Gap Analysis of Conserved Genetic Resources for Forest Trees

SARA R. LIPOW,∗†† KENNETH VANCE-BORLAND,∗ J. BRADLEY ST. CLAIR,† JAN HENDERSON,‡ AND CINDY MCCAIN§ ∗Department of Forest Science, Oregon State University, Corvallis, OR 97331, U.S.A. †U.S. Forest Service, Forestry Sciences Laboratory, Corvallis, OR 97331, U.S.A. ‡U.S. Forest Service, Supervisor’s Office, Mt. Baker–Snoqualmie National Forest, Mountlake Terrace, WA 98043, U.S.A. §U.S. Forest Service, Siuslaw National Forest, Corvallis, OR 97339, U.S.A.

Abstract: We developed a gap analysis approach to evaluate whether the genetic resources conserved in situ in protected areas are adequate for conifers in western Oregon and Washington (U.S.A.). We developed geographic information system layers that detail the location of protected areas and the distribution and abundance of each tree species (noble fir [Abies procera Rehd.] and Douglas-fir [Pseudotsuga menzeisii Mirb.]). Distribution and abundance were inferred from available spatial data showing modeled potential and actual vegetation. We stratified the distribution of each species into units for genetic analysis using seed and breeding zones and ecoregions. Most strata contained at least 5000 reproductive-age individuals in protected areas, indicating that genetic resources were well protected in situ throughout most of the study region. Strict in situ protection was limited, however, for noble fir in the Willapa Hills of southwestern Washington. An in situ genetic resource gap arguably occurred for Douglas-fir in the southern Puget lowlands, but this gap was filled by extensive ex situ genetic resources from the same region. The gap analysis method was an effective tool for evaluating the genetic resources of forest trees across a large region.

An´alisis de Claros de Recursos Gen´eticos Conservados para Arboles´ de Bosque Resumen: Desarrollamos un m´etodo de analisis´ de claros para evaluar si los recursos gen´eticos conservados in situ en areas´ protegidas son adecuados para con´ıferas en el oeste de Oregon y Washington (E. U. A.). Desarrollamos capas de sistema de informacion´ geografica´ que detallan la localizacion´ de areas´ protegidas y la distribucion´ y abundancia de cada especie de arbol´ (Abies procera Rehd. y Pseudotsuga menzeisii Mirb). La distribucion´ y abundancia fueron inferidas a partir de datos espaciales disponibles que muestran la vegetacion´ potencial modelada y la vegetacion´ existente. Estratificamos la distribucion´ de cada especie en unidades para el analisis´ gen´etico utilizando zonas de semillas y reproduccion´ y ecoregiones. La mayor´ıa de los estratos conten´ıan por los menos 5000 individuos en edad reproductiva en areas´ protegidas, lo que indica que los recursos gen´eticos estaban bien protegidos in situ en casi toda la region´ de estudio. Sin embargo, la proteccion´ in situ estricta estaba limitada para A. procera en las Colinas Willapa del suroeste de Washington. Se podr´ıa decir que ocurrio´ un claro de recursos gen´eticos in situ para P. menzeisii en las tierras bajas del sur de Puget, pero este claro fue llenado por recursos gen´eticos extensivos ex situ de la misma region.´ Encontramos que el m´etodo de analisis´ de claros es una herramienta valiosa para evaluar los recursos gen´eticos de arboles ´ de bosque en una region´ amplia.

††Current address: 2600 State Street, Oregon Department of Forestry, Salem, OR 97310, U.S.A., email [email protected] Paper submitted February 19, 2002; revised manuscript accepted July 29, 2003.

