based on their previous fiveyears of experience. Fifty-seven percent of re-spondents considered game use of their privatelands tolerable. A list of predefine explana-tions of why game and trophy wildlife use oftheir property was tolerable was included onthe questionnaire. Respondents were permittedto check more than one category. The majority(60 percent) of respondents who were tolerantof game animals believed that the presence ofwildlife on private property was part of naturethat comes with owning land. Thirty-nine per-cent gave benefits of hunting as a reason totolerate big game and trophy wildlife species.A similar percentage (38 percent) of privatelandowners considered the visual and aestheticvalue worth more than the costs big game andtrophy wildlife species impose. Nearly 18 per-cent of respondents indicated their tolerancewas linked to guiding and outfitting servicesthey provided and 14 percent tolerated big

game because of light and infrequent use.Twenty-six respondents made additional com-ments explaining their tolerance for wildlife.“Just tolerate” was the most common com-ment. Other comments in descending order offrequency were “Wyoming Game and FishDepartment pays damage”, “ wouldn’t ownland without wildlife”, “environmentalists”and “protection of private lands keeps animalsfrom extinction”.

Table 2 contains results from the probitequation used to analyze factors influencinglandowner tolerance of wildlife. The modelcorrectly classified 79 percent of respondentsin the sample. Eight variables were significantin segmenting the respondents.

Several economic factors were significantin classifying respondents as to their wildlifetolerance. Respondents with severe financialstress (STRESS 1) were less likely to indicatewildlife use on their private lands was tolera-ble. Marginal effects indicate the probabilityof big game use being tolerable was reducedby 34 percent if a landowner fell into the se-vere financial stress group. The reported dam-age occurring to crops and fences (DAMAGE)was not significant in determining if wildlifeuse was tolerable, but the general inconve-nience of wildlife (INCONVEN) was signifi-cant. The probability of big game use beingtolerable was reduced by 47 percent if the re-spondent felt their income was adversely af-fected by the “general inconvenience” of biggame. Perhaps this result occurs because theWGFD will compensate landowners for mostcategories comprising DAMAGE, but not forthe general inconvenience of wildlife. If thisis true, the damage claim submission processis at least partially successful in increasinglandowner tolerance of wildlife.

Management characteristics also were im-portant factors in determining if wildlife usewas tolerable. If the ranch was purchased orretained as a source of income or as an in-vestment, the landowner was more reluctant totolerate the presence of wildlife. If recreationalpurposes were a major factor in maintainingthe ranch, wildlife use was more tolerable.Purchasing or retaining farmsh-anches for eco-nomic reasons reduced the probability of tol-

Van Tassell, Yang, and Phillips: Depredation Claims and Wildl#e Tolerance 183

Table 2. Maximum Likelihood Estimates for the Probit Model Used to Analyze Factors In-fluencing Landowner Tolerance of Wlldlifea

Independent Estimated Change inVariableh Coefficient StandardError ProbabilityC,~ StandardError

INTERCEPTEXPERIENCEED/COLLEGEED/GRADUATERESIDENCEINC/SOURCESTRESS 1STRESS2STRESS4STRESS5SIZEPUR/ECONPURRECPUR/LIFEELKMULEDEERWHITEDEERANTELOPETROPHYOTHERDAMAGEMORALINCONVEN

1.321*–0.005–0.352–0.155–0.070

0.232–0.883”–0.338–0.133

0.247–0.00003–0.741**

0.564*0,305

–0.570**–0,367

0.498”0.2430.942*0.239

–0.0480.638**

–1.229***

0.71020.50000.01000.46970.41180.34120.50750.29910.44330.58810.000130.03180.33980.26990.26640.30330.27820.25310.52330.31450.09020.25730.2713

0.508*

–0.002–0.135–0.059–0.027

0.089–0.340*–0.130–0.051

0.095–0.00001–0.285**

0.217*0.117

–0.219**–0.141

0.192*0.0940.363*0.092

–0.0180.246”*

–0.473***

0.2702

0.00400.11540.17880.15880,13090.19650.11400,17000.22620.000040.12230.13070.10350.10280,11650.10730.09790.20060.12110.01490.10000.1019

