Can
biodiversity, human wellbeing and sustainable development indicators be linked?
Susan A. Mainka 1 & Bright B. Kumordzi2
1IUCN – International Union for Conservation of Nature, rue
Mauverney 28, CH-1196 Gland, Switzerland
2Community Ecology and Conservation Research Group, COCON,
University of Groningen, 64 Rijksstraatweg, 9752 AH, Haren, The Netherlands
Email: 1 sue.mainka@iucn.org, 2 Brightkumordzi@yahoo.com
Date of publication (online): 26
December 2010
Date of publication (print): 26
December 2010
ISSN 0974-7907 (online) | 0974-7893
(print)
Editor: Hari
Balasubramanian
Manuscript
details:
Ms # o2301
Received 29 August 2009
Final received 10 November 2010
Finally accepted 12 November 2010
Citation: Mainka, S.A. & B.B. Kumordzi (2010). Can biodiversity, human wellbeing and sustainable development indicators be linked? Journal of Threatened Taxa 2(13): 1372-1378.
Copyright: © Susan A.
Mainka & Bright B. Kumordzi 2010. Creative Commons Attribution 3.0 Unported
License. JoTT allows unrestricted use of this article in any medium for
non-profit purposes, reproduction and distribution by providing adequate credit
to the authors and the source of publication.
Author Details: Sue Mainka is the Head of Science and Learning at IUCN- International Union for
Conservation of Nature, based in Switzerland. Sue is responsible for
supporting integration of science in IUCN’s work and profiling the science that
IUCN generates around the world. She has a particular interest in
indicators as a means of measuring biodiversity’s connection to people. Bright
Kumordzi is an ecologist with interest in biodiversity conservation and
sustainable development. He is currently a consultant with the Ghana Ecological
Society and Ecotourism Centre, Ghana. He worked as a Chevening scholar in
Biodiversity at the UNEP-World Conservation Monitoring Centre (UNEP-WCMC),
Cambridge, UK focusing on CITES-related issues.
Author
Contribution: SM developed this paper in response to discussions about the
possibilities to link global development and biodiversity indicators. BK took the lead on statistical analysis for
this paper.
Acknowledgements: The authors thank Jeff McNeely and anonymous reviewers for comments on
drafts of this manuscript.
Abstract:A mission to reduce the rate of loss of biodiversity as a
contribution to poverty reduction was agreed as part of the Strategic Plan for
the Convention on Biological Diversity, adopted by the Conference of the
Parties in 2002. As 2010 draws to a
close it is clear that this target will not be met. To continue and build on momentum generated
by the 2010 target, the conservation community has been discussing a potential
post-2010 framework that again includes explicit reference to the link between
human wellbeing and conservation, and also considers the links with human
wellbeing and sustainable development. Given this agreement, we reviewed several human wellbeing and
sustainable development indicators compared to existing biodiversity status and
trends indicators to determine if clear correlations can be found that could be
used to track progress in a new framework. We undertook this review at both the global and continental levels. The indicators for protected area and forest
cover showed significant positive correlation across all continents. We found a significant negative correlation
between changes in protected area (PA ) cover and tonnage of greenhouse gas
emissions released (GHGe) between 1990 and 2005 for all the continents. At the global level we found no other
correlation across the indicators reviewed. However, we found that correlations between the biodiversity and human
wellbeing and sustainable development indicators varied across continents. As the only indicators for which global level
correlations exist, we suggest that either protected area coverage or forest
cover may be relevant biodiversity indicators for global analyses of
biodiversity-human wellbeing or sustainable development relationships, and that
the relationship between protected area cover and greenhouse gases could be one
indicator for links between biodiversity and sustainable development. More research is needed to better understand
factors involved in the relationships between biodiversity, human wellbeing and
sustainable development, and to identify useful indicators of these linkages at
global or continental level. In the
meantime, the challenges presented by demonstrating these links should not
delay urgently needed conservation actions.
Keywords:2010 targets, assessment, human wellbeing, Indicators,
sustainable development.
