ity of change) of how bioturbation changes
following extinction depend on the order in
which species are lost, because extinction
risk is frequently correlated with life-history
traits that determine the intensity of bio-
turbation. This finding is important because
it argues that the particular cause of extinc-
tion ultimately governs the ecosystem-level
consequences of biodiversity loss. Therefore,
if we are to predict the ecological impacts of
extinction and if we hope to protect coastal
environments from human activities that
disrupt the ecological functions species
perform, we will need to better understand
why species are at risk and how this risk
covaries with their functional traits.
References and Notes
1. G. C. B. Poore, G. D. F. Wilson, Nature 361, 597 (1993).
2. P. G. Falkowski et al., Science 281, 200 (1998).
3. P. Vitousek, H. Mooney, J. Lubchenco, J. Melillo,
Science 277, 494 (1997).
4. R. E. Turner, N. N. Rabalais, Nature 368, 619 (1994).
5. J. B. C. Jackson et al., Science 293, 629 (2001).
6. M. Jenkins, Science 302, 1175 (2003).
7. D. Malakoff, Science 277, 486 (1997).
8. O. E. Sala et al., Science 287, 1170 (2000).
9. M. C. Emmerson, M. Solan, C. Emes, D. M. Paterson,
D. Raffaelli, Nature 411, 73 (2001).
10. C. L. Biles et al., J. Exp. Mar. Biol. Ecol. 285, 165
11. S. G. Bolam, T. F. Fernandes, M. Huxham, Ecol.
Monogr. 72, 599 (2002).
12. D. Raffaelli, M. Emmerson, M. Solan, C. Biles,
D. Paterson, J. Sea Res. 49, 133 (2003).
13. B. Schmid et al., in Biodiversity and Ecosystem
Functioning, M. Loreau, S. Naeem, P. Inchausti, Eds.
(Oxford Univ. Press, Oxford, 2002), pp. 61–75.
14. D. S. Srivastava, Oikos 98, 351 (2002).
15. C. R. Tracy, T. L. George, Am. Nat. 139, 102 (1992).
16. S. L. Pimm, H. L. Jones, J. Diamond, Am. Nat. 132,
17. M. L. McKinney, Annu. Rev. Ecol. Syst. 28, 495
18. D. Pauly, V. Christensen, J. Dalsgaard, R. Froese,
F. Torres Jr., Science 279, 860 (1998).
19. J. E. Duffy, Ecol. Lett. 6, 680 (2003).
20. A. R. Ives, B. J. Cardinale, Nature 429, 174 (2004).
21. M. D. Smith, A. K. Knapp, Ecol. Lett. 6, 509 (2003).
22. M. Jonsson, O. Dangles, B. Malmqvist, F. Gue ´rold,
Proc. R. Soc. London B Biol. Sci. 269, 1047 (2002).
23. U. Witte et al., Nature 424, 763 (2003).
24. K. S. Johnson et al., Nature 398, 697 (1999).
25. Materials and methods are available as supporting
material on Science Online.
26. J. L. Ruesink, D. S. Srivastava, Oikos 93, 221 (2001).
27. M. Solan, R. Kennedy, Mar. Ecol. Prog. Ser. 228, 179
28. J. H. Lawton, in Population Dynamic Principles, J. H.
Lawton, R. M. May, Eds. (Oxford Univ. Press, Oxford,
1995), pp. 147–163.
29. K. F. Davies, C. F. Margules, J. F. Lawrence, Ecology
85, 265 (2004).
30. C. N. Johnson, Nature 394, 272 (1998).
31. D. D. Doak et al., Am. Nat. 151, 264 (1998).
32. J. M. Fischer, T. M. Frost, A. R. Ives, Ecol. Appl. 11,
33. D. K. Jacobs, D. R. Lindberg, Proc. Natl. Acad. Sci.
U.S.A. 95, 9396 (1998).
34. We thank J. E. Duffy, J. D. Fridley, A. Hector, A. R.
Ives, S. Naeem, O. L. Petchey, K. J. Tilmon, D. A.
Wardle, and J. P. Wright for comments and the
BIOMERGE Second Adaptive Synthesis Workshop for
insightful discussion. Supported by BIOMERGE (Biotic
Mechanisms of Ecosystem Regulation in the Global
Environment)—an NSF-funded research coordina-
tion network (to S. Naeem).