“Total number of observations = 177; X2with 22 degrees of freedom = 82.85; Pseudo R2 = 0.62; correct predic-tions= 74%.hEXPERIENCE = number of years landowner had been managing a farm/ranch; ED/COLLEGE = 1 if educationlevel of landowner was past high school graduate, but no graduate work; O otherwise; ED/GRADUATE ==1 it’ edu-

cation level of landowner was beyond a 4-year college degree; O otherwise; RESIDENCE = 1 if landowner resides

on the ranch; O otherwise; INC/SOURCE = 1 if landowner resides on the ranch; O otherwise; STRESS 1 = 1 iflandowner ranked financial stress severe; Ootherwise; STRESS2 = 1 if landowner ranked financial stress aboveaverage; O otherwise; STRESS3 = 1 if landowner ranked financial stress average; O otherwise (omitted from theequation to avoid singularity); STRESS4 = 1 if landowner ranked financial stress SIight; O otherwise; STRESS5 = 1if landowner ranked financial stress insignificant/none; O otherwise; SIZE = Value ($1,000) of total forage base;PUR/ECON = 1 if a major reason for purchasing the ranch was economic; O otherwise; PUR/LIFE = 1 if a major

reason for purchasing the ranch was for the way of life; O otherwise; ELK = 1 if elk were one of the top 3 species

causing damage; O otherwise; MULEDEER = 1 if mule deer were one of the top 3 species causing damage; O

otherwise; WHITEDEER = 1 if whitetail deer were one of the top 3 species causing damage; O otherwise; ANTE-LOPE = 1 if antelope were one of tbe 3 species causing damage; O otherwise; TROPHY = I if trophy animalswere one of the top 3 species causing damage; O otherwise; OTHER = 1 if other animals were one of the top 3species causing damage; O otherwise; DAMAGE = Average value ($1,000) of damage caused by big game per year(excluding rangeland forage); MORAL = 1 if landowner felt a moral obligation to care for big game; O otherwise;

INCONVEN = 1 if landowner felt their income was adversely affected by the “general inconvenience” of big

game; O otherwise.L*, **, and **:~, indicate significance levels at a = O. IO, 0.05 and 0.01, respectively.

[iCalculated at mean values of the independent variables. For dummy variables, the change in probability is calculat-

ed as the variable takes on its two values (O, 1).

erable big game use by 29 percent, while pur- tinue, wildlife depredation should become lesschasing for recreational purposes increased the of a concern for WGFD officials. Antitheti-probability by 22 percent. If trends in pur- cally, increased land prices stemming from the

chasing ranches for recreational purposes con- increased demand for ranches in Wyoming


will make economic survivability an even

more important factor to career ranchers en-

tering ranching.

Tolerance of wildlife was associated with

the respondent feeling a moral obligation to

care for big game. When a landowner felt this

moral obligation, the probability of big game

use being tolerable increased by 25 percent.

This moral consciousness concerning the bal-

ance of nature and the landowner’s role in that

balance appears to be an important factor in

defining the tolerance of landowners towards

wildlife. Comparison of the change in proba-

bility between MORAL and some of the eco-

nomic variables suggests, though, that a moral

obligation to care for wildlife may be subsid-

iary to the landowners economic dependency

on the land as suggested by Craven et al.

Results indicated that tolerance towardwildlife depredation was species specific.Damage initiated by elk was less tolerablethan other species and decreased the probabil-ity of the damage being tolerable by 22 per-cent. The presence of white-tailed deer, con-trarily, increased the probability by 20 percentof the landowner stating that damage was tol-erable. WGFD statistics denote the averagevalue of an individual elk claim is smaller thandeer or antelope claims, indicating that thelandowners’ lack of tolerance for elk is dis-tinctive and not necessarily associated with theamount of damage being created. Deer, partic-ularly white-tailed, are more apt to forageclose to the farmstead and have an aestheticvalue. The aesthetic value of deer may also berelated to their being targets of anthropomor-phism.

The positive sign accompanying the coef-ficient for TROPHY was different than hy-pothesized. While landowners were originallythought to be less tolerant to damage perpe-trated by mountain lions or bear, fair depre-dation settlements may partially account forthe tolerance of landowners toward trophygame. According to WGFD statistics, 96 per-cent of claims for mountain lions are relatedto depredation on domestic sheep and are con-fined geographically. Although some livestockdepredation is difficult to substantiate, theWGFD has attempted to be extraordinarily fair

in these settlements. The WGFD has recog-nized the rancher’s inability to document alllivestock depredation claims and has at timesdesignated special compensation areas for liondamage to livestock (Iverson). Depredationsettlements in these special compensation ar-eas have been based on a formula where therancher is reimbursed for confirmed kills plusa percent of all missing ewes and lambs. Thus,relatively liberal depredation settlements maypartially account for the landowners’ toleranceof trophy game.