Abbreviations:ANS - Adjusted Net Savings; CBD - Convention on Biological Diversity;
ECOPRINT - Ecological Footprint; FAO - Food and Agriculture Organization of the
United Nations; GDP - Gross Domestic Product; GHGe - Greenhouse gas emissions;
HDI - Human Development Index; IUCN - International Union for Conservation of
Nature; NMP - Numbers of malnourished people; UNDP - United Nations Development
Programme; UNEP - United Nations Environment Programme
Introduction
In recognition of the urgency of the biodiversity crisis, the
2010 biodiversity target “…to
achieve by 2010 a significant reduction of the current rate of biodiversity
loss at the global, regional and national level as a contribution to poverty
alleviation and to the benefit of all life on earth” was adopted by the Sixth
Conference of the Parties to the Convention on Biological Diversity (CBD; The
Hague, Netherlands, April 2002) as part of the Convention’s Strategic Plan (CBD
2002). A similar target was adopted at
several other fora from 2002 to 2007, including the Johannesburg Plan of Action
and the Millennium Development Goals. Through such targets the global community has recognized a link between
biodiversity conservation, human wellbeing and sustainable development.
Although the specific formulation differs for each, the 2010
biodiversity target is one of the most relevant international tools to draw
attention to the urgent situation for biodiversity globally, and to catalyze
action to conserve nature, which underpins human wellbeing (IUCN 2009). Nevertheless, despite the increased
awareness and energy invested in biodiversity conservation as a result of the
2010 biodiversity target, the target itself will not be met (Secretariat of the
CBD, 2010). The rate of biodiversity
loss has not measurably reduced, the world has more poor people than ever and
economic development is being achieved at the price of measurable climate
change. Action is still required to
improve environmental governance, ensure adequate investment in environmental
management, promote full engagement of all stakeholders in conservation and
provide for better long term monitoring of biodiversity.
In October 2010, the CBD held its 10th Conference of the Parties
at which a new strategic plan and associated post-2010 biodiversity
conservation framework of targets was adopted. Discussions are underway to articulate a post-2010 framework of
indicators within the next Strategic Plan of the CBD, including the need to
reinforce biodiversity’s role in sustainable development and poverty reduction,
as specified in the 2010 target. Ideally, any new framework should build on the lessons learned and
reinforce the positive aspects of the previous framework. With respect to the indicators, the lessons
learned from the 2010 target indicator framework include the fact that “The
framework does not explicitly include development/social indicators to measure
directly the impact of biodiversity loss on development and poverty
reduction. As the full wording of the
target includes specific reference to the link between biodiversity and
development/poverty reduction, inclusion of relevant indicators is essential to
highlight these links between impact of biodiversity loss or conservation
successes and development” (IUCN 2009).
Human wellbeing has been defined, within the conceptual
framework of the Millennium Ecosystem Assessment (MA) as comprising access to
basic materials for life, health, good social relations, security and freedom
of choice and action (MA 2003). Sustainable development has been defined, by
the Brundtland Commission as development that “meets the needs of the present
without compromising the ability of future generations to meet their own needs”
(UN 1987). Using these definitions,
human wellbeing focuses on the current situation while sustainable development
includes future considerations.
The role of biodiversity in supporting human wellbeing and
sustainable development is multi-faceted and has been described through
concepts including that of ecosystem services (Daily 1997; MA 2005). Many models have graphically represented the
relationship between people and nature (MA 2005; Diaz et al. 2006; McNeely
& Mainka 2009). Any post-2010
framework could consider including indicators that directly evaluate changes in
human wellbeing or sustainable development against indicators of biodiversity
status and trends. A cost effective and
efficient approach to monitoring progress would draw on indicators from among
those that are already being measured though new indicators may need to be
developed to fully assess the links.
This paper reviews the correlation among a selection of
national level indicators of biodiversity status and compares them to several
existing indicators for human wellbeing and sustainable development. Any resulting correlation could be useful to
inform any post-2010 biodiversity conservation framework as well as any future
research agenda for monitoring progress on human wellbeing, sustainable development
and biodiversity conservation.
Materials and Methods
Challenges in linking biodiversity indicators
with human wellbeing and sustainable development indicators include the need to
have a common spatial basis for measurement and also the need to have enough
data points to make the comparisons. For
time series comparisons, we also needed indicators that have been measured over
long enough periods of time.
