0596-0078 NWOS Supporting Statement B

The Supporting Statement B for OMB # 0596-0078
National Woodland Owner Survey

Note: This request is for renewal of the previously approved information collection OMB 0596-0078, the National Woodland Owner Survey (NWOS). The USDA Forest Service has completed the assessment in accordance with the Paperwork Reduction Act of 1995 and requests approval from OMB to continue the collection of information from the owners and managers of forestland across the United States.

B. Collections of Information Employing Statistical Methods

1. Describe (including a numerical estimate) the potential respondent universe and any sampling or other respondent selection method to be used. Data on the number of entities (e.g., establishments, State and local government units, households, or persons) in the universe covered by the collection and in the corresponding sample are to be provided in tabular form for the universe as a whole and for each of the strata in the proposed sample. Indicate expected response rates for the collection as a whole. If the collection had been conducted previously, include the actual response rate achieved during the last collection.

Respondent Universe: Based on the previous iteration of the NWOS, there are an estimated 11.5 million private ownerships of forestland in rural areas of the United States. The number of state and local government agencies managing forestland is unknown and determining this number is one of the objectives of this information collection. The number of owners and managers of trees in urban areas is also unknown, and also a question being addressed by this information collection.

Sampling: The sample is stratified by broad ownership category, by rural versus urban, and by state. The three ownership categories are large corporate private, other private, and non-federal public. Large corporate is defined as ownerships that are corporations and have at least 45,000 acres of forestland in the U.S. The area of land covered by trees is used to stratify rural (greater than or equal to 1 acre) versus urban (at least one tree, but less than 1 acre).

The target sample size for the rural small private owners is 250 respondents per state over a five year sampling period as determined in USDA Forest Service, National Woodland Owner Survey 2011-2013: Design, Implementation, and Estimation Methods (USDA Forest Service Gen. Tech. Rep. 2016) (https://www.fs.usda.gov/treesearch/pubs/50675). For large rural, the goal is to contact all of them per state. It is also our intention to contact all state agencies that manage rural forestland and up to 1,800 local agencies. The target sample size for private owners in urban areas is 100 per metropolitan area. There are currently no plans to contact public agencies in urban areas, but this could potentially be addressed in future collection efforts.

Table B-1: Estimated numbers of ownerships/managers and target numbers of responses for this three-year OMB approval (listed parenthetically) for the National Woodland Owner Survey by rural-urban, ownership category, and state strata.