Damage Claims Submissions

Over half the respondents (54 percent) had

submitted wildlife damage claims during the

last five years based on the WGFD wildlife

damage submission list. Respondents whosubmitted claims were asked how many

claims they had submitted over the previous

five years, how many claims were accepted,

how many were rejected and reasons for re-

jections. One-hundred and six respondents

said they submitted a total of 237 damage

claims over the previous five years, an average

of 2.24 claims per submittent, Maximum dam-

age claims submitted by a single landowner

was 10, while the majority (67 percent) had

only submitted one or two damage claims.

Two hundred and seven damage claims sub-

mitted by 95 respondents were accepted, an

average of 2.18 claims per submittent. Of

those who had submitted damage claims, 68

percent had at least one claim accepted and 25

percent had at least one rejected.

Respondents who had borne intolerable

wildlife damage but had not submitted damage

claims were questioned why they had not sub-

mitted damage claims, Almost 64 percent of

the respondents said the submission process

was more trouble than it was worth. Six per-

cent said they were not eligible because dam-

age was less than the $100 minimum, while

three percent were ineligible because they did

not allow hunting on their private land. None

of the respondents were ineligible because

they failed to meet the submission deadline,

Almost one-half of nonclaimants offered com-

ments or gave other reasons for not submitting

Van Tassell, Yang, and Phillips: Depredation Claims and Wildlife Tolerance 185

claims. Lack of knowledge concerning dam-age claim procedures or policies, “too hard toprove”, and “ WGFD does not pay for stand-ing rangeland forage depredation” were themajor reasons for not submitting claims.

Four descriptive variables were significantin classifying respondents as to who had orhad not submitted damage claims to theWGFD (Table 3). The estimated probit modelcorrectly classified 74 percent of respondentsin the sample.

Respondents with at least some graduatetraining beyond their college degree were 29percent less likely to submit damage claims.Landowners with higher education levels havegenerally been found to foster a positive ori-entation to wildlife presence (Adams, Ne-wgard and Thomas; Kellert).

Landowners’ lack of tolerance toward elkwas again manifest in their tendency to submitdamage claims for elk depredation. If elk wereinvolved in the depredation, there was a 25-percent higher probability that a damage claimwould be submitted.

The economic stress the respondent wasexperiencing was not a significant factor influ-encing submission of damage claims. Theamount of damage incurred and the “generalinconvenience” experienced were significantindicators. Each $1000 of reported damage in-creased the probability of a damage claim be-ing submitted by 3.4 percent and if the land-owner felt his or her income was adverselyaffected by the “general inconvenience” ofbig game, the probability of submitting a dam-age claim was increased by 27 percent. Be-cause the WGFD does not pay depredationclaims on the “general inconvenience” creat-ed by wildlife, results indicate damage claimsubmissions may be affected by the generalannoyance associated with the presence of biggame.

If respondents felt a moral obligation as alandowner to care for big game, results haveshown they were generally more tolerant ofwildlife depredation. Moral obligation,though, did not significantly alter the proba-bility that a damage claim would be submittedto compensate the landowner for the damagecaused by wildlife. Additionally, reasons why

the landowner purchased the ranch did not sig-nificantly influence the submission of damageclaims. Neither were damage claim submis-sions associated with the size of the ranchwhere the damage was occurring.

Summary and Implications

Maintaining or increasing the supply of wild-

life has been a motivation behind depredation

payments made by state wildlife agencies.

With the encroachment of residential areas

onto big game winter range and increased de-

mand for big game species, deeded agricultur-

al land is a key component in maintaining free

roaming, publicly owned wildlife herds. With

landowner tolerance being a major factor in-

fluencing the expanse of wildlife habitat, aug-

menting that tolerance is a major interest of

state wildlife agencies.