Supporting Online Material
Materials and Methods
Equations S1 and S2
23 July 2004; accepted 23 September 2004
Bushmeat Hunting, Wildlife
Declines, and Fish Supply in
Justin S. Brashares,1,2* Peter Arcese,3Moses K. Sam,4
Peter B. Coppolillo,5A. R. E. Sinclair,6Andrew Balmford1,7
The multibillion-dollar trade in bushmeat is among the most immediate
threats to the persistence of tropical vertebrates, but our understanding of its
underlying drivers and effects on human welfare is limited by a lack of
empirical data. We used 30 years of data from Ghana to link mammal declines
to the bushmeat trade and to spatial and temporal changes in the availability
of fish. We show that years of poor fish supply coincided with increased
hunting in nature reserves and sharp declines in biomass of 41 wildlife species.
Local market data provide evidence of a direct link between fish supply and
subsequent bushmeat demand in villages and show bushmeat’s role as a
dietary staple in the region. Our results emphasize the urgent need to develop
cheap protein alternatives to bushmeat and to improve fisheries management
by foreign and domestic fleets to avert extinctions of tropical wildlife.
The trade in bushmeat for human consump-
tion is a key contributor to local economies
throughout the developing world (1, 2), but it
is also among the greatest threats to the
persistence of tropical wildlife (1–4). Efforts
to manage the bushmeat trade are built on the
premise that bushmeat consumption is driven
by protein limitation. Thus, it is assumed that
increases in livestock and agricultural produc-
tion will reduce human reliance on wild
sources of food (5–7). Although it makes
intuitive and economic sense that consump-
tion of wild meat would be linked to the
availability of alternative sources of protein,
there is little empirical evidence to support
this assumption, particularly at large geo-
graphic scales (1, 5–7). Furthermore, contrary
to predictions of the Bprotein limitation[
hypothesis, unsustainable consumption of
wildlife remains a problem even in many
relatively prosperous countries (1). Identifying
bushmeat_s value as a dietary staple versus a
nonessential good is vital for targeting con-
servation interventions and, equally important,
for predicting the impacts of wildlife declines
on human livelihoods.
We evaluated the protein limitation hy-
pothesis by comparing annual rates of
decline for 41 species of wild carnivores,
primates, and herbivores (table S1) in six
nature reserves in Ghana with supply of fish
in the region from 1970 to 1998. As is the
case across the tropics, wild terrestrial
mammals are used as a secondary source of
animal protein in Ghana, and they comprise
the chief commodities in a regional bush-
meat trade estimated conservatively at
400,000 tons per year (8). Marine and
freshwater fish are the primary source of
animal protein consumed in West Africa,
and the fisheries sector directly and indirect-
ly accounts for up to one quarter of the
workforce in the region (9, 10). From 1965 to
1998, the supply of harvested fish in Ghana
(Fig. 1A) ranged from 230,000 to 480,000
tons annually and varied by as much as 24%
between consecutive years (11). Here, we
test a prediction of the protein limitation hy-
pothesis that years with low fish supply will
show larger declines in biomass of terrestrial
mammals, suggesting a transfer of harvest
pressure and consumption between these
resources. We also test for evidence of a
mechanism underpinning such a transfer by
examining (i) rates of hunting in nature
reserves, (ii) sales and price data from local
markets, and (iii) spatial trends in correla-
tions of fish supply and wildlife declines.
1Conservation Biology Group, Department of Zool-
ogy, University of Cambridge, Cambridge CB2 3EJ,
and Management, University of California, Berkeley,
CA 94720, USA.
Research, University of British Columbia, Vancouver,
BC V6T 1Z4, Canada.4Ghana Wildlife Division, Accra,
University of British Columbia, Vancouver, BC V6T
1Z4, Canada.7Percy Fitz Patrick Institute of African
Ornithology, University of Cape Town, Rondebosch
7701, Cape Town, South Africa.
2Department of Environmental Science, Policy
3Centre for Applied Conservation
5Wildlife Conservation Society, Bronx, NY
6Centre for Biodiversity Research,
*To whom correspondence should be addressed.
R E P O R T S
12 NOVEMBER 2004 VOL 306 SCIENCE www.sciencemag.org
In support of the prediction that annual
standing biomass of large mammals would
be linked positively with the annual supply
of marine and freshwater fish, we found that
changes in annual biomass of terrestrial
mammals from 1970 to 1998 were closely
related to annual per capita fish supply.