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Introduction fir and Douglas-fir, respectively. These ex situ collections are a valuable component of the total available genetic Biological diversity refers to the variety and abundance of resources for the species. species and the communities in which they occur and to The goal of our in situ analysis was to identify places the genetic composition of individual species. Land-use where large populations of each species are protected changes, disease conditions, and climatic change directly in reserves and places where few or no trees are pro­ threaten forest species and communities. They also jeop­ tected (gaps). We did this by performing a gap analysis ardize the genetic variation that enables tree species to in a geographic information system (GIS). Gap analysis evolve and thrive under changing environmental condi­ typically refers to a scientific process that identifies the tions. Threats to tree species can affect the long-term sur­ degree to which native species and natural communities vival of the associated flora and fauna. Genetic variation are represented in present-day conservation lands (Scott of forest trees is also essential for sustainable production & Jennings 1997). Those species and communities not ad­ of forest products and therefore has important social and equately represented in the existing network of conserva­ economic implications. tion lands constitute conservation “gaps.” The methods Concerns for biological diversity and the genetic as­ of gap analysis were originally developed for application pects of sustainable forest management prompted a group to vertebrate species and land-cover types (Scott & Jen­ of public and private organizations in western Oregon and nings 1998), but they are relevant to a wide range of taxa Washington to form the Pacific Northwest Forest Tree and hierarchies of biodiversity. We applied them to de­ Gene Conservation Group. One objective of this group is termine whether the genetic variation within species is to identify whether areas in the region exist where addi­ adequately represented. Gap analysis involves intersect­ tional conservation measures are necessary to ensure that ing digital maps displaying protected areas with those the adaptation and evolutionary potential of important showing species occurrences and, in this case, patterns tree species are maintained. To identify possible areas, of genetic variation. we have compiled data on genetic resources conserved both at their original location (in situ) and at some other location (ex situ). Methods We developed a gap analysis approach to investigate ge­ netic resources conserved in situ in protected areas. We Study Area present results for Douglas-fir (Pseudotsuga menziesii The study area included a wide region extending from [Mirb.] Franco var. menziesii) and noble fir (Abies pro­ the coast of Oregon and Washington through the eastern cera Rehd.). Results for six other tree species are reported slopes and foothills of the Cascades (Fig. 1). Douglas-fir separately: Tsuga heterophylla (Raf.) Sarg., Thuja plicata occurs throughout much of the study area. Noble fir is Donn ex D. Don, Pinus ponderosa Dougl. ex Laws, Picea found from the Cascades of northern Washington to the sitchensis (Bong.) Carr., Pinus monticola Dougl. ex D. McKenzie River Valley in Oregon and at high peaks in Don, and Pinus lambertiana Dougl. (S.R.L., K.V.-B., J.B.S., the Coast Range and Willapa Hills (Fig. 2a). South of the J.A.H., & C.M., unpublished data). These species are com­ McKenzie River, noble fir overlaps the range and intro­ mon in western Oregon and Washington (U.S.A.) and are gresses with Shasta red fir (Abies magnifica shastensis commercially important. Lemm.) (Sorenson et al. 1990). The in situ genetic resources we evaluated are only one component of an overall gene conservation strat­ Protected Areas egy (Yanchuk & Lester 1996; Lipow et al. 2001). The tree species also have extensive genetic resources in ex We projected all GIS coverages and grids (Table 1) in Uni­ situ collections, including progeny tests, seed orchards, versal Transverse Mercator Projection, Zone 10. Analyses and seed stores (Lipow et al. 2001; S.R.L., K.V.-B., J.B.S., were done with ARC/INFO and Arcview software (Envi­ J.A.H., & C.M., unpublished data). In Oregon and Wash­ ronmental Systems Research Institute 1999, 2000). ington, progeny from >1679 noble fir selections from A protected-areas coverage was developed following natural populations are maintained in genetic tests or conventions employed by the National Gap Analysis Pro­ in 1 of 14 seed orchards. The tested selections span gram (GAP). This program assigns land to four status levels the species’ range, excluding the Willapa Hills of south­ (Scott et al. 1993). We considered all status 1 and 2 lands western Washington. Hundreds of additional selections protected. Management plans for status 1 lands call for are maintained in Europe. For Douglas-fir, over 1 million maintaining a natural state and allowing natural distur­ progeny from >29,000 selections are maintained in re­ bance events to proceed; examples include wilderness gional first-generation progeny tests. Second-generation areas, national parks, and U.S. Forest Service (USFS) re­ tests will contain >2000 of the selections evaluated in search natural areas. Status 2 lands are generally managed the first-generation tests. Regional seed stores include for natural values but may be used in ways that degrade >1460 and >20,000 seed lots stored by family for noble the quality of existing natural communities; examples

Conservation Biology Volume 18, No. 2, April 2004 414 Genetic Gap Analysis for Forest Trees Lipow et al.

The protected-areas coverage combined data from sev­ eral available coverages (Table 1; Fig. 3). In Oregon most status 1 and 2 lands were identified on the land manage­ ment and stewardship coverage (Oregon GAP). Most pro­ tected areas in Washington were identified on the major public lands coverage (Washington Department of Nat­ ural Resources) or the natural areas coverage (Interior Columbia Basin Ecosystem Management Project). We fol­ lowed the Oregon GAP land designations when assign­ ing reserve status to these lands. For example, because the Oregon GAP designated wilderness areas as status 1, we assigned them to status 1 in Washington. Preserves of The Nature Conservancy and natural-area preserves and natural-resource conservation areas of the Wash­ ington Department of Natural Resources were also in­ cluded as status 1 lands. Federal Late Succession Reserves (FEMAT 1993) were included as status 2 lands.

Species Distributions Developing high-resolution species-distribution maps was essential to the gap analysis. Existing range maps (e.g., Lit­ tle 1971) were inadequate for our purposes because they indicated only species boundaries, not whether a species was present at a specific location within that range or the frequency of a species at a location. We derived distribu­ tion maps from spatial data showing vegetation type or plant association group. The quality and type of data var­ ied across the region. For each area, we chose the data set of highest resolution (Fig. 1). The tree-distribution maps in Washington and north­ western Oregon were based on the plant-association group (PAG) submodel of the potential natural vegeta­ tion (PNV) model (Henderson 1998). Plant-association groups have similar floristics and environment and are suitable units for mapping. They are defined by the cli­ max composition of overstory and understory vegetation and are recognized in field plots by the theoretical climax stage, although they include all seral stages (Hall 1998). Accordingly, the tree distributions we derived from the PAG submodel represented those expected under climax Figure 1. The study area boundary and underlying or subclimax conditions. This was advantageous for our data layers used to generate tree-distribution maps. gap analysis because the maps predicted where species Codes are defined in Table 1. Data types are described could potentially exist, including areas where they were in the text. no longer present because of human disturbance. Al­ though we would liked to have known the actual distri­ include national wildlife refuges and most state parks. Sta­ bution of species in protected areas, the necessary data tus 3 lands are subject to extractive uses such as timber were not available. We assumed that potential and actual harvest but have legal mandates that generally prevent distributions were equivalent in protected areas. This as­ permanent land-cover change from natural or seminat­ sumption was probably valid for many protected areas ural communities to anthropogenic cover types; exam­ because Douglas-fir and noble fir are found in a variety of ples include most “matrix” lands of the Bureau of Land seral stages, and protected areas presumably suffer from Management (BLM) and the USFS. Although we did not minimal human disturbance. consider status 3 lands protected, they often contain con­ The PNV model was an environmental gradient model siderable in situ genetic resources. Finally, status 4 lands that depended on quantifiable aspects of temperature and are managed for extensive human uses. moisture regimes. Predictor variables included elevation,

