Prepared in cooperation with the Hawaiÿi Cooperative Studies Unit, University 

of Hawaiÿi at Hilo 

Mapping Plant Species Ranges in the Hawaiian Islands—

Developing a Methodology and Associated GIS Layers 

By Jonathan P. Price, James D. Jacobi, Samuel M. Gon, III, Dwight Matsuwaki, Loyal Mehrhoff, Warren Wagner, 

Matthew Lucas, and Barbara Rowe 

Open-File Report 2012–1192

U.S. Department of the Interior 

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2012

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Suggested citation:

Price, J.P., Jacobi, J.D., Gon, S.M., III, Matsuwaki, D., Mehrhoff, L., Wagner, W., Lucas, M., and Rowe, B.,

2012, Mapping plant species ranges in the Hawaiian Islands—Developing a methodology and associated 

GIS layers: U.S. Geological Survey Open-File Report 2012–1192, 34 p., 1 appendix (species table), 1,158 

maps, available at http://pubs.usgs.gov/of/2012/1192/.

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endorsement by the U.S. Government.

Although this report is in the public domain, permission must be secured from the individual 

copyright owners to reproduce any copyrighted material contained within this report.
iii

Contents

Executive Summary .........................................................................................................................................................1

Introduction ......................................................................................................................................................................1

Climate Zone Classification .............................................................................................................................................2

Moisture Availability Index ...............................................................................................................................................3

Moisture Zone Map..........................................................................................................................................................6

Adaptation of the Moisture-Zone Map to Species Distributions .......................................................................................7

Young Lava Substrate Areas .........................................................................................................................................11

Biogeographic Regions..................................................................................................................................................13

Human Impact................................................................................................................................................................17

Additional Factors Influencing Species Ranges.............................................................................................................20

Species-Range Mapping................................................................................................................................................20

Applications of Estimated-Range Maps .........................................................................................................................21

Facilitating Field Surveys ...........................................................................................................................................21

Restoration Efforts .....................................................................................................................................................21

Studies of Range Size and Rarity ..............................................................................................................................29

Studies of Biodiversity................................................................................................................................................29

Conservation Planning ...............................................................................................................................................29

Invasive Species Management ..................................................................................................................................30

Summary and Future Modeling Efforts ..........................................................................................................................30

Acknowledgments..........................................................................................................................................................30

References Cited ...........................................................................................................................................................31

Appendix. Modeled Historic Range Maps for Hawaiian Vascular Plant Species...........................................................34

Figures

Figure 1. Elevational profile of potential evapotranspiration (PET). Modified from Bean and others (1994)...............5

Figure 2. Comparison of estimated moisture availability index (MAI) surface with mapped vegetation from Jacobi 

(1989). Areas of coincidence: orange, Dry areas; green, Mesic areas; and Dark Blue, Wet areas. Areas of 

disagreement are colored according to which combination of designations that were given. Areas in gray were 

not covered by Jacobi’s maps. Locations of rain gauges are shown for reference. .....................................................6

Figure 3. Approximate precipitation and elevation values used to define seven moisture zones used in this study. 

Zones are defined as follows: Zone 1, Arid; Zone 2, Very Dry; Zone 3, Moderately Dry; Zone 4, Seasonal Mesic; 

Zone 5, Moist Mesic; Zone 6, Moderately Wet; Zone 7, Very Wet. Sites in middle elevations may be in wetter 

moisture zones than areas that have comparable rainfall at higher or lower elevation, a function of depressed 

PET in middle elevations (fig. 1) that results in higher available moisture. Zonal boundaries only extend to 

precipitation-elevation combinations that exist; for example, no location exists above 2,300 m that receives more 

than 3,000 mm precipitation. Note that drier zones are more narrowly defined, in part, because areas that receive 

little rainfall are spatially extensive and, thus, more finely subdivided and, in part, because these are critical 

moisture thresholds that affect plant-species ranges. ..................................................................................................8

Figure 4. Moisture zones on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, Länaÿi, Maui, and Kahoÿolawe...................................9

Figure 5. Moisture zones on island of Hawaiÿi...........................................................................................................10

Figure 6. Areas of young lava substrates on Maui and Hawaiÿi. ...............................................................................14

Figure 7. Biogeographic regions on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, Länaÿi, Maui, and Kahoÿolawe. ....................15

Figure 8. Biogeographic regions on island of Hawaiÿi. ..............................................................................................16

Figure 9. Habitat-quality regions on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, Länaÿi, Maui and Kahoÿolawe. .....................18

Figure 10. Habitat-quality regions on island of Hawaiÿi. ..............................................................................................19
iv

Figure 11. Habitat quality across modeled range of Sadleria cyatheoides on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, 

Länaÿi, Maui, and Kahoÿolawe. This species is known from Mesic and Wet habitats (moisture zones 4 through 

7) across wide elevational range on many islands; it also extends into dryer areas in upper elevations on Maui 

and Hawaiÿi (Upland Dry Zone) but does not extend into drier habitats at lower elevations. Status of habitat for 

this species reflects commonly seen pattern for upland Wet/Mesic species in which much of estimated natural 

range remains in High- or Medium-quality habitat......................................................................................................23

Figure 12. Habitat quality across modeled range of Sadleria cyatheoides on island of Hawaiÿi. ................................24

Figure 13. Habitat quality across modeled range of Erythrina sandwicensis on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, 

Länaÿi, Maui, and Kahoÿolawe. This species is known from Arid to Seasonal Mesic habitats (moisture zones 1 

through 4) at low elevations on many islands; it also extends into Moist Mesic areas (Zone 5) along coast but not 

inland. Status of habitat for this species is typical for species restricted to drier lowland areas where much of 

estimated natural range is Medium- or Low-quality habitat. .......................................................................................25

Figure 14. Habitat quality across modeled range of Erythrina sandwicensis on island of Hawaiÿi..............................26

Figure 15. Habitat quality across modeled range of Chamaesyce kuwaleana, restricted to Oÿahu. ...........................27

Figure 16. Habitat quality across modeled range of Cyanea tritomantha, restricted to island of Hawaiÿi. This 

species is known from only a few biogeographic regions on one island, Hawaiÿi. Darker colors (+) show areas 

where Cyanea tritomantha has been recorded; lighter colors (–) depict areas where it has not been recorded. 

Many species exhibit this pattern in which part of island may have appropriate habitat for a species, but that 

species has never been recorded there. In some cases, a species is naturally restricted; in other cases, there 

has been insufficient sampling in its potential habitat.................................................................................................28

Tables

Table 1. Moisture availability index (MAI) values and approximate median annual precipitation (MAP) 

cutoff-zone values at different elevation boundaries of primary moisture zones...................................................... 4

Table 2. Climate zones in Hawaiian Islands, as adapted in plant-species database............................................. 11

Table 3. Percent “sparse” or “very sparse” vegetation cover according to Hawaiÿi Gap Analysis Program 

land-cover map within each substrate-age-by-moisture-class combination. .......................................................... 13

Table 4. Biogeographic regions for case-study species......................................................................................... 22

Table 5. Habitat parameters for case-study species.............................................................................................. 22
1

Mapping Plant Species Ranges in the Hawaiian Islands—

Developing a Methodology and Associated GIS Layers

By Jonathan P. Price1, James D. Jacobi2, Samuel M. Gon, III3, Dwight Matsuwaki4, Loyal Mehrhoff5, Warren 

Wagner6, Matthew Lucas1, and Barbara Rowe1

Executive Summary

This report documents a methodology for projecting the geographic ranges of plant species in the 

Hawaiian Islands. The methodology consists primarily of the creation of several geographic information 

system (GIS) data layers depicting attributes related to the geographic ranges of plant species. The most 

important spatial-data layer generated here is an objectively defined classification of climate as it 

pertains to the distribution of plant species. By examining previous zonal-vegetation classifications in 

light of spatially detailed climate data, broad zones of climate relevant to contemporary concepts of 

vegetation in the Hawaiian Islands can be explicitly defined. Other spatial-data layers presented here 

include the following: substrate age, as large areas of the island of Hawaiÿi, in particular, are covered by 

very young lava flows inimical to the growth of many plant species; biogeographic regions of the larger 

islands that are composites of multiple volcanoes, as many of their species are restricted to a given 

topographically isolated mountain or a specified group of them; and human impact, which can reduce 

the range of many species relative to where they formerly were found. Other factors influencing the 

geographic ranges of species that are discussed here but not developed further, owing to limitations in 

rendering them spatially, include topography, soils, and disturbance. A method is described for 

analyzing these layers in a GIS, in conjunction with a database of species distributions, to project the 

ranges of plant species, which include both the potential range prior to human disturbance and the 

projected present range. Examples of range maps for several species are given as case studies that 

demonstrate different spatial characteristics of range. Several potential applications of species-range 

maps are discussed, including facilitating field surveys, informing restoration efforts, studying range 

size and rarity, studying biodiversity, managing invasive species, and planning of conservation efforts.

