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  <front>
    <journal-meta>
<journal-id journal-id-type="publisher">WE</journal-id>
<journal-title-group>
<journal-title>Web Ecology</journal-title>
<abbrev-journal-title abbrev-type="publisher">WE</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Web Ecol.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1399-1183</issn>
<publisher><publisher-name>Copernicus GmbH</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
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    <article-meta>
      <article-id pub-id-type="doi">10.5194/we-15-25-2015</article-id><title-group><article-title>Defining heterogeneity as a second level of variation</article-title>
      </title-group><?xmltex \runningtitle{Defining heterogeneity as a second level of variation}?><?xmltex \runningauthor{B.~B.~Hanberry}?>
      <contrib-group>
        <contrib contrib-type="author" corresp="yes" rid="aff1">
          <name><surname>Hanberry</surname><given-names>B. B.</given-names></name>
          <email>hanberryb@missouri.edu</email>
        </contrib>
        <aff id="aff1"><institution>Department of Forestry, University of Missouri, 203 Natural Resources
Building, Columbia, MO 65211, USA</institution>
        </aff>
      </contrib-group>
      <author-notes><corresp id="corr1">B. B. Hanberry (hanberryb@missouri.edu)</corresp></author-notes><pub-date><day>19</day><month>June</month><year>2015</year></pub-date>
      
      <volume>15</volume>
      <issue>1</issue>
      <fpage>25</fpage><lpage>28</lpage>
      <history>
        <date date-type="received"><day>15</day><month>January</month><year>2015</year></date>
           <date date-type="rev-recd"><day>11</day><month>May</month><year>2015</year></date>
           <date date-type="accepted"><day>01</day><month>June</month><year>2015</year></date>
      </history>
      <permissions>
<license license-type="open-access">
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      <abstract>
    <p>The term heterogeneity has been defined in various ways so that
the meaning of heterogeneity has become ambiguous. However, heterogeneity
can be defined carefully as a distinct response to multiple single types of
underlying variation, that is, a secondary level of variation (or
“metavariation”). Identification of heterogeneity is affected by multiple
factors, including researcher decisions, and ecosystems at a specified scale
can contain both heterogeneous and homogenous variables. A formalized
definition may also reduce the suggestion that heterogeneity is more
beneficial than homogeneity.</p>
  </abstract>
    </article-meta>
  </front>
<body>
      