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Figure 2. Noble fir (a) density and distribution derived from modeled potential natural vegetation, (b) gap analysis results based on the seed-zone stratification, and (c) gap analysis results based on the ecoregion stratification. In (c), only ecoregion polygons containing noble fir are displayed, and all protection class 2 and 3 strata are labeled. Protection classes are defined in Table 2. precipitation, mean annual temperature, temperature each combination. We modeled four density levels: high lapse rate, fog effect, aspect, site moisture, cold-air (>100 stems/ha), medium 10–100 stems/ha), low (<10 drainage effects, and a logistical stratification (PNV eco­ stems/ha), and absent. zones). We used data from ecology plots on federal lands Data for the plant-association group submodel were not and various other plots (Henderson 1997) to develop and available for the entire study area. For the Deschutes and calibrate the model. At a minimum, the plot data indicated Winema National Forests, we derived tree distributions geographic location, PAG, and a set of environmental fac­ from GIS coverages of climax plant associations based tors. The nine PAG grids we used contained data from on aerial photography and field reconnaissance (1:24,000 >6600 plots in Oregon and >10,000 plots in Washing­ scale). Again, we generated tables showing four densities ton. of trees and joined them to the plant-association cover­ The PAG submodel generated a GIS grid in which each ages to create distribution maps. pixel represented 30 × 30 m2. We resampled to 90 × For southern Oregon and the remaining areas with 90 m2 to reduce processing time and because our other no PAG data, we used a GIS layer produced by Oregon data were coarser than 30 × 30 m2. We derived tree dis­ GAP using Landsat Thematic Mapper digital data and con­ tributions from the PAG output through a set of tables ventional remote-sensing analysis and classification tech­ to predict the density of each species in each PAG by niques (Kilsgaard 1999). This layer showed generalized PNV-ecozone combination. The tables showed the ex­ land-cover types representing actual vegetation and had pected density of mature individuals of each species for lower accuracy and precision than the spatial data for

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Table 1. Coverages and grids used in the gap analysis of the genetic resources conserved in situ in protected areas.

Source Coverage or grid (code) Scale or pixel size∗ Protected areas Interior Columbia Basin Ecosystem Management natural areas 1:24,0001:500,000 Project Oregon GAP Analysis Program land management and land stewardship 1:100,000 The Nature Conservancy of Washington Nature Conservancy preserves NM The Wilderness Society Option 9 lands (late-successional reserves) NM Washington Department of Natural Resources major public lands (1997 version) 1:100,000 Washington Natural Heritage Program Washington Department of Natural Resources 1:24,000 protected areas Tree distributions J. Henderson, Mt. Baker–Snoqualmie National Olympic National Forest plant association groups 30 × 30 m2 Forest ( January 2000 version) (OLY) J. Henderson, Mt. Baker–Snoqualmie National Okanogan National Forest plant association groups 30 × 30 m2 Forest ( January 2000 version) (OKA) J. Henderson, Mt. Baker–Snoqualmie National Mt. Baker–Snoqualmie National Forest plant 30 × 30 m2 Forest association groups ( January 2000 version) (MBS) J. Henderson, Mt. Baker–Snoqualmie National Gifford Pinchot National Forest plant association 30 × 30 m2 Forest groups ( January 2000 version) (GIP) J. Henderson, Mt. Baker–Snoqualmie National Wenatchee National Forest plant association groups 30 × 30 m2 Forest ( January 2000 version) (WEN) C. McCain, Siuslaw National Forest Siuslaw National Forest plant association groups 30 × 30 m2 (August 2000 version) (SIU) C. McCain, Siuslaw National Forest Willamette National Forest plant association groups 30 × 30 m2 (August 2000 version) (WIL) C. McCain, Siuslaw National Forest Mt. Hood National Forest plant association groups 30 × 30 m2 (August 2000 version) (MTH) C. McCain, Siuslaw National Forest Willamette Valley plant association groups (August 30 × 30 m2 2000 version) (VAL) Oregon Natural Heritage Program land cover for Oregon: OR-GAP Version 2 (SOR) 1:100,000 Deschutes National Forest plant association of the Deschutes National Forest 1:24,000 (DES) Fremont National Forest ecoclass mapping of the Fremont National Forest 1:24,000 (FRE) Winema National Forest vegetation plant community of the Winema 1:24,000 National Forest (WIN) Corvallis Forestry Sciences Laboratory, Pacific Northwest Ecosystem Research Consortium: 25 × 25 m2 Laboratory for Applications of Remote Sensing Willamette River Basin land use/land cover map in Ecology v.3, Oetter et al. 2001 Genetic and ecological stratifications Washington Department of Natural Resources Washington seed zones, Randall & Berrang 2002 NM Oregon Department of Forestry Oregon seed zones, Randall 1996 NM Environmental Protection Agency ecoregions (level IV), Pater et al. 1998 1:250,000 Deschutes National Forest Deschutes National Forest breeding zones NM Winema National Forest Winema National Forest breeding zones NM ∗NM, no metadata provided by the source agency. other areas. For analysis, we converted the original poly­ based on Landsat thematic mapper data and showed goncoveragetoagridof25 × 25 m2 resolution before conifer cover and age class. Again, we generated tables resampling to 90 × 90 m2. showing four densities of trees and joined them to the Finally, we identified low-elevation (<120 m), forested plant-association coverages to create distributions maps. portions of the Willamette Valley on a land-cover grid pro­ Again, we joined a table of tree abundances within cover duced by the Pacific Northwest Ecosystem Research Con­ types to the grid to produce species distributions. sortium (Oetter et al. 2001). Most low-elevation land in the Willamette Valley has been permanently converted to Accuracy Assessment of Species Distributions agriculture or urban development. The land-cover grid, which showed actual vegetation, was therefore more To estimate the accuracy of the resulting species-distri­ likely to reflect true tree distributions in Willamette Val­ bution maps, we analyzed data on species occurrences ley protected areas than the respective PAG grid, which from an independent data set produced by the USFS’sPa­ showed potential distributions. The land-cover grid was cific Northwest Region Current Vegetation Survey (CVS)

