Representing Biodiversity as an Ecosystem Service
Pat Comer, Dave Theobald, Dean Urban, Jimmy Kagan, Howard Townsend, Frank Casey, David Saah
NCEAS Working Group: Framework for Ecosystem Services, Subgroup on Biodiversity
Biodiversity is often defined as the variability one can observe in natural patterns and processes. These
patterns and processes occur at multiple levels of ecological organization - from genes, to species, to
communities, to landscapes. That variability is essential to many ecosystem services. Biodiversity itself
can also be viewed as an ecosystem service with a wide range of potential beneficiaries. For example,
provisioning services of biodiversity include wild plants and animals and their outputs. High-integrity
upland and wetland communities underlie regulation and maintenance services such as pollination,
water filtration, or erosion control. Biodiversity provides numerous cultural services as well, in terms of
scientific, cultural, and aesthetic outputs. While most services derived directly from biodiversity are
non-consumptive or non-use values, harvested fish and game species are one common example of a
consumptive ecosystem service from biodiversity.
Representing biodiversity as an ecosystem service can come in the form of map, tabular, and text
information. Below we depict a conceptual approach to organizing map and tabular information to
describe the location and relative significance of biodiversity on lands and waters of interest.
Our purpose is to structure information flexibly so that users can select all or part of this mapping
framework to address their varying needs and perspectives. For example, if one desires to focus on fish
and game resources as a consumptive ecosystem service, one might utilize just the information in the
“Migratory and Landscape Species” criteria (white-bounded boxes) of the framework. A more
comprehensive depiction of biodiversity as an ecosystem service should ideally include all four criteria in
the framework. Additionally, our intent is to organize biodiversity information for applications that vary
from reporting up to a national scale, with nationally-available data sets, or down to inform land
use/management decisions at a local project level. We presume that many distinct data sets and
technical tools could be deployed for a given circumstance, so no particular data set, methodology, or
software tool is implied by this framework.
We have incorporated a number of principals and assumptions into this framework design.
Fundamentally, we presume that any given ecosystem service derived from biodiversity will be viewed
as a finite resource, and its relative significance in any given location is indicated by the abundance,
quality, and relative rarity of its components. Within each of the four criteria, several measures aim to
indicate its relative ecological integrity or quality. For example, the relative patch area and connectivity
measures of habitat for landscape species like deer or antelope indicate the relative quality of that
habitat component. Below we explore some of these assumptions in more detail, and then discuss the
technical design principles imbedded in the mapping framework.
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A coarse-filter/fine-filter approach is deployed for selecting components of biodiversity to
efficiently address its multi-scaled nature; primary components include representative ecosystem
types complimented by species that face some degree of concern or vulnerability to being lost. For
the latter, because one could not presume that their habitat requirements are adequately
addressed by other criteria, they require specific treatment. Species categories include – e.g.,
NatureServe G1-G2 (critically imperiled and imperiled rangewide), G3-G4 (G4, if considered
declining and vulnerable), plus any identified species falling under legal conservation status, and of
conservation concern for consumptive services (hunting/fishing/collecting). All species are then
addressed in this framework either as landscape/migrants or local species, depending on the spatial
character of their ecology.
The number of overlapping distributions (i.e., few-to-many) of biodiversity components (species,
habitats, ecosystem types) adds relative significance to a given location for providing biodiversity
services. While at e.g., 30-90m pixel resolution on a map, only one ecosystem/habitat type would
practically fall within a given pixel, multiple species of concern could overlap in any given pixel.
Ecological Integrity - The relative integrity/viability (low-to-high) of biodiversity – referring generally
to the relative health of populations and intact character of ecological processes in a given area adds relative significance to the service by providing the environment for ecological and
evolutionary processes and supporting conditions for service provision.
Irreplaceability/rarity (Relative rarity modifier – green bordered box in framework diagram): by
explicitly acknowledging the relative rarity of a given biodiversity component at a given location
(e.g., using G1-G5 scale), it confers a measure of relative significance in terms of the number of
opportunities to represent that component of ecological, species, or genetic diversity.