Results showed that slightly over half of

the ranchers/farmers surveyed in Wyoming

felt wildlife depredation on their property was

tolerable, The financial stability and economic

purpose of the agriculture enterprise signifi-cantly influenced this tolerance. While indi-viduals maintaining agricultural operations forrecreation purposes may be more tolerant ofwildlife depredation, their intents may not al-ways coincide with WGFD management ob-jectives. For example, one of the few wildlifepopulation management tools available to theWGFD is the ability to control the number ofhunting licenses authorized in a particulararea. If landowners do not allow hunting ac-cess, the harvest desired by WGFD may notbe accomplished. This particularly compoundsthe depredation problem when wildlife moveonto another landowner’s property after thehunting season. Licensing programs that en-courage a more uniform harvest (e.g., har-vesting overpopulated females), especially forout-of-state hunters typically in search of tro-phy animals, can assist in meeting populationobjectives.

Because of the relationship found betweentolerance and the economic status or intent ofthe rancher, policies that financially rewardlandowners for succoring big game should beeffective in maintaining or increasing wildlife


Table 3. Maximum Likelihood Estimates for the Probit Model Used to Analyze Factors In-fluencing Damage Claim Submission

IndependentVariable

EstimatedCoefficient

StandardError

INTERCEPTEXPERIENCEED/COLLEGEED/GRADUATERESIDENCEINC/SOURCESTRESS1STRESS2STRESS4STRESS5SIZEPUFVECONPUR/RECPUR/LIFEELKMULEDEERWHITEDEERANTELOPETROPHYOTHERDAMAGEMORALINCONVEN

–1.088*0.007

–0.208–0.733*

0.065–0.162

0.2630.2180.133

–0.2430.00010.384

–0.158–0.1050.627**0.179–0.3540.0430.2170.2120.082*0.0880.699***

0.60780.00870.27010.41640.38230.30570.49620.27250.41560.44180.00010.28030.29810.24420.25080.26320.24580.22630.41730.28650.04970.24440.2479

Change inProbabilityC

–0.426*0.003

–0.081–0.287”

0.025–0.064

o.1030.0850.052

–0.0950.000050.151

–0.062–0.041

0.246**0.070

–0.1390.0170.0850.0830.032*0.0350.274***

StandardError

0.24070.00370.10660.16400.14710.12080.19430.10620.16250.17270.000050.11100.11700.09530.09880.10290.09650.08950.16340.11070.01900.09720.0982

‘ Total number of observations = 177; X2 with 22 degrees of freedom = 53.57; Pseudo Rz = 0.62; correct predic-

tions= 74’%0.

b EXPERIENCE = number of years lando wrier had been managing a farm/ranch; ED/COLLEGE = 1 if education

level of landowner was past high school graduate, but no graduate work; O otherwise. ED/GRADUATE = 1 if edu-

cation level of landowner was beyond a 4-year college degree; O otherwise; RESIDENCE = 1 if landowner resides

on the ranch; O olherwise; lNC/SOURCE = 1 if landowner resides on the ranch; O otherwise; STRESS 1 = 1 it’

landowner ranked financial stress severe; O otherwise; STRESS2 = I if landowner ranked financial slress above

average; O otherwise; STRESS3 = 1 it’ landowner ranked financial stress average, O otherwise (omitted from the

equation to avoid singularity); STRESS4 = 1 ]f landowner ranked financial stress shgbt; O otherwise; STRESS5 = 1

if landowner ranked financial stress insignificanthone; O otherwise; SIZE = Value ($ 1,000) of total forage base,

PUR/ECON = 1 if a major reason for purchasing the ranch was economic; O otherwise, PUR/LIFE = 1 if a major

reason for purchasing tbe ranch was for the way of life; O otherwise; ELK = 1 if elk were one of the top 3 spccles

causing damage; O otherwise; MULEDEER = I ]f mule deer were one of the top 3 species causing damage; Ootherwise; WHITEDEER = 1 if whitetail deer were one of the top 3 species causing damage; O otherwise; ANTE-

LOPE = 1 if antelope were one of the 3 species causing damage; O otherwise; TROPHY = 1 d’ trophy animats

were one of the top 3 species causing damage; O otherwise; OTHER = 1 tf other animals were one of the top 3

species causing damage; O otherwise; DAMAGE = Average value ($ 1,000) of damage caused by big game per year