Introduction

The Hawaiian Islands are home to nearly 1,200 native species of vascular plants, a large 

proportion of which either are listed as endangered, are candidates for such a listing, or are species of 

concern (U.S. Fish and Wildlife Service, 2012). A majority of these are restricted to a single island or 

are limited by habitat (Price, 2004); however, nonnative species now outnumber native species (Wagner 

and others,1990; Wagner and Herbst, 1999), and many nonnative species are invasive threats to native 

ecosystems (Cuddihy and Stone, 1990; Staples and Cowie, 2001). The ranges of many native species 

have been summarized in their taxonomic descriptions (especially those by Wagner and others, 1990). 

Species that are important components of forest canopies have been mapped using combinations of 

 1 University of Hawai'i, Hilo

2 U.S. Geological Survey

3 The Nature Conservancy of Hawai`i

4 Hawai`i Biodiversity and Mapping Program, University of Hawai`i, Honolulu

5 U.S. Fish and Wildlife Service

6 National Museum of Natural History, Smithsonian Institution
2

fieldwork and aerial photography (Jacobi, 1989). Still other species, especially rare ones, have had 

specific locations mapped, most notably by the Hawaiÿi Natural Heritage Program (now the Hawaiÿi 

Biodiversity and Mapping Program) and the U.S. Fish and Wildlife Service; however, no single schema

as yet exists for estimating geographic ranges that can be applied to all vascular plant species.

The most obvious approach to determining the geographic range of a given species would be to 

simply map its known locations; however, any mapping effort that is limited to documenting where 

species have been reliably recorded may prove problematic in several ways. First, widespread species 

are found at far too many locations to record them all, and, thus, only a subset of locations can be 

recorded with a reasonable effort. On the other hand, many rare species are known only from very 

scattered locations, and, thus, it would be difficult to assess their distributions in poorly explored areas.

Finally, historically known locations may not fully represent where a species lived prior to widespread 

human disturbance. If the full natural range of a given species could be assessed, that assessment might 

offer important clues as to the ecological context in which a species evolved, as well as provide a 

credible basis for its potential restoration at a site. Therefore, an approach applicable to all species would 

use reasonable amounts of data for each species in order to extrapolate its geographic range in the 

broadest sense possible.

This report describes a methodology for projecting the geographic ranges of plant species in the 

Hawaiian Islands. The methodology primarily consists of the creation of several GIS data layers that 

depict attributes related to the geographic ranges of plant species. These layers include (1) climate 

zones, (2) young lava-substrate areas, (3) biogeographic regions, and (4) degrees of human impact. A 

specially constructed database then relates species locations to these GIS layers, leading to estimations 

of a species’ potential geographic range.

The most important spatial-data layer described here is an objectively defined classification of 

climate as it pertains to the distribution of plant species. By examining previous zonal-vegetation 

classifications in light of spatially detailed climate data, broad zones of climate relevant to contemporary 

concepts of vegetation in the Hawaiian Islands are explicitly defined. A second spatial-data layer defines 

substrate age, as large areas of the island of Hawaiÿi, in particular, are covered by very young lava flows, 

which are inimical to the growth of many plant species. The third spatial-data layer divides larger 

islands, which are composites of multiple volcanoes, into definable biogeographic regions, as many 

species are restricted to a given topographically isolated mountain or a specified group of them. A final 

spatial-data layer depicts human impact, which can reduce the range of many species relative to where 

they formerly were found. Several other factors that influence the geographic ranges of species, 

including topography, soils, and disturbance, are discussed here but not developed further, owing to 

limitations in rendering them spatially.

Climate Zone Classification

Climate in the Hawaiian Islands is extremely variable: precipitation ranges from 250 mm to over 

10,000 mm, and temperature regimes range from tropical to alpine (Giambelluca and Schroeder, 1998).

Hawaiian vegetation has been described in terms of climate since the first botanical explorations after 

European contact. Hillebrand (1888) divided vegetation into four elevation zones but described the 

variation of their breadth as depending on whether they are on windward (wet) or leeward (dry) slopes.

A more detailed vegetation description by Rock (1913) similarly defined vegetation according to 

elevation and windward (wet) versus leeward (dry) aspects, in addition to including descriptions of 

major component species. In the first of these vegetation classifications to include potential vegetation 

maps, Ripperton and Hosaka (1942) used the dominance of characteristic native and nonnative species 

to define several major vegetation zones. In the most recent comprehensive vegetation classification,

Gagné and Cuddihy (1990) not only considered different moisture and elevation zones but defined them 

somewhat explicitly; although it did not include a vegetation map, its exhaustive descriptions of 
3

different sites throughout the state permit many areas to be attributed to a give vegetation type. A series 

of vegetation maps by Jacobi (1989) served as a basis for the Gagné and Cuddihy (1990) classification; 

using a combination of extensive fieldwork from the Hawaiian Forest Bird Survey (HFBS) and aerial 

photographs, these maps attribute finely resolved areas to detailed vegetation types according to 

moisture zone, dominant cover, stature, and understory composition. The maps, however, primarily 

cover upland areas, particularly areas that include forest bird habitat, as these were the areas surveyed

extensively by the HFBS. In addition, the maps only cover the islands of Länaÿi, Molokaÿi, Maui, and 

Hawaiÿi. A map by Gon and others (1998) that depicted potential vegetation also attempted to 

incorporate other influences in addition to climate, such as substrate, topography, and hydrography, for a 

generalized vegetation map for all islands, and these latter three vegetation classifications are used, and 

built upon, here.

The first step in generating a comprehensive map of climate zones is to rectify the functional 

definition of each zone with the perception of these on the ground. To do this, a median annual 

precipitation (MAP) map by Giambelluca and others (1986) was employed. This map, which consisted

of isohyet lines, was available in digital form from the State of Hawaiÿi. From this map a continuous 

surface (with values for each 30-m-square cell in a grid) was interpolated using ArcInfo’s TopoGrid 

command (Environmental Systems Research Institute, 2005), which accommodates line-data input, 

unlike other interpolation functions that require point-data input. Using this new MAP surface, a 

preliminary assessment was conducted of the agreement between Gagné and Cuddihy’s (1990) moisture 

classes with maps created by Gon and others (1998) and Jacobi (1989). Initially, Gagné and Cuddihy 

defined the Dry Zone as being less than 1,200 mm annual rainfall; the Mesic Zone, between 1,200 and 

2,500 mm annual rainfall; and the Wet Zone, greater than 2,500 mm annual rainfall; however, they did 

add itemized exceptions to these as a function of substrate or other influences in sections on individual 

types. This study depicts the mean annual precipitation (MAP) surface as the primary break points 

(1,200 mm for the Dry-Mesic boundary; 2,500 mm for the Mesic-Wet boundary), producing a map of 

the three moisture zones according to precipitation. When comparing this precipitation-based moisturezone map to other vegetation maps, a number of disparities were evident. Most notable was the fact that 

many areas that are considered Mesic on vegetation maps (Jacobi, 1989; Gon and others, 1998), such as 

the south slope of Haleakalä on Maui and the Kökeÿe region on Kauaÿi, receive somewhat less than 

1,200 mm of precipitation annually.