With respect to human wellbeing, standard
indices are generally available at national level and include the Human
Development Index (HDI) of UNDP and the numbers of malnourished people (NMP) as
reported by the FAO. For sustainable
development, the Adjusted Net Savings (ANS) of the World Bank, and the Ecological
Footprint (ECOPRINT) of the Global Footprint Network, along with greenhouse gas
emissions (GHGe) are also currently being regularly assessed at national level.
Therefore, biodiversity indicators assessed at national level were chosen for
this review.
Biodiversity status indicators have been under
development within the framework of the CBD’s 2010 framework and the
Biodiversity Indicators Partnership, a consortium of 28 partners collaborating
to further develop and promote indicators for the consistent monitoring and
assessment of biodiversity. Out of the
22 indicators selected, several still need either development or more complete
data sets and hence will be of limited use in assessing progress towards the
2010 target. For the purposes of
comparison on a national basis, one of the 22 CBD indicators (protected area
coverage) was available and for this review we supplemented it with other
biodiversity indicators that were already available, including the numbers of
threatened endemic species (biodiversity at species level), forest area cover
(biodiversity at ecosystem level) and national biocapacity (biodiversity at
ecosystem service level).
Detailed description of the indicators used are
as follows
Biodiversity status and trend indicators
The following were used in this review:
(i) Percentage of endemic species per country
that are threatened (Threatened Endemic Species; TES) - This includes data from
the 2000 and 2004 IUCN Red List of Threatened Species (www.iucnredlist.org). It is an indicator of level of threat to the
species most in need of conservation attention to prevent their global
extinction and includes data on mammals, birds, amphibians, freshwater crabs, reef-forming corals,
conifers, and cycads from 247 countries and territories. As no data on threatened endemics at national
level are available for 2005, data for 2004 were used. Threat status for species included in this
analysis are unlikely to change within one year and therefore the 2004 data
should represent a fair comparison with human well being and sustainable development
indicators for 2005 (Red list Officer (C. Hilton-Taylor, pers. comm.)).
(ii) Land area gazetted as protected areas (PA
coverage) - Data on terrestrial and
marine protected areas for 1990, 2000 and 2005 was downloaded from the MDG
indicator database (http://millenniumindicators.un.org/unsd/mdg/Data.aspx)
and included information from 218 countries and territories within which the
analysis for terrestrial and marine protected areas was conducted.
(iii) Land area with forest cover (Forest
Cover) - Data from the Global Forest Resources Assessments from 1990, 2000 and
2005 (ftp://ftp.fao.org/docrep/fao/008/A0400E/A0400E14.pdf)
included information from 207 countries and territories. Forest area was determined both by the
presence of trees and the absence of other predominant land uses, including
land spanning more than 0.5 hectares with trees higher than 5m and a canopy
cover of more than 10%, or trees able to reach these thresholds, such as areas
under reforestation and areas temporarily unstocked but expected to regenerate.
(iv) Biocapacity - The Global Footprint Network
(www.footprintnetwork.com) assesses, at
national level, the capacity of ecosystems to produce useful biological
materials and to absorb waste materials generated by humans, using current
management schemes and extraction technologies. Data for 1999 and 2005 were used in this analysis. As no data were available for 2000, the 1999
data were used as proxies for the 2000. The biocapacity of each country is expressed in units of global hectares per capita with a global
hectare referring to the amount of biologically productive land and water
available.
Human Well Being Status and Trend Indicators (HWB Indicators)
(i) Human Development Index (HDI) – The Human
Development Index (HDI) is a composite index that combines measures of life
expectancy (life expectancy at birth), education (adult literacy rate and
education enrollment levels) and living standards (GDP per capita). HDI is
calculated on a scale from 0-1 with values up to 0.500 representing low
development, 0.501-0.799 representing medium development and values above 0.800
representing high development. Data for
1990, 2000 and 2005 were used in this analysis.