	Rural
	Private			Public		Urban
State	Large corporate	Other private		Public, non-federal		Private	Public
Alabama	42	248,000		Unknown		Unknown	Unknown
	(25)	(150)		(30)		(0)	(0)
Alaska	1	36,000		Unknown		Unknown	Unknown
	(1)	(150)		(30)		(0)	(0)
Arizona	0	95,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(0)	(0)
Arkansas	30	217,000		Unknown		Unknown	Unknown
	(18)	(150)		(30)		(0)	(0)
California	16	248,000		Unknown		Unknown	Unknown
	(10)	(150)		(30)		(60)	(0)
Colorado	6	34,000		Unknown		Unknown	Unknown
	(4)	(150)		(30)		(120)	(0)
Connecticut	0	166,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(0)	(0)
Delaware	0	22,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
Florida	31	227,000		Unknown		Unknown	Unknown
	(19)	(150)		(30)		(0)	(0)
Georgia	33	462,000		Unknown		Unknown	Unknown
	(20)	(150)		(30)		(0)	(0)
Hawaii	0	88,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(0)	(0)
Idaho	0	28,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(0)	(0)
Illinois	0	149,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
Indiana	1	193,000		Unknown		Unknown	Unknown
	(1)	(150)		(30)		(0)	(0)
Iowa	0	80,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
Kansas	0	95,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
Kentucky	6	422,000		Unknown		Unknown	Unknown
	(4)	(150)		(30)		(0)	(0)
Louisiana	25	135,000		Unknown		Unknown	Unknown
	(15)	(150)		(30)		(0)	(0)
Maine	52	170,000		Unknown		Unknown	Unknown
	(31)	(150)		(30)		(60)	(0)
Maryland	1	149,000		Unknown		Unknown	Unknown
	(1)	(150)		(30)		(60)	(0)
Massachusetts	1	235,000		Unknown		Unknown	Unknown
	(1)	(150)		(30)		(0)	(0)
Michigan	8	375,000		Unknown		Unknown	Unknown
	(5)	(150)		(30)		(60)	(0)
Minnesota	5	213,000		Unknown		Unknown	Unknown
	(3)	(150)		(30)		(60)	(0)
Mississippi	19	284,000		Unknown		Unknown	Unknown
	(11)	(150)		(30)		(0)	(0)
Missouri	2	440,000		Unknown		Unknown	Unknown
	(1)	(150)		(30)		(180)	(0)
Montana	30	72,000		Unknown		Unknown	Unknown
	(18)	(150)		(30)		(0)	(0)
Nebraska	0	41,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
Nevada	0	5,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(0)	(0)
New Hampshire	5	196,000		Unknown		Unknown	Unknown
	(3)	(150)		(30)		(0)	(0)
New Jersey	0	124,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
New Mexico	5	449,000		Unknown		Unknown	Unknown
	(3)	(150)		(30)		(0)	(0)
New York	8	782,000		Unknown		Unknown	Unknown
	(5)	(150)		(30)		(60)	(0)
North Carolina	23	566,000		Unknown		Unknown	Unknown
	(14)	(150)		(30)		(0)	(0)
North Dakota	0	26,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
Ohio	2	486,000		Unknown		Unknown	Unknown
	(1)	(150)		(30)		(60)	(0)
Oklahoma*
East	6	89,000		Unknown		Unknown	Unknown
	(4)	(150)		(30)		(0)	(0)
West	13	173,000		Unknown		Unknown	Unknown
	(8)	(150)		(30)		(0)	(0)
Oregon	29	172,000		Unknown		Unknown	Unknown
	(17)	(150)		(30)		(60)	(0)
Pennsylvania	11	574,000		Unknown		Unknown	Unknown
	(7)	(150)		(30)		(120)	(0)
Rhode Island	0	46,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
South Carolina	22	212,000		Unknown		Unknown	Unknown
	(13)	(150)		(30)		(0)	(0)
South Dakota	0	17,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(0)	(0)
Tennessee	0	421,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(0)	(0)
Texas*
East	27	130,000		Unknown		Unknown	Unknown
	(16)	(150)		(30)		(120)	(0)
West	0	482,000		Unknown		Unknown	Unknown
	(0)	(150)		(30)		(60)	(0)
Utah	17	39,000		Unknown		Unknown	Unknown
	(10)	(150)		(30)		(0)	(0)
Vermont	5	148,000		Unknown		Unknown	Unknown
	(3)	(150)		(30)		(60)	(0)
Virginia	23	534,000		Unknown		Unknown	Unknown
	(14)	(150)		(30)		(0)	(0)
Washington	19	172,000		Unknown		Unknown	Unknown
	(11)	(150)		(30)		(0)	(0)
West Virginia	18	184,000		Unknown		Unknown	Unknown
	(11)	(150)		(30)		(0)	(0)
Wisconsin	14	414,000		Unknown		Unknown	Unknown
	(8)	(150)		(30)		(60)	(0)
Wyoming	2	88,000		Unknown		Unknown	Unknown
	(1)	(150)		(30)		(0)	(0)
American Samoa	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)
Federated States of Micronesia	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)
Guam	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)
Marshall Islands	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)
Northern Mariana Islands	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)
Palau	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)
Puerto Rico	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)
U.S. Minor Outlying Islands	Unknown	Unknown		Unknown		Unknown	Unknown
	(0)	(0)		0		(0)	(0)

**The eastern and western portions of Texas and Oklahoma are treated as separate strata by the Forest Inventory and Analysis forest statistical estimation procedures and therefore, they are treated as separate strata for the National Woodland Owner Survey.

In addition to the base sample indicated in table B-1, we will intensify up to 10 states that indicated interest in conducting intensified surveys in their states. The number of states in which intensification occurs will ultimately depend on funding, but it could result in as many as 1,500 additional responses.