Moisture Availability Index

A more detailed approach to the nature of moisture availability in different climates 

(Thornthwaite, 1948) assessed moisture availability as a function of annual precipitation and also 

potential evapotranspiration (PET), which represents the moisture demand of the atmosphere as a 

function of temperature and humidity and is strongly driven by the amount of incoming solar radiation.

Bean and others (1994) found that middle elevations in the Hawaiian Islands exhibited lower PET 

values because they lie within the cloud belt and, thus, are high enough in elevation to have lower 

temperatures than sea level but not so high as to exceed the trade-wind inversion, above which clouds 

generally do not form and insolation is comparatively high (Giambelluca and Schroeder, 1998). It also is 

highly likely that strong variation in PET values exist, depending on aspect to prevailing trade winds and 

local topographic effects that influence cloud cover; however, at present there are insufficient PET data 

to map this variation in any detail.

Juvik and others (1978) considered a function of moisture inputs (through precipitation) and 

moisture demands (through evapotranspiration) in order to determine the major components of water 

balance. Thus, they subtracted PET values from MAP values to determine areas of potential moisture 

surplus and deficit on the island of Hawaiÿi. Another study by Juvik and Tango (2003) established a 

more detailed profile of precipitation, including fog-drip inputs, and PET values to consider moisture 
4

availability on the leeward side of the island of Hawaiÿi. Following a similar methodology, this study 

considered the difference between MAP and PET values (calculated as MAP minus PET). The resulting 

moisture availability index (MAI) better reflects variation in available moisture than precipitation alone 

and was used as a primary framework to compare with vegetation maps. Breakpoints were chosen in the 

MAI values that best fit the concepts of the Dry, Mesic, and Wet vegetation zones in Jacobi’s (1989) 

maps. A breakpoint was chosen between Dry and Mesic that corresponds to the often-cited classification 

by Holdridge (1967), in which tropical dry forest climate is defined by those areas where annual PET 

values exceed MAP values (where MAI <0). A breakpoint was chosen between Mesic and Wet that 

approximates the value given by Gagné and Cuddihy (1990); although they defined this breakpoint at 

2,500 mm MAP, the breakpoint was set at the MAI value where 2,500 mm of rainfall is received at 

1,000 m elevation (where MAI=1,661 mm). Table 1 gives the moisture-balance values and the 

precipitation cutoffs at different elevations. 

Table 1. Moisture availability index (MAI) values and approximate median annual precipitation (MAP) cutoff-zone

values at different elevation boundaries of primary moisture zones.

[Note that Dry-Mesic boundary is where MAP value is equal to potential evapotranspiration (PET) value (MAI=0).

Precipitation cutoffs are given for several elevations. For any given moisture-zone boundary, lowest precipitation-cutoff 

value is at 1,000 m where PET is lowest. At lower or higher elevations, more precipitation is needed to balance out higher 

PET values there. Cutoff values for Dry-Mesic and Mesic-Wet boundaries are not given above 2,500 m elevation because all 

areas higher than that are within Dry Zone]

Moisture-zone 

boundary

MAI value 

(mm)

MAP value 

(mm) at 

0 m

MAP value 

(mm) at 

500 m

MAP value 

(mm) at 

1,000 m

MAP value 

(mm) at 

1,500 m

MAP value 

(mm) at 

2,000 m

MAP value 

(mm) at 

2,500 m

Dry-Mesic 0 1,300 1,000 800 900 1,050 1,500

Mesic-Wet 1,661 3,000 2,700 2,500 2,600 2,750 3,200

Maps of estimated MAP and PET values were used to estimate MAI values statewide. To 

characterize PET values in different areas, a generalized profile was first derived using data from Bean 

and others (1994) that reflects the somewhat lower PET values at middle elevations (fig. 1). Then a 

statewide digital elevation model (DEM) (standardized to a 30-m cell size and a 1-m vertical resolution) 

was used to attribute PET values to areas at different elevations. The resulting surface represents an 

estimate of PET across all islands. In reality, it is certain that PET values vary by island, by aspect with 

respect to trade winds, and by other factors; however, at present not enough measurements of PET 

values have been made in different areas to be able to map this spatial variability in detail. Nonetheless, 

the projected PET surface represents a rough approximation of spatial variation (with respect to 

elevation) and can be combined with precipitation values to better represent available moisture. By 

subtracting the estimated PET value from the estimated MAP value for each grid cell, a surface that 

estimates MAI statewide was generated. Then, using the MAI-value breakpoints defined above, the 

estimated MAI surface (representing MAP minus PET values) was partitioned into the three primary 

moisture zones (Dry, Mesic, and Wet).

The partitioned MAI surface was assessed using Jacobi’s (1989) map, as it represents a 

vegetation classification derived from field observations of vegetation characteristics and is largely 

independent of climate. Jacobi’s (1989) map was converted into a 30-m grid coverage of Dry, Mesic, 

and Wet Zones and then compared to the zones depicted in the estimated MAI surface. The MAI surface 

agreed with Jacobi’s map in 66 percent of grid cells; was drier in 10 percent of grid cells; and was wetter 

in 23 percent of grid cells. Areas classified as unvegetated by Jacobi (1989) were not considered, as

these represented lava flows across various moisture zones. Figure 2 shows a portion of Molokaÿi as an 

example of how the maps differ.
5

Figure 1. Elevational profile of potential evapotranspiration (PET). Modified from Bean and others (1994). 

Several possible reasons may explain why a given location is classified differently according to 

the MAI surface than it is in Jacobi’s (1989) map. First, the MAI surface is derived from interpolated 

precipitation maps that are fairly generalized and that, in some cases, may differ somewhat from actual 

local climate-station data. In other cases, comparatively few climate stations exist, and interpolated 

precipitation values may not accurately reflect actual MAP values. This absence of climate data is 

particularly acute for remote areas; however, many such areas lie within the regions covered by Jacobi’s 

(1989) map because they represent large tracts of native vegetation. Thus, where climate data is clearly 

lacking, Jacobi’s vegetation map may more accurately represent available moisture than the estimated 

MAI surface. 

In other areas that have good climate data, however, Jacobi’s (1989) map differs markedly from 

the estimated MAI surface. Such discrepancies typically are due to at least one of two situations. The 

first situation involves areas of relatively young lava substrates. One of the criteria that indicate Wet 

vegetation is the relative cover of tree ferns; however, even in areas that receive ample precipitation, 

relatively young lava substrates largely preclude their growth, and so the area is classified as Mesic in 

Jacobi’s map. Similarly, a more open canopy or shrub cover is an indicator of Dry vegetation in many 

areas of Jacobi’s map, even though these areas receive sufficient rainfall to classify as Mesic; again, 

however, this typically involves areas of young lava substrates. Because of this, young substrate areas 

are treated in a separate section for this study. The second situation where Jacobi’s (1989) map classifies 

areas as drier than the estimated MAI surface are areas of habitat degradation, particularly by introduced 

ungulates. For example, areas that are Wet according to the estimated MAI surface but where cattle 

grazing has disturbed the understory and reduced the cover of tree ferns are classified as Mesic in 

Jacobi’s map. Similarly, areas that are open or that even have no tree canopy and considerable cover by 

pasture grass are considered Dry in Jacobi’s classification, despite reliable climate data that places them 

in the Mesic or even Wet climate zone. 
6

Figure 2. Comparison of estimated moisture availability index (MAI) surface with mapped vegetation from 

Jacobi (1989). Areas of coincidence: orange, Dry areas; green, Mesic areas; and Dark Blue, Wet areas. Areas 

of disagreement are colored according to which combination of designations that were given. Areas in gray were 

not covered by Jacobi’s maps. Locations of rain gauges are shown for reference. 