Years with a lower-than-average supply of
fish had higher-than-average declines in
mammal biomass, and vice versa (Fig. 1B)
(12). In contrast, fish supply and wildlife
declines were unrelated to other potential
explanatory factors, including annual rain-
fall, land and water temperatures, political
cycles, oil prices, and gross national prod-
uct (P Q 0.19 for each term in multiple-
regression models) (13). This correlative
support for the protein limitation hypoth-
esis is further supported by three additional
First, our working hypothesis suggests
that the observed link between fish supply
and wildlife decline occurs because bush-
meat hunting and consumption increased
when fish became scarce. In support of this
suggestion, we found that annual counts of
hunters observed by wildlife rangers in five
nature reserves in Ghana (13) were related
negatively to per capita fish supply from
1976 to 1992 (Fig. 2A). Annual counts of
hunters were also closely related to annual
rates of wildlife decline in these same nature
reserves (R 0 0.76, n 0 17, P G 0.01). Thus,
hunters were more common in reserves in
years when fish supply was low, and these
increases in hunters were linked to acceler-
ated declines of wildlife.
Second, if annual variation in fish supply
and bushmeat hunting are linked causally,
we would expect that the availability of
bushmeat in local markets would be related
negatively to the supply of fish (5). In
support of this prediction, we found that
monthly supply of fish in 12 local markets in
northern, central, and eastern Ghana from
1999 to 2003 (13) was related negatively to
the volume of bushmeat sold in these mar-
kets (Fig. 2B). In addition, the price of fish
sold in markets was closely and negatively
related to local fish supply (R 0 0.73, n 0 52,
P G 0.01) and positively related to the
volume of bushmeat sold (R 0 0.48, n 0 52,
P G 0.01). The strong negative correlation
between fish price and quantity sold, com-
bined with the positive correlation between
fish price and bushmeat sales, is consistent
with the idea that variation in fish supply
drove bushmeat sales. Comparing monthly
fish price in markets with the bushmeat sales
in the following month yielded even stronger
correlations, again suggesting that bushmeat
sales were driven by fish availability and
price more so than the reverse case (fig. S1).
These results show a substitution of wildlife
for fish at the local scale. Taken together
with the observation of increased bushmeat
hunting during periods of fish scarcity, these
results also support our suggestion of a
causal, macroscale link between fish supply
and wildlife declines (Fig. 1).
Third, more than half of Ghana_s human
population of 20 million resides within 100
km of the coast, where the majority of
employment and dietary protein are derived
from fishing (10). Poor fish harvests result in
reduced income and food for coastal com-
munities and reduce the availability of fish
throughout the region (9, 14). The wide-
spread loss of jobs and income associated
with poor fish harvests also may lead some
portion of households to rely on bushmeat
hunting both for income and sustenance. If
fish supply and bushmeat consumption are
linked causally, it follows that the transfer of
harvest pressure between aquatic and terres-
trial resources would be most evident in
Fig. 1. Year-to-year change in es-
timated biomass of 41 large mam-
mal species was linked closely to
annual harvest of marine and
freshwater fish in Ghana (R 0
0.73, n 0 28 years, P G 0.001).
(A) Time series plots of annual
fish supply and change in esti-
mated mammal biomass. (B)
Conventional plot of data shown
in (A). The trend line describes
the equation y 0 0.0058x þ 0.81.
Values of annual fish supply
[from (11)] represent landings
plus imports and minus exports.
Biomass of large mammals was
calculated for each year by mul-
tiplying the number of animals
observed in È700 walking counts
of 10 to 15 km each (17) by
species-specific body weights.
The products of these calcula-
tions were then summed across
Fig. 2. Links between fish supply and bushmeat
hunting and consumption are evident in ob-
servations that (A) annual counts of hunters in
five terrestrial reserves in Ghana from 1976 to
1992 were related negatively to supply of fish
in the region (R 0 –0.52, n 0 17, P 0 0.03); (B)
monthly sales of bushmeat in 12 rural markets
in Ghana were related negatively to local fish
supply (R 0 –0.61, n 0 52, P G 0.01); and (C)
fish supply and wildlife declines were related
most closely in reserves occurring nearest to
the coast (R 0 0.81, n 0 6, P 0 0.05).
R E P O R T S
www.sciencemag.orgSCIENCEVOL 30612 NOVEMBER 2004
coastal areas where reliance on fish for both
income and animal protein is greatest. We
tested this last prediction by repeating the
analysis in Fig. 1 separately for each of six
nature reserves in Ghana. We found the
strongest link between annual variation in
marine and freshwater fish supply and annual
change in mammal biomass in reserves near
the coast and weaker, though still significant,
linkages for reserves farther inland (Fig. 2C).