<sec id="Ch1.S1" sec-type="intro">
  <title>Introduction</title>
      <p>Ecological definitions often can not be both generalized and fit specific
studies that vary in time, location, extent, taxa, history, disturbance,
land use, techniques, measurements, objectives, perspectives, and other
factors that present context. In addition, ecological terms with
inconsistent use (Hall et al., 1997; Lindenmayer and Fisher, 2007; Madin et
al., 2008; McInerny and Etienne, 2012) hinder communication about the concept.
Heterogeneity is one such term that may make sense as applied in each
particular case but not consistently as a whole. Heterogeneity often has a
unique definition in each study, even if the authors have not explicitly
stated their definition (Li and Reynolds, 1995). Kolasa and Rollo (1991)
recognized wide use of the term heterogeneity and definitional elusiveness
despite apparent simplicity. Rather than an exhaustive literature survey, my
objective is to initiate a discussion on a well-used ecological term,
heterogeneity, that may be of interest to a broad audience, by proposing a
more limited definition that is free of value judgments.</p>
</sec>
<sec id="Ch1.S2">
  <title>Why ambiguous terminology is a problem</title>
      <p>Variation is a hallmark of ecology, which eventually introduces ambiguity
into concepts and terminology. Ambiguity creates misdirection and confusion
in interpretation, reduces comparability and detection in literature
searches for related research, and prevents effective and efficient use and
understanding of terms (Madin et al., 2008; McInerny and Etienne, 2012). Use
of heterogeneity to invoke different themes may have resulted in a
panchreston, in that researchers can not readily understand what
heterogeneity means to other researchers and the implications of their
research (Lindenmayer and Fisher, 2007). It is symptomatic that Stein et al. (2014)
needed a figure to explain heterogeneity because there are hundreds
of terms, which often are not defined, unique to each researcher, or used
synonymously instead of in a controlled manner. When there is no consensus
about when a term should be used, there should be some critical response
suggesting that researchers carefully select and define their terminology
along with proposals for formalizing use of terminology to improve clarity
and communication.</p>
      <p>There are numerous publications that have produced varying definitions of
heterogeneity, more than one book can cover comprehensively (e.g., Kolasa
and Pickett, 1991; Hutchings et al., 2000). Heterogeneity may have originated
in reaction to the idea that nature was stable, orderly, constant, and
homogeneous (McIntosh, 1991; Weins, 2000). Heterogeneity initially was
differentiated from variation by including more than one variable (i.e.,
heterogeneity defined as composition of parts of different kinds; Kolasa and
Rollo, 1991). However, heterogeneity often appears to be used interchangeably
with variation (i.e., measurement of range of one variable; Fahrig et al.,
2011), diversity (i.e., species' richness and distribution, particularly
using diversity metrics; Malanson and Cramer, 1999), dynamics (i.e., temporal
dynamics), gradients (e.g., elevational, topographical, soil, climate,
resource, nutrient; Stein et al., 2014), complexity, and landscape metrics
(e.g., continuous, patchy, configuration, composition; Stein et al., 2014).
Rees et al. (2000) defined heterogeneity as (1) variation around a parameter,
(2) abiotic and biotic variables that cause variability (in population
demography), and (3) spatial and temporal variation in the abiotic and biotic
environment. Furthermore, there are multiple types of heterogeneity:
spatial, temporal, functional, measured, hierarchical, habitat,
environmental, population, and organizational (Kolasa and Rollo, 1991);
landscape, compositional, configural, and structural (Fahrig et al., 2011);
genetic and taxonomic (Olden and Rooney, 2006); non-specific and
individual-specific (Rees et al., 2000); surface reflectance,
spatio-spectral, wavelength, and nested (for land cover and other remotely
sensed variables; Lausch et al., 2013); biogenic and physical (Pickett et
al., 2000); statistical and network. Heterogeneity is also used outside of
ecology, in fields ranging from health to economics.</p>
</sec>
<sec id="Ch1.S3">
  <title>Limiting the definition of heterogeneity</title>
      <p>Consistent and formalized terminology will reduce the “heterogeneity of
heterogeneity” (Kolasa and Rollo, 1991) and perhaps require that at minimum,
researchers are more thoughtful in the use of the term heterogeneity. The
term variation should be used for all unspecified variation. Heterogeneity
arises from comparisons of different sources of variation that occur in
space, time, as interactive networks or contacts (e.g., plant-pollinator;
Marsh et al., 2011; Rosenberg and Freedman, 1994), or as studies for
meta-analysis. Because variation occurs independently within a sample, while
heterogeneity results from comparing samples, heterogeneity is additive or
emergent as a secondary level to variation. Instead of being multivariate
(including more than one variable; Kolasa and Rollo, 1991), heterogeneity is
“metavariate”, arising from underlying multiple sources of variation. For
example, heterogeneity appears to be most typically explicit for change over
space; thus, heterogeneity emerges in comparison among spatial units instead
of within spatial units (Fig. 1). Usually there is a reasonable boundary
in space or time to separate samples that match justifiably with the
variable of interest.</p>
      <p>Generally, abiotic variables present as the primary level of variation
and as such, use of the term “variation” instead of “heterogeneity” will be
more appropriate. In particular, although abiotic conditions (McInerny and
Etienne, 2012) of topography or elevation may be sources of heterogeneity,
these variables are static or slow to change over time (in a human
timeframe) and do not respond to other sources of variation. However, water
and soil are responsive abiotic variables; these resources are affected by
variation in plants and insects (Tsunoda et al., 2014) and thus,
heterogeneity can be an appropriate term.</p>
      <p>Homogeneity represents lack of response when comparing primary units of
variance. Homogeneity has also become accepted terminology for decreased
genetic, taxonomic, or functional diversity (Olden and Rooney, 2006).
Diversity is richness and evenness of species; because evenness has a
spatial component and types of diversity (alpha, beta, and gamma) have a
scale, heterogeneity and homogeneity can be interchangeable with diversity
that is measured spatially.</p>