Up to 16 focus groups will be conducted over the 3-year sampling period. The number of focus groups decreased from the previous iteration of the survey because we completed the urban focus groups. The locations will be distributed across the United States with the intent to fully test the science modules and to do qualitative research in the Caribbean and Pacific Islands. For the science module focus groups, two topics/modules would be addressed in each focus group session. Each focus group will consist of eight participants for a total of approximately 128 focus group participants over the three-year period. We will also conduct no more than 30 cognitive interviews. No additional interviews will be conducted once no additional information is being gleaned. These qualitative efforts will involve up to 158 landowners.

Expected Response Rates: The target response rate is 80+ percent. During the last iteration of the NWOS, the national response rate was just over 45 percent. Methods for increasing response rates and testing for non-response bias are described below.

2. Describe the procedures for the collection of information including:

• Statistical methodology for stratification and sample selection,

• Estimation procedure,

• Degree of accuracy needed for the pur­pose described in the justification,

• Unusual problems requiring specialized sampling procedures, and

• Any use of periodic (less frequent than annual) data collection cycles to reduce burden.

All of the statistical procedures have been peer-reviewed and have been published in USDA Forest Service, National Woodland Owner Survey 2011-2013: Design, Implementation, and Estimation Methods (USDA Forest Service Gen. Tech. Rep. 2016) and Methods for Estimating Private Forest Ownership Statistics: Revised Methods for the USDA Forest Service's National Woodland Owner Survey (Journal of Forestry 111(5): 319-325). The statistical procedures have not changed from the previous iteration of the NWOS.

STATISTICAL METHODOLOGY

The sampling design is, technically speaking, a spatially tessellated and temporally systematic, disproportionately stratified, with-replacement, and probability proportional to size sampling design. First, each state is divided into non-overlapping hexagons. In rural areas, the hexagons are approximately 6,000 acres in size. An interwoven panel design is used to distribute the sample evenly over the sample period. Within each hexagon, a sample point is randomly placed. The land use/cover at this point is determined using remotely sensed data. If the point is forested, the owner of the underlying land is identified using tax records or other public sources. The sample point is then assigned to one of the strata described above. In states where the base sample is insufficient or the sample is intensified as part of the state intensification process, the size of the hexagons is reduced to generate the desired number of respondents. In census-defined urban areas, analogous sampling procedures are used, except that the size of the hexagons is adjusted to generate the desired number of respondents.

ESTIMATION PROCEDURES

To account for the sampling design described above, the following population and variance estimators are used. These are further detailed in USDA Forest Service, National Woodland Owner Survey 2011-2013: Design, Implementation, and Estimation Methods (USDA Forest Service Gen. Tech. Rep. 2016) and Methods for Estimating Private Forest Ownership Statistics: Revised Methods for the USDA Forest Service's National Woodland Owner Survey (Journal of Forestry 111(5): 319-325).

Ownership-based Totals

The number of ownerships within a given stratum and domain of interest (e.g., the number of ownerships with a written forest management plan) can be estimated by:

(1)

Where
= number of forestland ownerships in stratum h and domain d,
= area of forestland in the stratum, derived from FIA data,
= number of sample points owned by survey respondents in the stratum,
= an indicator taking the value of 1 if ownership is in domain and 0 otherwise,
= area of forestland owned by ownership i, and
= .

The variance of this statistic can be estimated by:

(2)

Where

Ideally, a covariance term would be included in equation 2, but it is not estimable with the available data.

Acre-based Totals

The number of forested acres within a given stratum and domain of interest can be estimated by:

Where
= area of forestland in stratum h and domain d,
= area of forestland in the stratum, derived from FIA data,
= number of sample points owned by survey respondents in the stratum,
= an indicator taking the value of 1 if ownership is in domain and 0 otherwise, and
and is equivalent to the sample proportion of points associated with responding family forest ownerships which are in the domain of interest.