In order to rectify differences between Jacobi’s map and the estimated MAI surface, major areas 

where the two differ were assessed along with local climate data, when available. In areas outside those 

covered by Jacobi’s maps, designations from the map by Gon and others (1998) and descriptions in 

Gagné and Cuddihy (1990), as well as incidental observations, were used. In many instances, data from 

individual climate stations provide a more reliable local estimate of MAI than that from the estimated 

MAI surface, which can be inaccurate owing to the generalized nature of the MAP- and PET-value 

maps. 

Moisture Zone Map 

After resolving differences between the estimated MAI surface and other sources, a new 

moisture-zone map was created on which each of the three primary moisture zones was further 

subdivided, and each new zone was numbered from 1 to 7, from driest to wettest: 

• The Wet Zone was divided into two zones: areas that have an MAI value greater than 3,161 

(1,500 mm above the Wet-Mesic boundary) constitute the Very Wet Zone (Zone 7), and areas 

that have an MAI value less than 3,161 constitute the Moderately Wet Zone (Zone 6). 
7

• The Mesic Zone was divided into two zones: areas that have an MAI value greater than 861 

constitute the Moist Mesic Zone (Zone 5), and areas that have an MAI value less than 861 

constitute the Seasonal Mesic Zone (Zone 4). 

• The Dry Zone, because it includes far more area than the Wet or Mesic Zones, was subdivided 

into three new zones: areas that have an MAI value between 0 and -389 constitute the 

Moderately Dry Zone (Zone 3); areas hat have an MAI value between -389 and -689 constitute

the Very Dry Zone (Zone 2); and areas that have an MAI value less than -689 constitute the Arid 

Zone (Zone 1). 

The combinations of MAP values and elevation estimated to place a site within a given zone are 

depicted graphically in figure 3.

To produce the new moisture-zone map, lines were digitized according to whichever data source 

was considered the most reliable for a given region. In areas where the estimated MAI surface is 

considered reliable (in other words, where climate data are reliable), boundaries between moisture zones 

were placed according to appropriate breakpoints in the MAI values. In areas where the estimated MAI 

surface was not reliable, other sources (for example, Jacobi, 1989; Gon and others, 1998) were used to 

demarcate zonal boundaries. Lines were drawn so as to be smooth and generalized (rather than depicting 

a false sense of precision by following sinuous boundaries demarcated by a given source) at a scale of 

1:70,000. The result is a map of seven moisture zones, each representing a discrete zone of moisture 

availability for the main Hawaiian Islands (figs. 4, 5).

Adaptation of the Moisture-Zone Map to Species Distributions

The moisture-zone map was adapted to reflect patterns in species distributions. First, many 

species are known from several moisture zones but are restricted to areas near the coast; this is different 

from being restricted to low elevations because such species are frequently known at over 100 m 

elevation on sea cliffs but are not found at comparable elevations inland. Other species have more 

extensive distributions along the coast than they do inland. For example, Erythrina sandwicensis has 

been recorded in Zones 1 to 5 near the coast but is limited to Zones 1 to 4 inland. To depict this coastal 

zone on the habitat maps, a buffer of 500 m was generated from the coastline; those areas falling within 

the buffer are classified as coastal, and they too are divided among the seven climate zones. This 

distance was chosen because, although the coastal zone certainly varies in width and in the influences of 

salt spray, wind, and floating water table (the Ghyben-Herzberg effect), the area within 500 m likely 

contains the vast majority of sites with these conditions. 

Another adaptation of the moisture-zone classification is a special consideration of the three 

driest zones (1 to 3) at higher elevations. These zones are restricted to elevations below 1,000 m on all 

islands except on east Maui and on Hawaiÿi, where extensive areas that have drier climates are present at 

higher elevations. These upland Dry regions are largely separate from lowland Dry regions: on Maui, 

they are entirely disjunct, and on the island of Hawai‘i, a comparatively small amount of area at middle 

elevations connects upland and lowland Dry regions. In many cases, species that are otherwise restricted 

to the Mesic and Wet Zones inhabit one of the three Dry Zones at higher elevations on Maui and 

Hawaiÿi. This may reflect the fact that these higher elevation areas experience lower daytime high 

temperatures and, therefore, lower heat stress than lowland Dry regions. This may also be due to 

moisture input from fog at higher elevations, which may add critical moisture during otherwise dry 

summer months (Juvik and Ekern, 1978; Juvik and Tango, 2003). However, these regions also have very 

poor precipitation records, owing to the large distances between climate stations. For example, the

central plateau of Hawaiÿi has only a few rain gages scattered along its margin, and none in its center.

Therefore, although these dry upland regions can be considered climatically distinct from lower 

elevation dry regions, there is little confidence that boundaries among Zones 1, 2, and 3 are well 

defined. Records of native plant species also are somewhat limited in these areas, adding further 
8

Figure 3. Approximate precipitation and elevation values used to define seven moisture zones used in this 

study. Zones are defined as follows: Zone 1, Arid; Zone 2, Very Dry; Zone 3, Moderately Dry; Zone 4, Seasonal 

Mesic; Zone 5, Moist Mesic; Zone 6, Moderately Wet; Zone 7, Very Wet. Sites in middle elevations may be in 

wetter moisture zones than areas that have comparable rainfall at higher or lower elevation, a function of 

depressed PET in middle elevations (fig. 1) that results in higher available moisture. Zonal boundaries only 

extend to precipitation-elevation combinations that exist; for example, no location exists above 2,300 m that 

receives more than 3,000 mm precipitation. Note that drier zones are more narrowly defined, in part, because 

areas that receive little rainfall are spatially extensive and, thus, more finely subdivided and, in part, because 

these are critical moisture thresholds that affect plant-species ranges.
9

Figure 4. Moisture zones on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, Länaÿi, Maui, and Kahoÿolawe. 
10

Figure 5. Moisture zones on island of Hawaiÿi. 
11

difficulty in the ability to confidently place species within a given moisture zone. For purposes of 

defining species ranges, Zones 1, 2, and 3 were, therefore, combined for areas above 1,250 m. This new 

Upland Dry Zone is considered distinct from Zones 1 to 3 at lower elevations. The final set of zones 

used in the species database is presented in table 2.

Table 2. Climate zones in Hawaiian Islands, as adapted in plant-species database.

Climate zone Moisture zones Islands

Coastal - Arid 1 All islands

Coastal - Very Dry 2 All islands except Länaÿi

Coastal - Moderately Dry 3 All islands except Länaÿi and Kahoÿolawe

Coastal - Seasonal Mesic 4 All islands except Länaÿi and Kahoÿolawe

Coastal - Moist Mesic 5 Kauaÿi, Molokaÿi, Maui, and Hawaiÿi

Coastal - Moderately Wet 6 Molokaÿi, Maui, and Hawaiÿi

Coastal - Very Wet 7 Maui only

Arid 1 All islands

Very Dry 2 All islands

Moderately Dry 3 All islands except Kahoÿolawe

Seasonal Mesic 4 All islands except Kahoÿolawe

Moist Mesic 5 All islands except Niÿihau and Kahoÿolawe

Moderately Wet 6 All islands except Niÿihau and Kahoÿolawe

Very Wet 7 Kauaÿi, Oÿahu, Molokaÿi, Maui, and Hawaiÿi

Upland Dry 1,2,3 Maui and Hawaiÿi only

Young Lava Substrate Areas

Young lava substrates impose several well-known influences on vegetation in the Hawaiian 

Islands. The unweathered nature of most volcanic substrates permits little soil formation and results in a 

high degree of drainage that retains less moisture than weathered substrates (Kitayama and others, 

1995). In addition, younger soils are deficient in nutrients, particularly nitrogen (Crews and others, 

1995). According to a study of several lava flows of varying age within the moderately wet climate zone 

(Kitayama and others, 1995), lava flows younger than 200 years restrict many species and, thus, support 

only very sparse vegetation. However, in drier climate regions, vegetation remains stunted on even 

moderately aged lava flows (Aplet and Vitousek, 1994). The pioneer vegetation associated with young 

lava substrates is likely inimical to the growth of many plant species that cannot tolerate such 

conditions; on the other hand, some species such as Rumex skottsbergii and Scaevola kīlaueae appear to 

prefer this type of vegetation (Wagner and others, 1990).