(ii) Numbers of undernourished people (NMP) –
As reported by the FAO, undernourishment refers to “the condition of people
whose dietary energy consumption is continuously below a minimum dietary energy
requirement for maintaining a healthy life and carrying out a light physical
activity with an acceptable minimum body-weight for attained-height”. Data for the number of malnourished people
indicator is organized for two year interval, and for this analysis we used the
values for 1990-1992, 2000-2002 and 2004-2006 as proxy for the years 1990, 2000
and 2005.
Sustainable Development Status and Trend Indicators (SD Indicators)
(i) Adjusted Net Savings (ANS) – Adjusted Net
Savings (ANS) is an aggregate indicator, from the World Bank, that attempts to
quantify the various forms of capital that a country possesses and then assess
the net value of that capital. This is a
composite index calculated from standard national accounting measures of gross
national savings adjusted according to educational expenditures, depreciation,
mineral depletion, energy depletion, and damage from carbon dioxide and fine
particulate emissions. Positive ANS
values imply sustainability while negative values imply countries living beyond
their means. Data for 1990, 2000 and
2005 were used in this study and are available http://databank.worldbank.org)
for an average of 90-100 countries since 1990.
(ii) Ecological Footprint (ECOPRINT) –
Ecological footprints are measures of the human demands on biological capacity
to sustain consumption across fisheries, cropland, forests, land use/urban and
carbon. For the years 2000 and 2005 data are available (http://www.globalfootprintnetwork.com ) for 150 countries.
(iii) Greenhouse gas emissions (GHGe) - Data
for total emissions of carbon dioxide, methane, nitrous oxide, hydrofluorocarbons,
perfluorocarbons and sulfur hexaflouride, and including land use change for 185
countries and territories for 1990, 2000 and 2005 were obtained from the World
Resources Institute’s Climate Analysis Indicators Tool (http://cait.wri.org).
As single point data may reflect stochastic
events as opposed to general trends, we sought to review at least two data
points per country. Unfortunately such
data does not exist for all the indicators, thus we limited our analyses to
indicators for which data points in the year 2000 and 2005 were available. This meant that we had at least two data
points per country for an indicator for each comparison.
We also attempted to assess correlations,
through correlation matrices, in changes over a 15 year period of the
indicators for which such data was available. Data was available for 1990 and 2005 for forest cover, protected area
coverage, HDI, NMP, ANS and GHGe. Countries were included in these analyses if data points were available
for both years.
Data analyses were done on global and
continental levels. We grouped countries
for which the indicators were available into continents following the standard
UN regional classifications (http://millenniumindicators.un.org/unsd/methods/m49/m49regin.htm)
consisting of Africa, Asia, Europe, North and Central America and the Caribbean
(NCAC), South America and the Oceania.
All analyses were conducted with the R 2.10.1
statistical software (R core Team 2009). We examined the correlation between biodiversity indicators using the
Pearson product-moment correlation and tested for the biodiversity indicators
across continents using analyses of covariance (ANCOVA) followed by Tukeys’
Honest Significant test (p > 0.05). Based on Pearson product-moment
coefficient correlation matrix, we examined the correlations between the
biodiversity and human well being and sustainable development indicators. We report only significant correction
coefficients computed from more than ten data points. We also emphasize here that correlation
should not be taken to mean causality; it does imply some relationship between
the two parameters, including relationships involving an external but common
factor.
Results
Biodiversity indicators
Among the biodiversity indicators, only forest cover and PA coverage were correlated across all continents. Only an estimated 13.5% of global forests are included within IUCN Category 1-VI protected areas (Schmitt et al. 2009) so this correlation is unlikely to be simply because forest ecosystems represent the majority of protected area systems. We also found a significant difference between some of the biodiversity indicators at continental level (p < 0.001) under consideration. The TES per country was positively correlated with forest cover only for Africa. We found significant correlations across changes in biodiversity indicators between 1990 and 2005. There was a positive correlation between change from 1990-2005 in percentage of PA cover and percentage forest cover in South America, while negative correlation was found for NCAC and Oceania. (Table 1).
Correlations across
Biodiversity, Human Wellbeing and Sustainable Development Indicators
At the global level, no correlation across either HWB and
biodiversity indicators or SD and biodiversity indicators was found. At continental level, some other patterns
across these indicators did emerge (Table 2).