These three lines of evidence indicate
that fish supply is linked negatively to the
price of fish, the number of wildlife hunters,
and the sales and supply of bushmeat in local
markets. Our results also show that the sub-
stitution of fish for bushmeat occurs most
intensively close to the coast, where fish are
more important as sources of food and
income. All of these findings are consistent
with the protein limitation hypothesis and
inconsistent with the notion that bushmeat in
Ghana is primarily a nonessential good
(summarized in fig. S2).
Our results provide clear evidence to
suggest that the outcomes of programs aimed
at promoting economic development, food
security, and the conservation of biological
diversity in Ghana, and perhaps elsewhere in
Africa, will be closely linked. First, the close
correlation between hunting pressure, mar-
kets, and long-term trends in wildlife abun-
dance suggests strongly that the persistence
of the more than 400 species of terrestrial
vertebrates that supply the bushmeat trade in
West Africa will depend ultimately on the
availability of affordable alternative protein
sources for the region_s growing human
population. Second, our failure to conserve
existing wildlife populations as core sources
for managed, sustainable harvests could have
serious deleterious effects on the stability of
the long-term human food supply and the
livelihoods of bushmeat hunters and sellers.
Our findings and those of others suggest that
the harvest of terrestrial wildlife can buffer
the impact of environmental or other shocks
by providing animal protein and income in
times of economic hardship or food scarcity
(2, 15, 16). However, marked declines in large
mammal abundance and marine and fresh-
water fish stocks documented in the region over
the past 30 years now suggest that this buffer
system can no longer be sustained (14, 17–20).
From 1970 to 1998, the biomass of 41
species of mammals in nature reserves in
Ghana declined by 76% (Fig. 3), and 16 to
45% of these species became locally extinct
(17). Similarly, trawl surveys conducted in
the Gulf of Guinea since 1977 and other
regional stock assessments estimate that fish
biomass in nearshore and offshore waters has
declined by at least 50% (Fig. 3). At the
same time, a threefold increase in human
populations in the region since 1970 has
resulted in per capita declines in fish supply,
despite steady increases in regional fish
harvests (11, 14). These sharp declines in
terrestrial wildlife and marine fish suggest
that stocks in this region may face imminent
collapse (9, 18). The consequences of col-
lapse of either fish or terrestrial wildlife are
daunting and may be felt immediately as
widespread human poverty and food inse-
curity in the region (14). Reduced fish stocks
have already severely damaged the region_s
artisanal fisheries sector (14, 21), and recent
collapses of mammal populations in some
areas of West Africa have been linked to geo-
graphic patterns of poverty and malnourish-
ment (8, 17). Agricultural production is a
third potentially critical, though poorly un-
derstood, factor linking human food supply to
biodiversity conservation in the region (16).
One management response to the poten-
tial collapse of fish and terrestrial wildlife
stocks in West Africa is to build up region-
al livestock and agriculture sufficiently to
alleviate pressure on overexploited wild
resources (7). However, such efforts could
take decades to implement and face enor-
mous economic, regulatory, and political
hurdles. Thus, more immediate plans to
enhance the sustainability of wild protein
sources are required. One immediate route
to increasing production and sustainability of
domestic fisheries, and thereby reducing
pressure on terrestrial wildlife, is to limit
the access of large and heavily subsidized
foreign fleets to fish off West Africa (18–24).
Declines of fish stocks in nearshore and
offshore waters of West Africa have coin-
cided with more than 10-fold increases in
regional fish harvests by foreign and domes-
tic fleets since 1950 (11). The European
Union (EU) has consistently had the largest
foreign presence off West Africa, with EU
fish harvests there increasing by a factor of
20 from 1950 to 2001 (fig. S3). Furthermore,
EU financial support of its foreign fleet
increased from about $6 million in 1981 to
more than $350 million in 2001 (fig. S3),
with the effect of artificially increasing the
profitability of fishing in African waters for
EU boats, despite declining fish stocks (22).
West African commercial fleets also have
expanded considerably since 1950 (fig. S3)
and there is no guarantee that reductions of
foreign catches would not be taken up by
increased domestic fishing. However, even
short-term increases in the domestic supply
of fish both for commercial export and local
consumption may enhance regional econo-
mies (14) and ease exploitation of terrestrial
wildlife resources. Over the longer term,
intensive management to enhance fish stocks
and stabilize harvests must become a region-
al conservation and economic priority.