Although many studies have chronicled the development of vegetation on lava flows within wet 

climates, comparatively little has been done in areas that have a drier climate. Stemmerman and Ihsle 

(1993) demonstrated that in Very Dry, Moderately Dry, and Seasonal Mesic areas (moisture Zones 2 to 

4), vegetation shows marked changes in composition and dominance with increasing age. Most

substrates 3,000 years or older support well-developed vegetation, as opposed to the pioneer vegetation 

on younger flows dominated by either sparse or small ÿÖhiÿa (Metrosideros polymorpha). A study of 

litter production across sites receiving different amounts of rainfall (Austin, 2002) indicated that a site at 
12

Kanikuü Lava Flow, Hawai‘i, which is within the Moderately Dry Zone (Zone 3) and has a substrate age 

of 2,800 years, shows characteristics of a pioneer community when compared to moister sites that have a 

similar substrate age. These characteristics include fewer species, low rates of litter production, low 

foliar-nitrogen concentration, and a dominance by ‘Ohi‘a (which does not dominate on older substrates 

in drier climate zones). 

In summary, it appears that, in the wettest areas, young lava substrates support well-developed 

vegetation within perhaps as little as a few hundred years, whereas in drier areas the process may take as 

many as 3,000 years or more. An exception to this general pattern are the comparatively young, deep 

volcanic-ash substrates, which show species composition and soil characteristics comparable to very 

well developed substrates (Balakrishnan and Mueller-Dombois, 1983; Vitousek and others, 1983). To 

better resolve the general pattern, substrate characteristics were assessed in this study using both 

geologic and climatic GIS maps.

Geologic maps depicting lava-flow age are available for the islands of Hawaiÿi (Wolfe and 

Morris, 1996) and Maui (Sherrod and others, 2006). These maps classify lava age as one of the 

following seven categories: younger than 200 years; 200-750 years; 750-1,500 years; 1,500-3,000 years;

3,000-5,000 years; 5,000-10,000 years; and older than 10,000 years. Some substrates, however, notably 

alluvium, were not given an age designation, although in some cases they represent landslide deposits 

attributable to lava flows of known age. These areas were, therefore, classified according to the most 

likely source of parent material. Regardless of their actual age, areas that have deep ash substrate were 

reclassified into the oldest age class (>10,000 years), owing to the unique characteristics of this substrate 

type. The geologic maps were converted to 30-m grids that contain values representing the seven age 

classes. Then this age-class grid was combined with a 30-m grid of climatic moisture zones (defined 

earlier in this report) to determine the combination of age class and moisture zone at each given location. 

In order to determine which age classes should be designated as young lava substrate for each 

given moisture zone, moisture zones and substrate ages were examined in the context of a land-cover 

classification; this land-cover grid, produced by the Hawaiÿi Gap Analysis Program (HIGAP), is based 

on LandSat Thematic Mapper satellite imagery and represents major structural vegetation types (Gon,

2006). Land-cover classes were then grouped according to those that were considered either unvegetated 

or vegetated with what is considered to be pioneer vegetation (including land-cover classes “Very 

Sparse Vegetation to Unvegetated” and “Sparse ÿÿÖhiÿa/Native Shrub”). For each moisture-zone-bysubstrate-age combination, the proportion of the area covered by sparse vegetation was examined. Areas 

in the arid zone that are associated with alpine habitats (that is, above 3,000 m elevation) were excluded, 

as these consist almost entirely of sparse vegetation, regardless of substrate age. Results are summarized 

in table 3.

A clear trend exists where sparse vegetation makes up large proportions of areas that are young 

substrate age. In the wettest areas (Zones 6 and 7), no age class had a majority of its area covered by 

sparse vegetation; instead, areas within the two wettest zones that were on the youngest substrates (<200 

years) tended to be covered in open ÿÖhiÿa and Uluhe (Dicranopteris linearis), a mat-forming fern. 

Nonetheless, studies from areas with this moisture-substrate combination (Kitayama and others, 1995; 

Aplet and Vitousek, 1994) have indicated that species composition is limited. Starting with the Moist 

Mesic Zone (Zone 5), progressively older lava-substrate age classes are covered primarily (at least 75%) 

by sparse vegetation. At the Arid end of the spectrum (Zone 1), all age classes younger than 3,000 years 

were covered at least 75 percent in sparse vegetation. The 3,000-to-5,000-year-old age class within the 

Arid Zone included nearly as high a proportion of its vegetation covered in sparse vegetation (73%); 

however, much of this area is human modified (the Kailua-Kona region includes the city of Kailua, 

Hawaiÿi, and the resort areas to the north) and, thus, might have had a higher proportion of sparse 

vegetation originally. This pattern is generally in agreement with that of studies of individual sites where 

substrate development takes longer at drier sites. 
13

Table 3. Percent “sparse” or “very sparse” vegetation cover according to Hawaiÿi Gap Analysis Program land-cover 

map within each substrate-age-by-moisture-class combination.

[Age-by-moisture combinations that have more than 75% of their area being sparsely vegetated are designated as young 

substrates and are shown in bold. Areas within Zone 6 and 7 (Moderately Wet and Very Wet) and in the youngest substrate 

age class (<200 years) are also considered young substrate areas because their vegetation is limited in species composition. In 

addition, areas within moisture Zone 1 (Arid) and in the 3,000-to-5,000-year-old substrate age class, although being only 

73% covered in sparse vegetation, are also nominally included]

Age (in years) Moisture 

Zone 1

Moisture 

Zone 2

Moisture 

Zone 3

Moisture 

Zone 4

Moisture 

Zone 5

Moisture 

Zone 6

Moisture 

Zone 7

<200 94 99 98 95 76 58 7

200 – 750 92 99 84 82 39 9 5

750 – 1.500 63 96 75 58 17 3 0

1,500 – 3,000 79 91 58 38 10 2 0

3,000 – 5,000 73 67 29 20 4 1 0

5,000 – 10,000 29 54 22 11 2 3 1

>10,000 6 15 6 6 2 2 2

Certain substrates were considered to be young lava, using the following moisture and age 

criteria: in the Moist Mesic through Wet moisture zones (Zones 5 to 7), substrates that are <200 years 

are considered young lava; in the Seasonal Mesic Zone (Zone 4), <750 years; in the Moderately Dry 

Zone (Zone 3) <1,500 years; in the Very Dry Zone (Zone 2), <3,000 years; and in the Arid Zone (Zone 

1), <5,000 years. These areas represent a large portion of the island of Hawaiÿi and a limited portion of 

Maui, but they are not found on other islands (fig. 6). Although substrate age and climatic moisture are 

primary drivers of rates of succession, the designation given here should be considered as a general 

estimate of soil and vegetation development. Additional factors such as elevation or whether the 

substrate is ÿaÿa or pahoehoe lava may be of comparable importance in determining the ability of species 

to colonize lava flows. These additional factors will require further research.

Biogeographic Regions

By subdividing the Hawaiian Islands into distinct geographic regions, a species’ potential habitat 

can be bracketed by those islands and by portions of islands on which the species has been recorded. 

Isolation of populations on different islands facilitates the evolution of distinct species that are restricted 

in their distribution (Carlquist, 1980; Wagner and Funk, 1995). Furthermore, some islands consist of 

more than one topographically distinct volcanic mountain, promoting further possibilities for geographic 

restriction. Consequently, over 40 percent of native Hawaiian flowering plant species are restricted to a 

single volcanic mountain (Price, 2004).

Following Price (2004), the islands of Oÿahu, Molokaÿi, and Maui were divided into two 

geographic regions, each corresponding to separate volcanic masses. The island of Hawaiÿi was divided 

into its five constituent volcanic mountains (Kohala, Mauna Kea, Hualälai, Mauna Loa, and Kīlauea). In 

addition, Mauna Loa was subdivided into four additional subregions because it covers far more area than 

any other volcanic mountain, and also because its slopes include disjunct areas of certain climate zones. 