(excluding rangeland forage); MORAL = 1 if landowner felt a moral obligation to care for big game; O otherw]se;

INCONVEN = 1 if landowner felt their income was adversely affected by tbc ‘Jgcneral inconvenience” of big

game; O otherwise.. x, **, and ***, indicate significance levels at a = O. 10, 0.05 and 0.01, resPcctlveIY

11Calculated at mean values of the independent variables. For dummy variables, tbe change in probability is calcLllat-

ed as the variable takes on Its two values (O, 1).

tolerance. Several policies aimed at accom- licenses within a hunt area to patrons huntingplishing this task have been proposed over the on their land or land that is accessed throughpast decade. One suggested policy is to allow their property. This policy has proven to belandowners to market a portion of big game effective in increasing landowner tolerance to-

Van Tassell, Yang, and Phillips: Depredation Claims and Wildlife Tolerance 187

ward wildlife and enlisting landowners in in-creasing the supply of big game (Dagget). Byrequiring landowner to participate in this pro-gram to provide hunting access to a specifiednumber of general license hunters, land accessproblems also may be reduced. However, anadvisory team established in December 1995was unable to reach a consensus on any suchrecommendation. They surmised that “anyproposal to reallocate licenses . . . will notmeet the task force’s own criteria of fairnessand acceptability to the Wyoming public”(Rea and Winner, p. E2). Further examinationof this alternative is recommended as it pro-vides entrepreneurial opportunities to rancherswhile encouraging a more active role in themanagement of wildlife.

Elk were found to be at the heart of thewildlife tolerance and damage claim submis-sion controversy. Elk contributed to decreasedlandowner tolerance and increased damageclaim submissions. Wyoming elk numbershave grown from 23,000 in 1923 to 102,439in 1995 (Wyoming Game and Fish Depart-ment, 1995). While elk were shown to be themost unpopular big game species among Wy-oming landowners, they are popular amonghunters. Developing equilibrium between sup-ply (landowner tolerance) and demand for elkwill probably necessitate a more thoroughlandowner compensation system such as thereallocation of licenses previously discussed.The WGFD has tried to curb elk depredationby purchasing several private properties foruse as wintering grounds. This is a controver-sial practice because many opponents feel ittakes land out of productive use and decreasesthe economic activity and tax base of the localeconomy.

Results showed that the complexity of thesubmission process was a deterrent to manyrespondents who were experiencing wildlifedepredation but had not submitted a damageclaim. Educational or training seminars maybe beneficial if the intent of the WGFD is tofurther improve landowner tolerance of wild-life through depredation payments.

Few factors other than the degree of dam-age itself were significant in categorizing re-spondents as to whether they had submitted

damage claims. This indicated that alternativemotives, other that the dislike of elk depre-dation, generally did not influence damageclaim submissions. For example, the damageclaim policy apparently was not abused bylandowners experiencing financial difficulty,not by those not residing in Wyoming, and notby those with varying motives for purchasingtheir property.

The issues of wildlife tolerance and privatelandowner compensation will not quickly dis-appear. In fact, as one of the members of the1995 WGFD advisory team recently observed,the relationships between sportsmen, landown-ers and the WGFD may be at “an all-timelow” (Rea and Winner, p. E2). While theWGFD depredation program has done muchto increase the supply of wildlife in Wyoming,new avenues still need to be explored.

References

Adams, C., E. Newgard, and J. K. Thomas. “HowHigh School and College Students Feel AboutWildlife.” American Biology Teacher 48(1986):263–267 .

Amemiya, T. “Qualitative Response Models: ASurvey. ” Journal of Economic Literature19(1981):1483–1536.

Bastian, C., T. Foulke, and J.l? Hewlett. “WyomingFarm and Ranch Land Market: 1990–1992.”Agr. Exp, Bull. B-999, Univ. of Wyoming,1994.

Belsley, D.A. Conditioning Diagnostics: Collinear-

ity and Weak Data in Regression. New York:John Wiley and Sons, Inc., 1991.

Brown, T. L., D. J. Decker, and D. L. Huston.“Farmers’ Tolerance of White-tailed Deer inCentral and Western New York. ” Agr. Exp. Sta.Rep. No. 7, Cornell Univ., 1980.

Conover, M.R. “Perceptions of Grass-Roots Lead-ers of the Agricultural Community About Wild-life Damage on Their Farms and Ranches. ”Wildlcfe Society Bulletin 22,1( 1994):94–99.