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tribution map was based on the Oregon GAP land-cover coverage because it showed actual vegetation. Only plots in national forests or BLM districts where a given species was known to occur were evaluated. For instance, the analysis for noble fir included plots in the Gifford-Pinchot National Forest but not the Olympic National Forest be­ cause the latter is outside the species’ range (Little 1971). To estimate the accuracy of the species-distribution maps, we compared pixels on the distribution maps to the corresponding CVS plots. We compared the number of pixels where a species presence was predicted at ei­ ther high or medium density with the number of CVS plots in which a species was detected. The number of pixels where a species absence was predicted was also compared to the number of CVS plots in which a species was not detected. We could not adequately assess the ac­ curacy of the low-density level with the CVS plot data be­ cause of limitations of the survey-plot sampling design.

Patterns of Genetic Variation We applied two systems to stratify each species into pop­ ulations for analysis: (1) seed and breeding zones and (2) ecoregions. The species-specific seed zones were de­ signed to inform land managers about risks associated with moving seed from a source environment to another location during reforestation (Randall 1996; Randall & Berrang 2002). Their sizes and boundaries reflect infor­ mation obtained from common garden, genecological, isozyme, and seed-movement studies indicating the ex­ tent and geographic patterns of genetic variation in the studied populations. Species like Douglas-fir with a high proportion of among-population genetic diversity have Figure 3. Location of protected areas in western small seed zones subdivided into relatively narrow eleva­ Oregon and Washington. Status 1 and 2 codes are as tional bands (Fig. 4b). Noble fir has less population-level defined by the National Gap Analysis Program (Scott genetic variation and, consequently, larger seed zones et al. 1993). with wider elevational bands (Fig. 2b). Seed-zone polygons were divided into the defined el­ evation bands (Randall 1996; Randall & Berrang’s 2002) ( Johnson 1998). Survey plots were distributed in a grid based on a 90-m digital elevation model. Randall’s (1996) and were spaced 2.7 km apart on most federal lands, ex­ seed zones for Douglas-fir in Oregon do not extend east cept in wilderness areas, where they were spaced 5.5 km of the Cascade crest. For this area, we substituted breed­ apart. Species was recorded for all trees >1.219 m di­ ing zones and elevation bands delineated by the USFS ameter at breast height (dbh) in a 1-ha plot and for trees (Fig. 4b). 0.330–1.218 m dbh in five 0.076-ha subplots, 0.076–0.329 The ecoregion stratification was developed by a group m dbh in five 0.017-ha subplots, and 0.025–0.124 m dbh of government agencies, including the Environmental in five 0.004-ha subplots. The data set we used showed Protection Agency and the U.S. Geological Survey, with species presence in all CVS plots but did not indicate the intent of providing a spatial framework for environ­ subplot. mental resource management (Omernik 1995; Pater et In areas where the distribution maps were based on the al. 1998). Ecoregions denote areas of general similarity PNV model, the analysis was limited to plots in protected in ecosystems and were based on environmental factors areas, where we assumed that actual and potential dis­ and vegetation. We used the most detailed level IV ecore­ tributions were equivalent. Because of limited protected gions (see Gallant et al. 1989). The study region contained areas in the Deschutes and Winema national forests, we 55 level IV ecoregions represented by 335 polygons (i.e., examined all CVS plots there regardless of protected sta­ they were not continuous). Application of this stratifica­ tus. All CVS plots were analyzed for regions where the dis- tion to genetic analysis required assuming correlation of

Conservation Biology Volume 18, No. 2, April 2004 418 Genetic Gap Analysis for Forest Trees Lipow et al.