The subregions of Mauna Loa include the following: northwest, positioned between Hualälai and Mauna 

Kea; northeast, stretching from Mauna Kea south and including the Mauna Loa part of Hawaiÿi 

Volcanoes National Park; southeast, stretching from the Hawaiÿi Volcanoes National Park boundary to 

the Kaÿü–South Kona District boundary; and southwest Mauna Loa, stretching from the Kaÿü–South 

Kona District to Hualälai. To explicitly define each of these regions, GIS coverages (figs. 7, 8) were
14

Figure 6. Areas of young lava substrates on Maui and Hawaiÿi. 
15

Figure 7. Biogeographic regions on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, Länaÿi, Maui, and Kahoÿolawe. 
16

Figure 8. Biogeographic regions on island of Hawaiÿi. 
17

generated from a composite geology coverage for the island of Hawaiÿi (Wolfe and Morris, 1996), as 

well as from a statewide DEM (USGS open-source data) and a land-parcel-boundary coverage (State of 

Hawaiÿi Office of Planning, 2006). 

Human Impact

Many habitats in the Hawaiian Islands have been severely altered by human activity. Areas that 

have been converted for urban use or intensive agriculture are likely inimical to the vast majority of 

native species. In addition to these areas, many ecosystems in the Hawaiian Islands are now dominated 

by nonnative species (Cuddihy and Stone, 1990; Gagné and Cuddihy, 1990), which probably also 

contribute to the limiting of many native species. On the other hand, certain native species, even some 

rare and endangered species, may persist in habitats that are dominated by nonnative species. A map by 

Gon and others (1998) categorized areas as being generally either native or nonnative dominated. 

To more precisely identify areas where native species may presently be found, a map was 

generated that considers the following three categories of habitat quality: High, areas dominated by 

native vegetation; Medium, areas dominated by nonnative vegetation; and Low, highly modified 

landscapes. The primary source for mapping these three categories is the HIGAP land-cover 

classification (Gon, 2006). The High category includes all HIGAP land-cover classes that are considered 

to be either native dominated or mixed native and nonnative in order to represent those areas that have 

substantial native-species composition. The Medium category includes areas that are dominated by 

nonnative species but are not otherwise intensively developed. This incorporates all nonnativedominated HIGAP land-cover classes. The Low category includes all land-cover classes pertaining to 

urban land, other developed lands, and active cropland. In addition, many areas of former or fallow 

cropland were mapped as grassland or alien forest in the HIGAP land-cover map. These are best 

included in the Low category because they include areas where all native vegetation was removed at one 

time. These areas are different from other nonnative-dominated areas where native species may be more 

likely to have persisted. 

A GIS layer of the agricultural land-use map developed by the State of Hawaiÿi Department of 

Agriculture (1980) was generated into a 30-m grid, and then all cells identified as cropland and other 

intensive agricultural uses were reclassified into the Low-habitat-quality category. In addition, areas 

classified as “Very Sparse Vegetation to Unvegetated” in the HIGAP land-cover map cannot be directly 

attributed to a given habitat quality because they may represent native pioneer vegetation on lava or 

barren sites within a nonnative-dominated area. Therefore, the average habitat-quality value was 

assigned to each unvegetated cell for all cells within a 3 km radius. Owing to limitations in the accuracy 

of the HIGAP land-cover map, the resulting map is still somewhat general but otherwise represents a 

good approximation of habitat quality (figs. 9, 10).

To test whether or not native species tend to be found in areas considered as native dominated on 

the three-level habitat-quality map, a set of point locations that show where rare native plant species are 

known to be found were used. The data, which were compiled by the U.S. Fish and Wildlife Service, 

consist of 5,575 locations and represent over 600 species. Points that had the highest precision were 

selected, and those where the location was overly general (for example, “Koÿolau Mountains”) were 

excluded. The points were then converted to a grid coverage, and the number of locations associated 

with each of the three habitat-quality categories was determined. High-habitat-quality areas make up 

only 46 percent of all land area but include 75 percent of the rare-native-plant-species locations. In 

addition, Medium-habitat-quality areas make up 41 percent of all land area but include just 23 percent of 

the rare-native-plant-species locations, whereas Low-habitat-quality areas make up 13 percent of all land 

area but include less than 2 percent of the rare-native-plant-species locations. In fact, nearly all of the 

rare-native-plant-species locations associated with Low habitat quality represented Abutilon menziesii, a 

peculiar endangered species that persists in former sugar cane fields. The habitat-quality designations,
18

Figure 9. Habitat-quality regions on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, Länaÿi, Maui and Kahoÿolawe. 
19

Figure 10. Habitat-quality regions on island of Hawaiÿi. 
20

therefore, reflect the tendency of native species to be strongly associated with High habitat quality, 

nominally associated with Medium habitat quality, and minimally associated with Low habitat quality.

Additional Factors Influencing Species Ranges

Several other influences on species distributions in the Hawaiian Islands deserve mention, 

although as yet it is not feasible to map them. Different types of topography, including gulches and 

ridges, as well as various aspects with respect to sun, wind, and moisture, certainly favor some species 

while restricting others. Unfortunately, although it is feasible to firmly establish a species within a given 

climate zone, available records often do not consistently contain detailed site information from which a 

trend might be discerned. And although collecting such data for a few species may be possible, this 

would likely prove extremely difficult for the entire vascular flora. In addition, presently available 

DEMs, although they may depict large-scale variations in topography, may not include small-scale 

topographic features. For example, many species either prefer, or are now restricted to, very steep slopes 

and cliff faces; such habitats may be present in fairly small pit craters or cracks that are unlikely to be 

represented at the presently available resolution of DEMs. Another potential influence that could be 

mapped is soils. At present only very coarse and outdated soil maps exist; however, the Natural 

Resources Conservation Service is presently developing a new soils map for the island of Hawaiÿi.

Hydrography is another influence that can be very important in determining suitable habitat but is at 

present difficult to map. Large wetland areas can be mapped, for example, but attributing species only to 

those areas can potentially omit many smaller wetland areas and streambanks that are far from the larger 

wetland bodies, and this would lead to an underestimate of the species range. In the future, these 

potential problem areas might be incorporated into more sophisticated species-distribution models. It 

may also be feasible to build mathematically complex statistical models that are based on trends from 

parameters drawn from detailed point data.

Species-Range Mapping

At present the most effective way to map plant-species ranges in the Hawaiian Islands is by 

demarcating a general bioclimatic envelope within biogeographic regions in which a species is known to 

have been found. To do this, this study builds upon a database of native Hawaiian plant species that 

includes data on the distribution of species by geographic region, major habitat type, and elevation range 

(Price, 2004). These data come from published sources, herbarium specimens, unpublished reports and 

field notes, and targeted field work. The database has been expanded in several ways to accommodate a 

comprehensive species-range mapping program. First, the database now includes data for Hawaiian 

Pteridophytes that are based largely on the recently published flora by Palmer (2002) and also on 

specimens from the Bishop Museum. It has also been modified to explicitly document species in the 

climate zones developed here. Where possible, voucher specimens from specific locations (1) document 

the presence of a species in each applicable climate zone on the zonal map, (2) establish whether it is 

found on young lava substrates, as defined here, and (3) documents its elevation limits. The full

database, derived from that used by Price (2004), contains these data for all native species and also 

includes referenced sources for each data cell.

To generate a map of the estimated range of a given species, the database is used to generate a 

script in Arc Macro Language (AML) that can then be read by a Grid Module of ArcInfo 

(Environmental Systems Research Institute, 2005). This method was favored because a single AML 

script can run a batch process to generate estimated range maps for many species and also because 

problems can be intercepted and amended easily. All layers are converted to a 30-m grid of values. First, 

using layers for climate zones, biogeographic regions, and young lava substrates, as well as a DEM for 

elevation range, the AML script selects out those areas that have values appropriate to that species. This 
21

represents the estimated natural range of the species prior to human modification of habitat. In some 

cases, a species has been recorded in one biogeographic region on a given island but not in another. The 

species range can also be calculated for where it might have been present in regions in which it has not 

been recorded. To examine the status of habitat quality within the estimated natural range of a given 

species, the range can be parsed into areas corresponding to Low, Medium, and High habitat quality.