Craven, S.R., D.J. Decker, W.l? Siemer, and S.E.Hygnstrom. “Survey Use and Landowner Tol-erance in Wildlife Damage Management. ”Transactions of the North American Wildl#e

and Natural Resource Conference. 49( 1992):75–88.

Dagget, D. Beyond the Rangeland Conjiict: Toward

a West that Works. Layton, UT. Gibbs SmithPublishers, 1995.

188 Journal of Agricultural and Applied Economics, Apri12000

Davis, R. K., E.G. Parsons, and R.M. Randall.“Role of Access Fees in Managing WildlifeHabitat in the Federal Lands. ” Transactions of

the North American Wildhfe and Natural Re-source Conference 52(1987):544–5 1.

Decker, D. J., and T. L. Brown. “Fruit Growers’ vs.Farmers’ Attitudes Toward Deer in New York. ”Wildhfe Society Bulletin 10,2(1982): 150–55.

Ervin, C.A., and D.E. Ervin. “Factors Affecting theUse of Soil Conservation Practices: Hypotheses,Evidence, and Policy Implications. ” Land Eco-nomics 58(1982):277–92.

Greene, W.H. LIMDEP (LIMited DEPendent)User’s Manual. Bellport. New York: Econo-metric Software, Inc., 1989.

Greene, W.H. Econometric Analysis. New York:MacMillan Publishing Company, 1993.

Hackett, E, “Involving Hunting and Trapping inCooperative Wildlife Damage Control. ” Pro-

ceedings of the Eastern Wildll~e Damage Con-

trol Conference 3(1987):309.Iverson, R. “Trophy Game Animal Damage in Wy-

oming. ” Great Plains Wildl&e Damage ControlWorkshop Proceedings 9(1 989):34–39.

Kellert, S.R. “Americans’ Attitudes and Knowl-edge of Animals. ” Transactions of the North

American Wildlife and Natural Resource Con-

ference 41(1980): 111-24.Korsching, E?F., C.W. Stofferahn, P.J. Nowak, and

D. Wagener. “Adoption Characteristics andAdoption Patterns of Minimum Tillage: Impli-cations for Soil Conservation Pro grams.” Jour-nal of Soil and Water Conservation 38(1983):

285–88.Kruckenberg, L.L. “An Overview of Wildlife Pri-

vatization and Access in Wyoming. ” In Pro-

ceedings of the Privatization of Wildllfe and

Public Lands Access Symposium, pp. 3–19. Cas-per, WY Wyoming Game and Fish Department,1987.

Lacey, J.R., K. Jamtgaard, L, Riggle, and T. Hayes.“Impacts of Big Game on Private Land inSouth-western Montana: Landowner Percep-tions. ” Journal of Range Management

46(1993):31–37.

McFadden, D, “The Measurement of Urban De-mand. ” Journal Public Economics 3(1974):

308–28.McNamara, K.T., M.E. Wetzstein, and G.K. Deuce.

“Factors Affecting Peanut Producer Adoptionof Integrated Pest Management. ” Review of Ag-

ricultural Economics 13, 1(199 1): 129–39.More, T. A. “Wildlife Preferences and Children’s

Books.” Wildl~e Society Bulletin 7(1979) :274–78.

Rea, T., and C. Winner. “Legislative CommitteeGets Update on Wildlife Task Force. ” Casper

Star Tribune (Aug. 15, 1996) :E1–2.Stoll, R.J. Jr., and G.L. Mountz. Rural Lundowner

Attitudes Toward Deer and Deer Population inOhio. Ohio Fish and Wildlife Report 10, 1983.

Van Tassell, L. W,, C. Phillips, and W.G. Hepworth.“Livestock to Wildlife is not a Simple Conver-sion. ” Rangelands 17,6(1995): 191–93.

Wyoming Agricultural Statistics Service. 1996 Wy-

oming Agricultural Statistics. United States De-partment of Agriculture. Cheyenne, Wyoming.1996,

Wyoming Game and Fish Department, LAWS-Re-

vised and Updated to Include Changes and Re-visions Made as a Result of the 1991 and 1992

Legislative Sessions. 1993.Wyoming Game and Fish Department. Annual Re-

port. 1995.

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