Figure 4. Douglas-fir (a) density and distribution derived from data layers showing potential natural vegetation or actual vegetation (location of a disjunct population on the Fremont National Forest is indicated with a star). (b) Gap analysis results based on seed- and breeding-zone stratifications. Each stratum is numbered and assigned a three-digit code in which the first value indicates the number of elevation bands assigned to protection class 1, the second the number assigned to protection class 2, and the third the number assigned to protection class 3. Seed and breeding-zone-by-elevation-band polygons assigned to protection classes 2 and 3 are shaded. In some seed zones, protection class 2 and 3 elevation bands include only a small fraction of the total area. (c) Gap analysis results based on the ecoregion stratification. All class 2 and 3 ecoregions are shaded and labeled. adaptive and environmental variation across a species’ coverage and tabulated the area in each density class in range. We expect the extent of this correlation, and the each ecoregion and in protected areas in each ecoregion. accuracy of the assumption, to vary among species. Next, we assigned species in strata to one of three classes of protection defined by the minimum expected population sizes of species in whole strata and in status 1 and 2 protected areas (Table 2). We estimated minimum Gap Analyses expected population sizes as: (ha at high density × For the seed- and breeding-zone gap analyses, we over­ 100) + (ha at medium density × 10) + (ha at low layed the protected-areas coverage on each seed or density). breeding-zone-by-elevation coverage. We then tabulated Protection class 1 was defined as well protected in sta­ the area of each density class in each elevation band of tus 1 protected areas. For strata where species were com­ each seed or breeding zone and the area of each density mon (minimum expected population size >25,000), class class in protected areas in each elevation band of each 1 required at least 5000 individuals to be in status 1 pro­ seed or breeding zone. For the ecoregion analyses, we tected areas. For strata where species were uncommon overlayed the protected-areas coverage on the ecoregion (minimum expected population size of 5000–25,000),

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Table 2. Definitions of the classes of protection assigned to strata in the gap analysis of conserved genetic resources for Douglas-fir and noble fir.

Minimum expected population size∗ Class of Species status 1 status 1 and 2 protection occurrence Description of class entire stratum protected areas protected areas

1 common well protected in status 1 areas alone >25,000 >5,000 1 not common well protected in status 1 areas alone 5,000–25,000 >10% of entire stratum 2 common well protected in status 1and 2 areas >25,000 <5,000 >5,000 combined 2 not common well protected in status 1and 2 areas 5,000–25,000 <10% of entire >10% of entire combined stratum stratum 3 common not well protected >25,000 <5,000 3 not common not well protected 5,000–25,000 <10% of entire stratum ∗Minimum expected population size calculated as Σ(ha at high density × 100) + Σ(ha at mid density × 10) + Σ(ha at low density). Status 1 lands have management plans that call for maintaining a natural state and allowing natural disturbance events to proceed (Scott et al. 1993). Status 2 lands are generally managed for natural values but may be used in a way that degrades the quality of existing natural values (Scott et al. 1993). class 1 required the number of individuals in protected areas to 96.6% on the Deschutes and Winema National areas to exceed 10% of the number in the whole stratum. Forests to 60.0% for Oregon GAP land-cover areas. Protection class 2 was defined as well protected, consider­ ing both status 1 and 2 protected areas. A stratum ranked Gap Analyses in this class if, when the species was common, at least 5000 individuals were in status 1 and 2 protected areas For noble fir, the gap analysis indicated adequate con­ combined, with less than 5000 individuals in status 1 pro­ servation of genetic resources in all three seed zone by tected areas alone. For strata where a species was uncom­ elevation band combinations. The analysis categorized mon, at least 10% of all individuals in a stratum must have the species as well protected in status 1 protected ar­ been in status 1 and 2 protected areas. The cutoff popu­ eas in both the high- and low-elevation Cascades zones lation size of 5000 is in line with recommendations from (Table 4; Fig. 2b). The Coast Range zone was categorized research addressing the desirable population size for the as well protected in status 1 and 2 protected areas, al­ purposes of gene conservation (Lande 1995; Lynch 1996; though our field observations indicated that the actual Yanchuk & Lester 1996; Yanchuk 2001). Protection class number of trees in status 1 protected areas exceeded 3 was defined as not well protected in either status 1 or 2 5000. protected areas. We did not classify species in strata with Of the 10 ecoregions containing noble fir, only the a minimum expected population size of <5000. Willapa Hills ecoregion was classified as not well pro­ tected (class 3). This ecoregion occurs in the Coast Range of northern Oregon and southwestern Washington. The

Results Table 3. Number of current vegetation survey plots on which a species was predicted to be present or absent at the corresponding location Accuracy of Species-Distribution Maps on the distribution map and, of these, the number of plots validated.