Thus, a given species range can be considered in several different ways on a particular island on which it 

is known.

To demonstrate how different ways of viewing a range might be practically applied to different 

species, we selected four species to use as case studies, including two widespread species (Sadleria 

cyatheoides and Erythrina sandwicensis) and two rare species (Cyanea tritomatha and Chamaesyce 

kuwaleana). Sample data matrices show presence in biogeographic regions (table 4) and habitat 

parameters (table 5) for the four case-study species. Sample range maps for these case studies, along 

with a description of important patterns, are given in figures 11 through 16. Maps for all species 

modeled can be downloaded using the table in the appendix to this report.

Applications of Estimated-Range Maps

The estimated-range maps generated using the methods described here can be applied to both 

natural history questions and conservation management. They can be used either individually for single 

species applications or collectively for questions pertaining to species assemblages. The following are 

several proposed applications, several of which are presently being developed.

Facilitating Field Surveys

Field biologists often require tools to focus search efforts on species likely to be in a given area. 

Using species-range parameters and associated GIS maps, it is feasible to produce a list of species 

potentially within a given area. Many members of a given genus often are present on an island but exist 

in different geographic regions or different habitats. Field biologists can thus employ the tools 

developed here to help identify species in their survey area. In other cases, surveys for rare species can 

be guided by focusing on those areas where a species is most likely to occur. For example, in the case 

study for Cyanea tritomatha (fig. 16), areas of High habitat quality within the estimated range could be 

targeted to search for the species.

Restoration Efforts

Large areas in the Hawaiian Islands are now dominated by nonnative species (figs. 9, 10). Even 

in areas dominated by native species, significant disturbance from nonnative plants and animals 

(Cuddihy and Stone, 1990) means that many species are likely to have been extirpated from areas in 

which they formerly were found. At many sites in the state, rare plants have been outplanted in areas 

where they formerly grew in order to expand wild populations: for example, the silversword 

(Argyroxiphium sandwicense) on Mauna Kea (Walker and Powell, 1999) and several rare dry-forest 

species at Kaÿüpülehu Preserve on Hawaiÿi (Cabin and others, 2002). In other cases, sites where a given 

rare species formerly were found are now highly degraded or may be on lands not presently designated 

for conservation management. In such cases, outplanting may occur at sites designated for conservation 

and presumed to constitute appropriate habitat. The method employed here presents a reasonable 

estimate of suitable habitat for each given species, although other site characteristics such as substrate or 

soil type, degree of canopy closure, and associated species must also be taken into consideration. For

example, the case study of Chamaesyce kuwaleana (fig. 15) suggests that, despite severe alteration of its 

habitat, suitable restoration sites may be available within its estimated natural range. Producing a list of 

all species appropriate for a given area will facilitate diverse, community-level ecological restoration.
22

Table 4. Biogeographic regions for case-study species.

[For each species, “X” indicates that record exists for that species from given biogeographic region]

Species

NiÿiahuKauaÿiOÿahu - WaiÿanaeOÿahu - KoÿolauMolokaÿi - WestMolokaÿi - EastL

änaÿi

Maui - WestMaui - EastKahoÿolaweHawaiÿi - KohalaHawaiÿi - Mauna KeaHawaiÿi - Hual

älai

Hawaiÿi - KïlaueaHawaiÿi - Northwest Mauna LoaHawaiÿi - Northeast Mauna LoaHawaiÿi - Southeast Mauna LoaHawaiÿi - Southwest Mauna Loa

Sadleria cyatheoides X X X X X X X X X X X X X X X

Erythrina sandwicensis X X X X X X X X X X X X X X X X X X

Cyanea tritomatha X X X X

Chamaesyce kuwaleana X X

Table 5. Habitat parameters for case-study species.

[For each species, “X” indicates that a record exists for that species from given biogeographic region]

Species

Lower elevation limit (m)Upper elevation limit (m)Lower moisture limit (zone)Upper moisture limit (zone)Lower coastal-moisture limit (zone)Upper coastal-moisture limit (zone)Upland Dry zoneYoung lava substrates

Sadleria cyatheoides 5 2,348 4 7 4 7 X

Erythrina sandwicensis 0 854 1 4 1 5 X

Cyanea tritomatha 350 1,524 6 7 0 0

Chamaesyce kuwaleana 10 500 2 3 2 3
23

Figure 11. Habitat quality across modeled range of Sadleria cyatheoides on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, 

Länaÿi, Maui, and Kahoÿolawe. This species is known from Mesic and Wet habitats (moisture zones 4 through 7) 

across wide elevational range on many islands; it also extends into dryer areas in upper elevations on Maui and 

Hawaiÿi (Upland Dry Zone) but does not extend into drier habitats at lower elevations. Status of habitat for this 

species reflects commonly seen pattern for upland Wet/Mesic species in which much of estimated natural range 

remains in High- or Medium-quality habitat. 
24

Figure 12. Habitat quality across modeled range of Sadleria cyatheoides on island of Hawaiÿi. 
25

Figure 13. Habitat quality across modeled range of Erythrina sandwicensis on Niÿihau, Kauaÿi, Oÿahu, Molokaÿi, 

Länaÿi, Maui, and Kahoÿolawe. This species is known from Arid to Seasonal Mesic habitats (moisture zones 1 

through 4) at low elevations on many islands; it also extends into Moist Mesic areas (Zone 5) along coast but not 

inland. Status of habitat for this species is typical for species restricted to drier lowland areas where much of 

estimated natural range is Medium- or Low-quality habitat.
26

Figure 14. Habitat quality across modeled range of Erythrina sandwicensis on island of Hawaiÿi. 
27

Figure 15. Habitat quality across modeled range of Chamaesyce kuwaleana, restricted to Oÿahu. 
28

Figure 16. Habitat quality across modeled range of Cyanea tritomantha, restricted to island of Hawaiÿi. This 

species is known from only a few biogeographic regions on one island, Hawaiÿi. Darker colors (+) show areas 

where Cyanea tritomantha has been recorded; lighter colors (–) depict areas where it has not been recorded. 

Many species exhibit this pattern in which part of island may have appropriate habitat for a species, but that 

species has never been recorded there. In some cases, a species is naturally restricted; in other cases, there 

has been insufficient sampling in its potential habitat.
29

Studies of Range Size and Rarity

A growing body of work seeks to understand the causes of variation in the size of species’

geographic ranges in the Hawaiian Islands. Many geographically restricted species are threatened with 

extinction, and, therefore, information about the nature of their rarity may be useful to their conservation 

(Gaston, 2002). Nearly half of Hawaiian plant species are naturally restricted to a single island (Price,

2004), and this rarity is correlated with restriction to few habitats and a narrow elevation range (Price 

and Wagner, 2004). The method presented here produces comparatively precise estimates of both the 

natural range size and the probable actual present-day range size (by taking into account human-induced 

range reduction). These two estimates vary independently among species, and, therefore, a species that 

is presently rare may have been quite common in the past. For example, in the case study for Eythrina 

sandwicensis (figs. 13, 14), which is a species that was probably extremely widespread prior to human 

landscape modification, has undergone range reduction so that it is now somewhat rare. By comparison, 

the case study for Cyanea tritomantha (fig. 16) suggests that this species was already somewhat rare 

prior to human landscape modification. This distinction between human-induced rarity and natural rarity 

may have important management implications, as naturally rare species may be better adapted to 

maintaining small populations than species that have lost much of their original population structure 

(Gaston, 1994).