      <?xmltex \floatpos{t}?><fig id="Ch1.F1"><caption><p>In this example, primary variation occurs in abiotic and biotic
variables. Abiotic conditions, such as topography, will affect other
variables but generally will not respond to other variables, while abiotic
resources, such as water, and biotic resources, such as herbaceous
vegetation that provides fine fuels, will interact with other variables. A
process, such as fire, may be necessary for some interactions to create a
secondary level of response, for example by vegetation in the form of
varying phases of forest ecosystems. A heterogeneous continuum of savannas
to woodlands to closed forests develops due to different exposure to fire,
based on underlying primary levels of topography, moisture, and fine fuels.</p></caption>
        <?xmltex \igopts{width=236.157874pt}?><graphic xlink:href="https://we.copernicus.org/articles/15/25/2015/we-15-25-2015-f01.png"/>

      </fig>

</sec>
<sec id="Ch1.S4">
  <title>Heterogeneity is affected by multiple factors</title>
      <p>Identification of heterogeneity will vary with decisions about study design
and the response variable of interest, such as the scale of comparison
(i.e., spatial sampling units) and hierarchical levels of organization
(e.g., individuals, populations). For example, historically in North
America, frequent surface fires were heterogeneous in space but produced low
tree species diversity and a simple overstory canopy structure in oak- or
pine-dominated ecosystems (Hanberry et al., 2014). However, even though tree
species' richness and evenness were low, there was a wide range of tree
densities from savannas to closed woodlands across the landscape, and
richness of herbaceous plants and animals associated with light increased.
Similarly, but without disturbance, old growth eastern forests of sugar
maple-American beech contained low tree species diversity, but contained a
high diversity of unique species dependent on complex tree structure. These
forest ecosystems were both heterogeneous and homogenous.<?xmltex \hack{\newpage}?></p>
      <p>In addition, the type, severity, and extent of a disturbance process may
reverse identification of heterogeneity or homogeneity. For example, Kolasa
and Rollo (1991) pointed out that initially, disturbances produce
heterogeneity in the landscape but as the extent of disturbances increases
beyond 50 % of the area, the matrix may be of a new type and become
increasingly homogenous. Abiotic factors and biotic organisms will also
influence disturbances and may increase or decrease measurements of
heterogeneity.</p>
</sec>
<sec id="Ch1.S5">
  <title>Heterogeneity as a value-laden term</title>
      <p>Heterogeneity is considered a desirable attribute, but heterogeneity depends
on what is measured. A landscape composed of only pines or oaks may not be
heterogeneous in measurements of tree richness in space, but still is
valuable. Unexpected implications (when heterogeneity is considered
desirable) of the term heterogeneity (e.g., Geri et al., 2010) can occur when
heterogeneity due to multiple land uses may indicate the detrimental
condition of fragmentation rather than a range of vegetation stages and
types beneficial to wildlife and plants. Heterogeneity can be undesirable
when representative of invasive species or intensive land use (e.g.,
diversity may not be greater in a heterogeneous landscape that is
predominantly agricultural or urban and heterogeneity may increase due to
invasive species). Thus, heterogeneity does not necessarily connote a
positive situation and likewise, homogeneity does not imply a negative
situation.</p>
</sec>
<sec id="Ch1.S6" sec-type="conclusions">
  <title>Conclusions</title>
      <p>Generalizations about heterogeneity can be misleading and meaningless
without context (Wiens, 2000). Ambiguity can be resolved by coordination in
the concept and application of the terms heterogeneity and homogeneity. To
be classified as heterogeneous, the variable should be responsive to primary
sources of variation, such as environmental gradients. At the very least,
researchers who use the term heterogeneity should define all aspects of
heterogeneity to prevent ambiguous terminology from creating confusion. What
are the units of comparison? Which abiotic gradients, biotic organisms,
biotic level of organization (e.g., genetic, assemblage), processes,
structure, or landscape metrics vary among units? Are the response variables
(heterogeniables?) a secondary response to primary sources of variation? In
some cases, use of the term variation rather than heterogeneity may be
clearer and less complicated by value judgments (i.e., the notion that
increased heterogeneity is better).<?xmltex \hack{\newline}?><?xmltex \hack{\newline}?><?xmltex \hack{\noindent}?><?xmltex \bgroup\small?>Edited by: J. M. Halley<?xmltex \hack{\newline}?> Reviewed by: two anonymous referees<?xmltex \hack{\newpage}?><?xmltex \egroup?></p>
</sec>

      
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