Considering only those national forests within the range Number Number of noble fir, the distribution map (Fig. 2a) predicted Prediction predicted validated Ratio species presence on 309 CVS plots, and, of these, de­ Noble fir: potential natural vegetation model tections occurred on 160 (51.8%) (Table 3). Of the 1130 present 309 160 0.518 plots for which the PNV model predicted no noble fir, absent 1130 1055 0.934 none were detected on 1055 (93.4%). Overall, Douglas- Douglas-fir: potential natural vegetation model fir was detected on 88.6% of plots for which it was pre­ present 1564 1305 0.834 absent 433 343 0.790 dicted, with successful detection percentages equaling Douglas-fir: Deschutes and Winema national forests 83.4% for areas based on the PNV model, 71.3% on the De­ present 108 77 0.713 schutes and Winema National Forests, and 96.3% for areas absent 645 623 0.966 based on the Oregon GAP land-cover coverage (Table 3). Douglas-fir: Oregon gap land cover Of the plots where Douglas-fir absence was predicted, present 1272 1225 0.963 absent 25 15 0.600 validation percentages varied from 79.0% for PNV model

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Table 4. Protection class and minimum expected population size in whole strata and in status 1 and 2 protected areas for the gap analysis of noble fir based on seed zone and ecoregion stratifications.

Minimum expected population size∗ status 1 Protection Stratum stratum status 1 and 2 class Seed zone-elevation (code) Coast Range, all (1) 32,922 3,483 22,397 2 Cascade Range, low (2) 2,995,788 1,399,964 2,394,652 1 Cascade Range, high (2) 5,506,527 783,264 2,263,462 1 Ecoregions (code) Coastal volcanics (1d) 69,317 3,605 24,875 2 Willapa hills (1f ) 27,811 0 2,859 3 Western Cascades lowlands (4a) 1,080,050 62,239 295,400 1 Western Cascades montane highlands (4b) 3,774,190 669,968 1,975,290 1 Cascade crest montane forest (4c) 2,651,963 1,094,981 1,771,308 1 Cascades subalpine/alpine (4d) 409,477 246,758 383,244 1 North Cascades highland forests (77b) 30,214 5,263 7,768 1 Grand fir mixed forest (9b) 22,617 6,336 13,628 1 ∗See Table 2 for explanation. only protected area in it with noble fir is Oregon’s Sad­ the next-lower elevation band, large Douglas-fir stands are dle Mountain State Park (status 2), where several hundred present in late-successional reserves and in four widely scattered individuals grow throughout the park in stands spaced status 1 protected areas. The categorization of dominated by Douglas-fir and Sitka spruce (S.R.L., per­ the remaining class 3 seed-zone-by-elevations bands for sonal observation). Douglas-fir was based largely on the arbitrary delineation Douglas-fir genetic resources were adequately con­ served throughout most of the species’ regional range Table 5. For strata belonging to protection class 3 in the Douglas-fir (Fig. 4b). Of the 204 seed-zone-by-elevation bands in gap analyses,a the minimum expected population size in each stratum Washington and west of the Cascade Crest in Oregon, as a whole and in status 1 and 2 protected areas. 198 (97.1%) were well protected in status 1 or 2 pro­ Minimum expected tected areas (classes 1 and 2). Of the 18 breeding-zone­ population sizeb by-elevation bands defined for the Deschutes and Winema national forests east of the Cascade Crest in Oregon, 14 status 1 Location of class-3 stratum stratum status 1 and 2 (77.8%) were well protected in status 1 or 2 protected ar­ eas. In the analysis using ecoregions, 52 of the 54 (96.3%) Seed-zone-by-elevation-band analysis ecoregions containing Douglas-fir were well protected in OR5 by 915–1066 m 86,297 0 243 OR11 by 0–305 m 122,075 1458 4,212 status 1 or 2 protected areas. Thus, a total of 12 Douglas-fir OR15 by 610–762 m 123,412 0 0 strata were identified as putative gene-conservation gaps OR16 by 306–457 m 738,317 510 585 (class 3) (Table 5). WA6by306–610 m 7,790,915 0 0 Three putative gene-conservation gaps (two seed­ WA6by611–914 m 643,470 0 0 zone–by-elevation bands and a partially overlapping Breeding-zone-by-elevation-band analysis Deschutes-Fort Rock 36,933 820 820 ecoregion) occurred in the southern Puget lowlands. by <1524 m These elevation bands were comprised of scattered Winema-Chiloquin 43,460 43 2,104 higher-elevation sites in the otherwise low-elevation area. by <1524 m The southern Puget lowland consists primarily of pri­ Winema-Chiloquin 51,473 0 3,979 vately owned and agricultural or developed land and by 1525–1676 m Winema-Chiloquin 32,040 0 4,101 has few protected areas. Four putative gene-resource by 1677–1829 m gaps (three breeding-zone–by-elevation bands, all below Ecoregion analysis 1829 m, and a corresponding ecoregion) were found on 2h-Cowlitz/Chehalis 5,540,481 0 2,568 the Chiloquin Ranger District of the Winema National For­ foothills 9h-Fremont Pine/ 41,755 40 1,384 est, where Douglas-fir occupies one north-south running Fir forest ridge system with little designated protected area. The a lowest elevation band (<1524 m) in the Fort Rock breed­ Gap analyses were done using seed-zone-by-elevation bands for ing zone of the Deschutes National Forest was identified Washington and west of the Cascade crest in Oregon, breeding-zone-by-elevation bands for the Deschutes and Winema as a putative gap. In the north Oregon Coast Range, the National Forest, and ecoregions for the entire study region. highest elevation band received class 3 designation. In bSee Table 2.