The estimator of the variance of this total estimator is:

(4)

Where

DEGREE OF ACCURACY

The target sample size for rural private owners with small land holdings is a minimum of 250 in a state over a 5-year reporting period, or 150 per state over the 3-year OMB approval period. Examining the coefficients of variation for the estimated numbers of ownerships from the previous iteration of the NWOS, the values approach an asymptote of approximately 0.15 at a sample size of about 250 and hence our target sample size. Samples sizes beyond this number allow us to ask additional questions and to provide meaningful sub-state level estimates. Similar accuracies are sought for other strata, but a current lack of data on population size and coefficients of variation impede calculations.

UNUSUAL PROBLEMS

No unusual problems requiring specialized sampling procedures will be used.

PERIODIC DATA COLLECTION

No ownership is asked to respondent more than once every five years, so periodic (less frequent than annual) data collection methods are not needed.

3. Describe methods to maximize response rates and to deal with issues of non-response. The accuracy and reliability of information collected must be shown to be adequate for intended uses. For collections based on sampling, a special justification must be provided for any collection that will not yield "reliable" data that can be generalized to the universe studied.

To maximize the response rates, we follow the standard methods described in Internet, Phone, Mail, and Mixed-mode Surveys: The Tailored Design Method by D. Dillman, J. Smyth, and L. Christian in order to establish trust, increase rewards, and reduce social costs. Part of the trust comes from the fact that the NWOS is conducted by a federal agency. We try to enhance this trust by stressing the importance and confidentiality of their answers in our interactions with them. To increase rewards, we highlight the specific uses of the data collected and the fact that they are a part of a statistical sample and their answer represents many other owners. To reduce social costs, we have developed a questionnaire that is as short as possible, easy to understand, and contains no sensitive questions.

Survey implementation will include a pre-notice, a first copy of the questionnaire with a cover letter, a reminder notice, and a second questionnaire with a cover letter. First, a pre-notice letter will be mailed to all potential respondents describing this information collection – why we are doing it and why we need their help. Second, the potential respondents will receive a questionnaire with a cover letter. The cover letter will reiterate the purpose and importance of this information collection and provide the respondents with all legally required information. Third, a reminder will be mailed to thank the respondents and encourage the non-respondents to respond. For those who have not yet responded, they will receive a second questionnaire and cover letter. Telephone interviews will be attempted for respondents who did not respond to previous contact. To reduce burden on respondents, respondents will be able to choose between hardcopy and electronic versions of the questionnaire.

Tests will be conducted to assess if non-response biases are present. These tests will include those outlined by the Federal Committee on Statistical Methodology Workshop’s How to do Nonresponse Bias Analyses in Household and Establishment Surveys and the tests prescribed in publications, such as Groves et al.’s Survey Nonresponse. For example, early vs. late (e.g., mail vs. telephone) responses will be compared. In addition, we will use data collected as part of the sample frame (e.g., acres of land owned) and other external data sources to test for non-response biases. These tests have been conducted on previous iterations of the NWOS and no significant biases have been found, but we will continue to look and continue to refine our detection techniques. If a significant non-response bias is detected, statistical estimates will be adjusted appropriately. The specific adjustment procedure used will depend on the type and severity of bias, but could include post stratification, weighting based on auxiliary data, and/or imputation.

4. Describe any tests of procedures or methods to be undertaken. Testing is encouraged as an effective means of refining collections of information to minimize burden and improve utility. Tests must be approved if they call for answers to identical questions from 10 or more respondents. A proposed test or set of tests may be submitted for approval separately or in combination with the main collection of information.

The questions and procedures used have been tested as part of previous iterations of the NWOS. In addition, we are proposing to conduct focus groups and cognitive interviews as part of this iteration of the NWOS to further test the survey instruments and refine our understanding of the responses.

5. Provide the name and telephone number of individuals consulted on statistical aspects of the design and the name of the agency unit, contractor(s), grantee(s), or other person(s) who will actually collect and/or analyze the information for the agency.

• Peter Quan, USDA National Agricultural Statistics Service, Mathematical Statistician. (703) 877-8000

• James Westfall, USDA Forest Service, Research Forester. (610) 557-4043

• Paul Patterson, USDA Forest Service, Mathematical Statistician. (970) 295-5966

• Mark Hansen, USDA Forest Service, Forest Inventory and Analysis Program. (651) 649-5148 

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