With these approaches and assumptions in mind, the mapping framework includes a series of technical
design considerations, including:
1. Ecosystem services are represented spatially as a map surface (i.e., pixels each including a relative
score [say 0.0-1.0]) rather than having scores applied to variably sized polygon-based patches. This
technical approach provides flexibility for summarizing the data using administrative units to
address a range of common land use scenarios.
2. Pixel attributes within a given INDICATOR (upper, colored sharp-edged boxes) are represented as an
index value (e.g., 0.0-1.0) and assigned a relative weight to derive a composite pixel value (e.g.,
weighted average) for one of the four CRITERIA (the white bordered rectangles).
3. Results can be customized through both selection (inclusion or exclusion) of criteria and relative
weighting as needed. For example, a map surface could be constructed to only represent wild plant
species (e.g., Ginseng, Goldenseal, etc.) that are collected as a consumptive ecosystem service, and
certain of those species could be weighted by users as providing greater significance than others.
Next, the four criteria from the mapping framework address options for representing biodiversity
components and their relative quality. Each of these criteria is describe in more detail below.
Land/Seascape Integrity – This category aims to address properties of natural land/seascapes that
support biodiversity, but does not pertain to any particular ecosystem type or species. A Landscape
Intactness indicator provides a measure of likely alteration from nearby stressors. This continuous
surface is thresholded to identify relatively intact patches. Landscape permeability gauges ‘centrality’ of
a location and ease of lateral movement for any process or species across the gradient of landscape
intactness.
Ecosystem/Habitat Integrity – Spatial Pattern Index could emphasize spatial configuration of vegetation
structure (e.g., contagion of trees that characterize a “clumpy” savanna mosaic). It could also address
biophysical variability, such as is described by ecological land units, which are biophysically homogenous
areas sharing similar microclimate, soil chemistry, moisture, and exposure. Biophysical variety provides
local-scale ecological buffering (e.g., in light of climate change). The Dynamic Process Departure Index
factors in models of fire or hydrologic regime to gauge relative departure due to land use decisions that
affect ecological integrity. An index of Biotic Composition factors in observed vs. expected species
composition for a given ecosystem/habitat type. In some instances, presence/abundance of invasive
species would be used as a stressor-based index for this measure.
Migratory and (Area-Sensitive) Landscape Species – This category addresses many species of concern
that are represented by distribution maps in a variety of forms. For a given species, maps based on
habitat-affinities would fall into this category. This is also where specific habitat components for species
are addressed, such as known landscape corridors between core habitat patches. Integrity indicators
address spatial aspects of habitat patches, including patch core area and connectivity measures (such as
centrality and flow measures).
Local Species – This category includes most small vertebrates, invertebrates, and plants of conservation
concern that occupy relatively localized areas; many addressed by Natural Heritage program occurrence
or other point observation data. Natural Heritage data may include a composite viability score (EO Rank
of A-D), while other data might be gauged for viability using indicators of relative population size and
biotic condition.
Finally, functional aspects of this mapping framework include:
Selecting components and indicators: Again, the user would have the option to include or exclude
components of biodiversity, depending on their needs and intentions. This extends to selection of
entire criteria as well as to the species or habitats that are included within those criteria. While these
decisions should be informed by scientific understanding, they are ultimately decisions to be taken
within a social context.
Weighting components and indicators: Similar to selection, the relative weighting among criteria and
indicators should be informed by scientific understanding, but this framework is designed to support
decision making in a social context.
Summarizing Indices: In a practical context, users might summarize index values for an overall score for
biodiversity significance in a given location, or they might choose to report only at some disaggregated
level of the framework. Mapping and reporting for individual indicators may be quite informative for
analyzing conditions and developing specific conservation strategies; quite complimentary to broader
measures of reporting.
Scenarios: The framework is designed to support mapping these services within the context of common
natural resource assessment and planning processes. These processes typically require assessment of
the location, abundance, density, and quality of multiple services. They also typically require analysis of
past, current, and potential future land and water use scenarios to document their implications for
service provision. This framework aims to support scenario planning and related decision making.
Next Steps
We have tentatively identified a number of national and regional data sets that could be utilized in this
framework. Through pilot projects, the NCEAS working group will further investigate and refine this
framework for use in a variety of practical circumstances around the United States. This document will
be expanded upon to more fully document the assumptions used, data needs, methodological issues,
and technical tools that could facilitate application.