Conservation Biology Volume 18, No. 2, April 2004 Lipow et al. Genetic Gap Analysis for Forest Trees 421 of seed-zone boundaries. These elevation bands included adequacy of conservation of genetic resources for noble limited areas toward the margin of a seed zone, with many fir. This area has the northernmost, coastal populations of individuals at the same elevation effectively conserved in the species. Here, noble fir is found as scattered individ­ an adjacent seed zone. uals and in small stands. The closest protected noble fir Thirty-three strata were identified as having Douglas-fir occurs at high elevations in Saddle Mountain State Park in well protected in status 1 and 2 protected areas com­ northern Oregon. Willapa Hills populations have the po­ bined, but not in status 1 protected areas alone (class tential to have diverged genetically due to the effects of 2). Fourteen of these represented either the highest or isolation, genetic drift, and natural selection. The only ex lowest elevation sites in a seed zone, included limited situ genetic resources for these populations are found in area, or lay along a zone border where the same eleva­ operational seed stores held by the Weyerhaeuser Com­ tional band in the adjacent zone was assigned to class pany, the Washington Department of Natural Resources, 1. Two class 2 seed-zone-by-elevation bands contained a and The Campbell Group. These are not presently man­ protected area that was bisected by the seed-zone bor­ aged as gene archives. der. Had the zone boundaries included the entire pro­ Increased conservation of Willapa Hills noble fir tected area, these strata would have ranked in class 1. through either ex situ or in situ measures offers several po­ Land designated as late-successional reserve comprised tential advantages. In several European countries where the majority of the protected area in seven other class noble fir is grown commercially for boughs, the Willapa 2 combinations of seed-zone-by-elevation bands. For five Hills is a preferred provenance (U. Nielson, personal com­ class 2 ecoregions, the seed zone with the most similar munication). Tree breeders in Germany have established geography ranked in class 1. Four other class 2 ecoregions a clone bank in response to their concerns over in situ overlapped with seed zones that were variously assigned conservation of Willapa Hills populations, but it has only a to classes 1–3. few selections (Ruetz et al. 1990; W. Ruetz, personal com­ munication). As the bough industry grows in Oregon and Washington, additional Willapa Hills selections may yield Discussion economic benefits. Moreover, geographically peripheral and isolated populations deserve high conservation prior­ The gap analysis proved an effective method for evalu­ ity because they may be important to species migration, ating genetic resource conservation for the forest trees especially in response to global climate change (Lesica & we studied. Genetic resources for Douglas-fir and noble Allendorf 1995). fir were well protected in situ throughout much of the Our gap analysis revealed a possible in situ genetic re­ study area. This conclusion holds regardless of whether source gap for Douglas-fir in the southern Puget lowlands, seed zones or ecoregions were used to stratify the distri­ especially at the highest elevations. This area is heavily bution of species into units of genetic conservation. By forested, and Douglas-fir is ubiquitous throughout. Refor­ well protected we mean that at least 5000 reproductive- estation with local seed is especially important to gene age individuals were growing on sites in each stratum conservation here, given the paucity of protected land. that were unlikely to be harvested during the next sev­ Hundreds of selections from the southern Puget lowlands eral decades. In most strata, the number of protected trees are located in genetic tests and comprise a valuable ex was much greater. Additionally, the majority of strata have situ genetic resource (S.R.L., K.V.-B., J.B.S., J.A.H., & C.M., large populations in status 1 protected areas so that, in unpublished data). the unlikely event of future unsustainable logging in late- Other apparent genetic-resource gaps for Douglas-fir re­ successional reserves or other status 2 protected areas, vealed by our analysis occur in the Fort Rock (Deschutes the genetic resources would remain protected. National Forest) and Chiloquin (Winema National For­ Our gap analysis includes as conserved only those trees est) breeding zones. In the Fort Rock breeding zone, growing “naturally” in status 1 and 2 protected areas. most Douglas-fir occupies sites on or near lava flows Many additional genetic resources are conserved in situ that are unlikely to be harvested (R. Evans, personal through application of current forest-management prac­ communication). In the Chiloquin breeding zone, an es­ tices, including natural regeneration and the placement timated 60% or more of the natural Douglas-fir stands of streamside and landscape buffers throughout the man­ have not been logged previously, and future harvesting aged landscape. Reforestation with wild stand seedlots is unlikely because mistletoe has reduced their economic and seed-orchard seed of appropriate population size and value (S. Puddy, personal communication). Wildfire poses from the local area also ensures the maintenance of ge­ the biggest potential threat to the Chiloquin populations, netic diversity. Additionally, there are extensive regional because several large fires could eliminate them. The USFS genetic resources in ex situ forms, including progeny holds seed stores for the Chiloquin zone, however, that tests, seed orchards, and seed stores. could be used for reforestation. The Willapa Hills of southwestern Washington is the A disjunct population of Douglas-fir occurring on the one area where we advise further consideration of the Fremont National Forest in south-central Oregon was not