Studies of Biodiversity

Examinations of patterns in biodiversity frequently use species-richness maps produced by 

overlaying the ranges of all species of interest within a region (Flather and others, 1997; Hortal and 

others, 2001; Lennon and others, 2004). Using the methodology presented here, species-range estimates 

and derivative species-richness maps are much more highly resolved locally, when compared to other 

country- or continent-scale maps used in most studies. Using high-resolution species-richness maps, 

more detailed analyses of the factors contributing to biodiversity are feasible. Although factors such as 

habitat, elevation, and island age have been examined in the Hawaiian Islands (Price, 2004), more 

spatially explicit analyses may elucidate complex interactions among factors not apparent through other 

analyses.

Conservation Planning

Species range maps may be employed in a Gap Analysis Program (GAP), in which they are 

compared to the spatial placement of conservation areas in order to identify gaps in conservation efforts

(Scott and others, 1993). The national GAP seeks to incorporate this type of analysis for all U.S. states 

to produce a comprehensive evaluation of biodiversity conservation (Scott and Csuti, 1992). The 

Hawaiÿi GAP is unique among these in incorporating endangered plant-species ranges, rather than 

vertebrates only as in other state GAPs (Gon, 2006). Nonetheless, debate continues as to whether GAP 

appropriately incorporates critical aspects of species conservation (Burley, 1988; Flather and others,

1997). Although the GAP for the Hawaiian Islands considered federally endangered plant species only, 

examination of all plant species may produce different results. Moreover, alternative measures of 

conservation value, independent of federal listing or total richness, may be feasible. Potential measures 

include richness of species that show natural geographical rarity or richness of species that show humaninduced rarity (that is, having small range size after human impact). The comprehensive nature of these 

measures of conservation value, coupled with their comparative detail, may promote landscape-scale 

tools for conservation planning not possible in other regions.
30

Invasive Species Management

Invasive plant species pose a serious threat to Hawaiian ecosystems by displacing and competing 

with native plant species and disrupting key ecological processes (Cuddihy and Stone, 1990).

Conservation agencies and organizations expend considerable resources to control highly invasive plant 

species such as Miconia calvescens. New invasive threats appear each year as incipient populations 

expand. By using known or projected environmental parameters, the potential range of a given invasive 

species can be estimated. Using such an estimated range can help assess the degree of threat posed by a 

given invasive species and may inform management efforts to strategically search for and control 

incipient populations before the species becomes a widespread problem. For example, a study of several 

nonnative species on Maui by Price and Jacobi (2006) used similar methodology to assess the potential 

for range expansion relative to presently known distributions. The resulting analysis may inform 

strategic plans for control of species that are considered most likely to expand their ranges and, thus,

negatively impact native ecosystems or rangeland resources.

Summary and Future Modeling Efforts

The tools and methods presented here provide a simple but comprehensive way to generate maps 

of the estimated natural ranges and probable present-day ranges of Hawaiian plant species. Nonetheless,

these estimates will need to be reassessed or refined periodically. The prospect of new location data that 

is based on continued fieldwork may result in new parameters that necessitate reassessing the range 

estimate for a given species. For example, species continue to be discovered on islands or in habitats 

where they were previously unknown. The development of new GIS layers (including soils, 

geomorphology, and highly refined canopy cover), coupled with point-quality location data for all 

known locations of a given plant species, will promote more sophisticated modeling methodologies that 

are based on probability and include error estimates, capable of being subjected to rigorous model 

testing. At present, however, the methodology documented here presents a useful first approximation of 

the ranges of Hawaiian plant species not previously available.

Acknowledgments

This research was made possible, in part, thanks to support from U.S. Fish and Wildlife Service 

(Cooperative Agreement FWS IA 14 16 0006 87 930) and the U.S. Geological Survey (USGS) Invasive 

Species Program. We would like to thank Rick Warshauer of the Hawaiÿi Cooperative Studies Unit and 

Linda Pratt of the USGS Pacific Island Ecosystems Research Center for offering much of their extensive 

knowledge of Hawaiian ecosystems. Tom Giambelluca of the University of Hawaiÿi at Mänoa provided

important insights into Hawaiian climate, and Dave Sherrod of the USGS supplied digital geological 

maps. Three anonymous reviewers also provided many useful comments on the manuscript. We would 

also like to acknowledge support provided by the Pacific Island Ecosystems Research Center through 

the USGS Invasive Species Program, including federal staff support and administration, as well as for 

support by personnel hired by the Research Corporation of the University of Hawaiÿi and administered 

through the USGS Hawaiÿi Cooperative Study Unit, University of Hawaiÿi at Hilo. Additional 

administrative support and personnel were provided as part of a cooperative project with the University 

of Hawai`i at Mänoa, through the Pacific Cooperative Studies Unit.
31

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Appendix. Modeled Historic Range Maps for Hawaiian Vascular Plant Species

This appendix contains maps that show the modeled ranges of 1,158 Hawaiian plant species, including all native Hawaiian vascular 

plant species that have enough data for modeling their range. For this initial mapping effort, the plants were only mapped at the species level. 

Species taxonomy follows Wagner and others (1990).

Accompanying the maps is a table entitled “of2012-1192_appendix-table.pdf.” Each species contains an entry that includes 

information on its family name, common name, conservation status, and native status, according to the Smithsonian National Museum of 

Natural History’s Flora of the Hawaiian Islands database (Wagner and others, 2005). In addition, the table lists the type of range map 

modeled in this study and also includes links to the range maps, which can be downloaded either in JPG format or as GIS shapefiles. 

The following is a excerpt from the table, in addition to a list of the table’s fields and an explanation of their content.

Name Family Common 

Name

Conservation 

Status

Native 

Status

Map 

Type DOWNLOAD JPG FILES DOWNLOAD GIS FILES(shapefiles, in zip format)

Abutilon eremitopetalum Malvaceae n/a Endangered Endemic Model http://pubs.usgs.gov/of/2012/1192/jpgs/

Abutilon_eremitopetalum.jpg

http://pubs.usgs.gov/of/2012/1192/shapefiles/

abuerem.zip

Abutilon incanum Malvaceae Ma`o Apparently Secure Indigenous Model http://pubs.usgs.gov/of/2012/1192/jpgs/

Abutilon_incanum.jpg

http://pubs.usgs.gov/of/2012/1192/shapefiles/

abuinca.zip

Abutilon menziesii Malvaceae Ko`oloa `ula Endangered Endemic Model http://pubs.usgs.gov/of/2012/1192/jpgs/

Abutilon_menziesii.jpg

http://pubs.usgs.gov/of/2012/1192/shapefiles/

abumenz.zip

Etc. ... [total of 1,230 table entries for 1,158 species and maps]

• Name—Lists the genus and species name of each taxon. In some cases where the species names have recently been revised, both a synonym and a 

table entry to the most recently used scientific name for that taxon are provided to facilitate locating the maps. 

• Family—Lists the family name of each taxon.

• Common Name—Lists the common name of each taxon, if available (n/a, not available).

• Conservation Status—Contains the listing status for each species, according to the Smithsonian National Museum of Natural History’s Flora of the 

Hawaiian Islands database (Wagner and others, 2005) and the U.S. Fish and Wildlife Service (2012). Categories include “Extinct,” “Endangered,”

“Vulnerable,” “Rare,” and “Apparently Secure” (see http://botany.si.edu/pacificislandbiodiversity/hawaiianflora/1999Assessment.html for 

discussion of conservation status categories; see also, Wagner and others, 1999).

• Native Status—Lists the natural distribution of the species. Categories include “Endemic” to the Hawaiian Islands and “Indigenous” to the Hawaiian 

Islands but also found naturally elsewhere. 

• Map Type—Lists the type of range map that has been generated by this study. Categories include “Model,” which means that the range map shows 

the potential range of a species (either estimated, possible, or both) modeled by this study; “Point,” which means that the approximate location of 

the only known locality of a species is shown on the range map as a point locality; and “Descriptive,” which means that the “potential area of 

historic collections” of an extinct species has been shown on the range map.

• DOWNLOAD JPG FILES—Contains a link to download the JPG file of the range map for each species.

• DOWNLOAD GIS FILES (shapefiles, in zip format)—Contains a link to download the shapefile for the range map of each mappable species. The 

shapefiles are projected in UTM Zone 4N coordinates using NAD83 datum.