A second route to increase the sustainabil-
enhancing the protection of harvested marine
and terrestrial resources. Pirate fishing ves-
sels from foreign ports are abundant in West
African waters and illegally extract fish of the
highest commercial value while, like many
commercial fleets, dumping 70 to 90% of
their haul as by-catch (9, 18). Increased
policing of exclusive fishing zones and
enforcement of existing quotas and tariffs
for commercial fleets should reduce exploi-
tation and provide an immediate boost to
marine resources available to local fisheries
(14, 19). On land, wildlife has persisted at
near historic levels in inaccessible and well-
protected areas of West Africa_s nature
reserves (4, 17). Increasing the size, number,
and protection of wildlife reserves in the
region may not offer a long-term solution to
concerns over human livelihoods and protein
supply, but it is likely to offer the most
immediate prospects for slowing the region_s
catastrophic wildlife decline.
References and Notes
1. J. G. Robinson, E. L. Bennett, Hunting for Sustain-
ability in Tropical Forests (Columbia Univ. Press, New
2. E. J. Milner-Gulland et al., Trends Ecol. Evol. 18, 351
3. J. G. Robinson, K. H. Redford, E. L. Bennett, Science
284, 595 (1999).
4. World Conservation Union, International Union for
Conservation of Nature and Natural Resources
(IUCN) Red List of Threatened Animals (IUCN, Gland,
5. D. S. Wilkie, R. A. Godoy, Science 287, 975 (2000).
6. E. L. Bennett, Conserv. Biol. 16, 588 (2002).
Fig. 3. Estimates of marine fish
biomass in the Gulf of Guinea
(gray circles) and large mammal
biomass in Ghana (black circles).
Estimates of fish biomass are
from trawl surveys (24, 25). Ana-
lyses of fisheries catch data with
ecosystem models indicate that
fish biomass in coastal West and
Northwest Africa has declined by
a factor of 13 since 1960 (20).
Estimates of mammal biomass
are based on abundances of 41
species observed in È700 wildlife
counts per year in six nature
reserves (17) (see map, fig. S4).
R E P O R T S
12 NOVEMBER 2004VOL 306 SCIENCE www.sciencemag.org
7. Organisation for Economic Co-operation and Devel- Download full-text
opment (OECD), Shaping the 21st Century: The
Contribution of Development Cooperation (OECD,
8. Y. Ntiamoa-Baidu, Wildlife Development Plan: 1998–
2003 (Wildlife Department, Accra, Ghana, 1998).
9. United Nations Environment Programme (UNEP), Africa
Environment Outlook; available at www.unep.org/aeo.
10. Food and Agriculture Organization (FAO), Country
Profiles: Ghana; available at www.fao.org/country-
11. Foodand Agriculture Organization (FAO),Fisheries Data-
bases; available at www.fao.org/fi/statist/statist.asp.
12. Statistics are based on a linear regression of annual
change in mammal biomass [calculated as (kgt þ 1)/
kgt] against per capita fish harvest. Regressing per
capita change in mammal biomass [i.e., (kgt þ 1–
kgt)/human populationt þ 1] against per capita fish
catch gave a similar result (adjusted R20 0.52, P G
13. Materials and methods are available as supporting
material on Science Online.
14. J. Atta-Mills, J. Alder, U. R. Sumaila, Nat. Resour.
Forum 28, 13 (2004).
15. C. B. Barrett, P. Arcese, Land Econ. 74, 449 (1998).
16. G. J. S. Dei, Ecol. Food Nutr. 22, 225 (1989).
17. J. S. Brashares, P. Arcese, M. K. Sam, Proc. R. Soc.
Lond. Ser. B. 268, 2473 (2001).
18. Food and Agriculture Organization (FAO), The State
of World Fisheries and Aquaculture 2002; available at
19. D. Pauly et al., Nature 418, 689 (2002).
20. V. Christensen et al., in Pe ˆcheries Maritimes, Ecosys-
te `mes et Socie ´te ´s: Un Demi-Sie `cle de Changement, B. A.