Conservation Biology Volume 18, No. 2, April 2004 422 Genetic Gap Analysis for Forest Trees Lipow et al. included in the gap analysis. It is in an area known as study (Sorenson et al. 1990) plus a few provenance tests the Punchbowl, approximately 110 km east of the next done in other countries (Randall & Berrang 2002). Hence, closest known stand. This population consists of approx­ the noble fir seed zones might best be considered first ap­ imately 2000 individuals of all ages scattered across an es­ proximations. More information, including genecological timated 50 ha. The Fremont National Forest is committed and allozyme studies, was available to direct delineation to protecting this presumably unique genetic resource of Douglas-fir seed zones. in situ (D. Stubbs, personal communication) and stores The gap analysis done with ecoregions is intended to seed from 29 parent trees. The population is potentially complement and add to the one done with seed zones. threatened by wildfires and competition from true firs. Ecoregions are widely used in Oregon and Washington The accuracy and resolution of the tree-distribution for demarcating areas of similar environmental and eco­ maps largely determine the robustness of our gap anal­ logical characteristics (Omernik 1995). They can serve as ysis. The data necessary to generate high-resolution tree- a surrogate for data on genetic structure if genetic struc­ distribution maps is not yet available for many forested ture is well correlated with environmental and ecological regions. Our study area, however, contains a high pro­ characteristics. Another reason for running the gap anal­ portion of public land and has been subject to extensive ysis with ecoregions is that various U.S. federal and state mapping of vegetation and landscape features. We expect agencies use them in conservation assessments. Their the distribution maps to be most accurate in protected ar­ use should therefore facilitate the integration of these re­ eas, at least those on federal lands, because this is where sults with those from analyses of other ecosystem com­ the ecology plots used to calibrate the PNV-model are ponents. concentrated. We suspect that many of the map errors that do occur stem from problems with the underlying plant-association group and vegetation layers rather than Acknowledgments from miscoding in the associated tree-distribution tables, because Douglas-fir and noble fir are indicator species Organizations that contributed to the Pacific North­ for many plant-association groups and vegetation types west Forest Tree Gene Conservation Group are Boise (Hall 1998; Kilsgaard 1999). The accuracy of the tree- Cascade, Olympic Resource Management, the Oregon distribution maps was lowest in southwestern Oregon, Department of Forestry, Oregon State University, The Tim­ where they were based on the relatively poor-resolution ber Company, the U.S. Forest Service (Region 6, Pacific Oregon GAP coverage. Northwest Research Station, and State and Private), the For most of the study area, the distribution maps re­ U.S. Bureau of Land Management, the Washington De­ flected expected tree distributions under theoretical cli­ partment of Natural Resources, Weyerhaeuser Company, max conditions. We assumed that the actual distributions and Willamette Industries. We thank C. Chappell of the were equivalent to these theoretical climax distributions Washington Natural Heritage Program for reviewing the in protected areas. Because of natural disturbance and tree-distribution maps and J. Ohmann of the Pacific North­ human activities, this assumption was surely violated in west Research Station for providing compiled plot data some places, adding a source of error to our analysis. In from the Northwest Region Current Vegetation Survey. particular, late-successional reserves, designated status 2 L. Riggs, W. Libby, and R. Burdon initially developed the and a large component of the total protected area, varied gap analysis concept for conserved genetic resources in considerably in the amount of late-successional and old- forest trees. We also thank P. Berrang, C. Dean, R. Evans, growth forest they contained. In some, past management J. Hamlin, and N. Mandel for helpful comments on the practices involved planting of Douglas-fir or noble fir. manuscript. The usefulness of the genetic gap analysis is also in­ fluenced by the stratification used to subdivide species distributions into populations for conservation. An ideal Literature Cited stratification would be based on a thorough assessment of Environmental Systems Research Institute (ESRI). 1999. ARC/INFO a species’ genetic variability and structure, with emphasis user’s manual. ESRI, Redlands, California. given to variation in adaptive traits (Libby & Critchfield Environmental Systems Research Institute (ESRI). 2000. ArcView Spa­ 1987; Eriksson 1995). Because genetic knowledge was tial Analyst white paper. ESRI, Redlands, California. Also available from http://www.esri.com/library/whitepapers/pdfs/avspanal.pdf incomplete for the study species, we conservatively em­ (accessed July 2003). ployed two independent stratifications, seed and breed­ Eriksson, G. 1995. Which traits should be used to guide sampling for ing zones and ecoregions, to increase the likelihood of gene resources? Pages 349–358 in P. Baradat, W. T. Adams, and G. detecting all genetic-resource gaps. Muller-Starck, editors. Population genetics and genetic conservation When developing seed zones, Randall (1996) and of forest trees. SPB Academic Publishing, Amsterdam. Forest Ecosystem Management Assessment Team (FEMAT). 1993. For­ Randall and Berrang (2002) incorporated much of the est ecosystem management: an ecological, economic, and social as­ accumulated genetic information about each species. For sessment. U.S. Forest Service and U.S. Bureau of Land Management, noble fir, however, this was limited to one 3-year nursery Washington, D.C.

Conservation Biology Volume 18, No. 2, April 2004 Lipow et al. Genetic Gap Analysis for Forest Trees 423

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