From the perspective of biodiversity indicators, the %TES per
country showed a positive correlation with NMP in Africa, Asia and South
America and with ECOPRINT in Asia. Forest cover was negatively correlated with HDI and ANS in Africa. Positive correlations were seen for forest
cover and NMP and GHGe in Africa, Asia and South America and with GHGe in
Europe. Forest cover was positively correlated with HDI in North America. PA coverage showed similar correlations to
that for forest cover with the exception of no correlation with ANS for Africa
or with GHGe for South America. Biocapacity showed no correlation with either of the HWB indicators but
did show a negative correlation with ANS in both Africa and South America and a
positive correlation with ECOPRINT in Europe and South America.
Correlations across Changes in
Biodiversity, Human Wellbeing and Sustainable Development Indicators from
1990-2005
Change in forest cover between 1990-2005 correlated
negatively with HDI in Europe and NCAC, and with NMP in Africa, Asia and South
America. Forest cover also correlated
negatively with GHGe in NCAC and Oceania but positively for Africa (Table
3). Over the same period, we also found
that change in PA cover correlated negatively with HDI only for NCAC and with
NMP for Asia and South America. Changes
in PA cover correlated positively with ANS in Europe and Asia. We found a
significant negative correlation between PA cover and GHGe for all the
continents (Table 3).
Discussion
The 2010 biodiversity target included an
explicit reference to the contributions of biodiversity to “.. poverty alleviation
and to the benefit of all life on earth”. It is probable
that any post-2010 framework chosen by Parties will echo this contribution and
continue to emphasize the importance of biodiversity to people. Any targets that are adopted that include
this aspect of biodiversity’s role should, therefore, include measurements of
human wellbeing and/or sustainable development that parallel measurements of
status and trends in biodiversity. However, the usefulness of including such HWB or SD indicators in a
post-2010 biodiversity framework will depend on whether the selected indicators
have some correlation with indicators for biodiversity.
Correlation among biodiversity
indicators
One of the important results from our
preliminary data analyses is that correlation among the biodiversity indicators
is not necessarily global and do differ between continents. This finding has implications for studies
that use these indicators for global comparison of biodiversity-development
relationships and highlights the need to include consideration of continental
differences in natural resources distribution, socio-cultural, political and
economic factors when considering links across biodiversity and HWB or SD. For example, we found a positive correlation
between TES and forest cover in Africa. A positive correlation may result, generally speaking, because more
species are located in larger areas although the specific relationship, as
defined by species/area curves may change depending on local conditions. Therefore, areas with greater numbers of
species will likely have more potentially threatened species as well. Why this threatened endemic species/area
relationship did not apply beyond Africa is an interesting question. One factor that might play a role would be
different percent total forest cover. The 2005 Global Forest Resources Assessment (FAO 2006) reports that
Africa had 21.4% forest cover compared to 18.5% for Asia, 44.3% for Europe,
47.7% for South America and 24.3% for Oceania. However, if lower continental percentage of forest cover (global average
~30%; FAO 2005) was a factor then Asia and Oceania should also show no
correlation.
We did not find any correlation between biocapacity and other biodiversity indicators across any of the continents. This may be because biocapacity, as a measure of ecosystem capacity to deliver services, considers only “biologically productive land” and does not include what are deemed to be “non-productive and marginal areas” such as arid regions, open oceans, the cryosphere and other low-productivity surfaces. Areas producing biomass that is not of use to humans are also not included. Therefore, in 2003, for example, biocapacity was a measure of biodiversity for only about one quarter of the planet’s surface (Kitzes et al.2007) and perhaps limiting its use as a more general indicator of biodiversity status.
Interestingly, while PA cover and forest cover
were correlated across all continents using the 2000/2005 data, changes in
those parameters over 15 years were not correlated globally but showed a positive
correlation for South America and a negative correlation for NCAC and
Oceania. This result could suggest that,
in these continents, proportional representation of forests within protected
areas has varied differently during this 15 year period. However, the differences may also be related
to the FAO data used. As described by
Hansen et al. (2010), the FAO provides the premier global database on forest
cover but the data have several features that should be considered in
interpreting analyses. These include (i)
different methods to quantify forest change among all countries; (ii) the
definition of “forest” is based on land use instead of land cover; (iii) forest
area changes are reported only as net values; and (iv) forest definitions used
in successive reports have changed over time.
Human Wellbeing and Sustainable Development Indicators and
Biodiversity Indicators
No correlation was found, at global level, for
any of the biodiversity indicators across either HWB or SD indicators, nor was
any correlation found for changes over 15 years for the selected HWB or SD
indicators. There could be several reasons for this result. First, the link between
sustainable development/human wellbeing is confounded by the multitude of other
influences beyond biodiversity (for example, economic issues such as perverse
incentives) and the complex interactions between these other influences may not
be yet well enough understood to be measured. Second, several of the sustainable development indicators used today (including
those in this study) do not fully integrate biodiversity into the calculations,
as noted above in the individual indicator descriptions. Third, conservation happens at a local level
and local impacts and conservation successes may not be reflected in a national
indicator or at global level. Fourth,
national level indicators do not always include impacts from external
sources. With respect to changes over
time, as noted above regarding forest data, changes in definitions and scope
over time can confound synthesis and analysis of data collected across many
sources. In addition, there is likely a
time lag between changes in biodiversity status and measurable impacts on human
wellbeing and vice versa.
The negative correlation seen in Africa across HDI and two of the
biodiversity indicators and ANS and forest cover is also interesting. Lower forest cover or PA coverage accompanied
by increasing HDI suggests that Africa, as compared to other continents,
continues to be heavily reliant on using natural resources to support HWB. The negative correlation for Africa across
ANS and both forest cover and biocapacity is counterintuitive, since ANS
purports to measure national ‘savings’ including natural capital, yet the
correlation in Africa across forest cover and biocapacity shows that as these
values decrease (meaning lower natural capital) the ANS value increases. The positive correlation between changes in
PA coverage and ANS in Europe and Asia, however, does support the concept that
protected areas represent an investment in national natural capital and wealth.
Based on this review, a comparison of the national level biodiversity
indices across either HWB or SD indices used here showed no correlations at
global level along with some correlations at continental level, with several of
the latter being difficult to explain. However, this exercise was far from comprehensive and continuing to
explore other HWB or SD indicators, and combinations thereof, may provide different
results. For example, Mikkelson et al.
(2007) conclude that including indicators for economic inequality, such as the
GINI index, can significantly improve prediction of biodiversity loss, although
the number of countries reviewed was limited both by availability of
biodiversity data and time-relevant GINI measurements. In addition, comparison of changes in
indicators across different time frames, to allow for delays in impacts to be
measured, may also provide useful information.
Another lesson gained from this exercise to
demonstrate or monitor the relationships between biodiversity and HWB or SD, is
that some of the indicators commonly used to assess progress in human wellbeing
and sustainable development may not be telling us what we really need to know. For example, 88% of countries are in medium
or high development for HDI but neither the potential cost nor longer term
implications of that development on biodiversity and ecosystem services appear
to be reflected in the indicator. As
noted above, ANS which measures national ‘savings’ appeared to increase with
decreasing biodiversity in at least one continent. Similarly, the Ecological Footprint is
tracking demand on biological capacity yet demonstrated few correlations with
any of the biodiversity indicators, which should provide information on the
status of the raw material providing that capacity in this review.
As the conservation community debates the many
options for the next CBD Strategic Plan, the formulation of any targets within
that Plan should consider the challenges faced by measuring the links between
biodiversity conservation and supporting human well being and poverty
reduction. McNeely (2009) notes that the
2010 framework is stated in a way that makes assumptions about the link between
biodiversity conservation and poverty reduction that is “…perhaps best regarded
as an hypothesis that is likely to show considerable variability at different
geographical scales”. These challenges
notwithstanding, should the Parties decide to include the role of biodiversity
conservation in supporting human well being in a future framework for action,
any strong correlations resulting from a comparison across biodiversity and
development indicators would be useful to identify data that should or could be
highlighted therein. No matter which
way Parties choose to include a link with human wellbeing and poverty reduction
in the next framework, the inability to explicitly make the link through
indicators should not stop or delay biodiversity conservation actions that are
urgently needed both to support human wellbeing and biodiversity itself.
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