Moctar, P. Chavance, D. Gascuel, M. Vakily, D. Pauly,
Eds. (Institut de Recherche pour le Developpement,
21. World Wide Fund for Nature (WWF), West Africa Puts
EU To Shame (WWF European Policy Office, Brussels,
22. V. M. Kaczynski, D. L. Fluharty, Mar. Policy 26, 75 (2002).
23. S. L. Pimm et al., Science 293, 2207 (2001).
24. Sea Around Us Project (SAUP), Web Products: Marine
Database; available at www.seaaroundus.org.
25. Ghana Marine Fisheries Research Division (MFRD),
Oceanographic Data Centre, Marine database; available
26. We thank the Ghana Wildlife Division for permis-
sion to work in reserves and access to data, and we
thank J. Atta-Mills for discussion. C. Kresge, P. Kresge,
J. Mason, B. Volta, N. Ankudey, D. Boateng, L. Lanto,
and G. Agbango provided assistance in Ghana, and
C. Barrett, J. Hellmann, D. Pauly, I. Watson, J. Smith,
V. Christensen, E. J. Milner-Gulland and four
anonymous reviewers gave many helpful sugges-
tions. Supported by NSF INT-0301935 (J.S.B.).
Supporting Online Material
Materials and Methods
Figs. S1 to S5
Tables S1 and S2
7 July 2004; accepted 7 October 2004
The Genetic Basis of Singlet
Oxygen–Induced Stress Responses
of Arabidopsis thaliana
Daniela Wagner,1*. Dominika Przybyla,1* Roel op den Camp,1
Chanhong Kim,1Frank Landgraf,1Keun Pyo Lee,1Marco Wu ¨rsch,1
Christophe Laloi,1Mena Nater,1Eva Hideg,2Klaus Apel1-
Plants under oxidative stress suffer from damages that have been interpreted
as unavoidable consequences of injuries inflicted upon plants by toxic levels
of reactive oxygen species (ROS). However, this paradigm needs to be
modified. Inactivation of a single gene, EXECUTER1, is sufficient to abrogate
stress responses of Arabidopsis thaliana caused by the release of singlet
oxygen: External conditions under which these stress responses are observed
and the amounts of ROS that accumulate in plants exposed to these envi-
ronmental conditions do not directly cause damages. Instead, seedling le-
thality and growth inhibition of mature plants result from genetic programs
that are activated after the release of singlet oxygen has been perceived by
Abiotic stress conditions limit the ability of
plants to use light energy for photosynthesis,
often reducing their growth and productivity
and causing photooxidative damages (1–3).
The emergence of these stress symptoms has
been closely associated with the enhanced
production of several ROS (4, 5). Because
different ROS are generated simultaneously, it
is difficult to determine the biological activity
and mode of action for each of these ROS
separately. In order to address this problem,
one would need to find conditions under
which only one specific ROS is generated at
a given time, within a well-defined subcellular
compartment, and which also triggers a
visible stress response that is easy to score.
Recently, we have isolated the condition-
al flu mutant of Arabidopsis thaliana that
fulfills these requirements (6). The mutant
generates singlet oxygen in plastids in a con-
trolled and noninvasive manner. Immediate-
ly after the release of singlet oxygen, mature
flu plants stop growing, whereas seedlings
bleach and die (6). Here, we demonstrate that
the two stress responses, growth inhibition and
seedling lethality, do not result from physico-
chemical damage caused by singlet oxygen
during oxidative stress but are caused by the
activation of a genetically determined stress
We set out to identify such a genetic pro-
gram by identifying second-site mutations
that abrogate either one or both of the two
stress responses of the flu mutant. Three
different groups of second-site mutations
could be distinguished (7) (fig. S1A). One of
these groups contained 15 mutants that
behaved like wild type when kept under non-
permissive light-dark conditions (7) Egroup III
(fig. S1, B to D)^. Allelism tests and mapping
revealed that they were allelic, representing a
single locus that was named EXECUTER1. In
contrast to wild-type plants but like flu, the
executer1/flu double mutant accumulated free
protochlorophyllide (Pchlide) in the dark (Fig.
1, A to C, and fig. S1B). After transfer to the
light, executer1/flu generated singlet oxygen
in amounts similar to those of flu (Fig. 1, F to
H) but grew like wild type when kept under
nonpermissive light-dark cycles (Fig. 1, A to
C). The second stress reaction of flu to the
release of singlet oxygen is an inhibition of
growth. In flu plants, the growth rate was
reduced immediately after the beginning of
reillumination (Fig. 1D). The executer1/flu
plants, however, grew like wild-type plants
(Fig. 1D). Growth inhibition of flu plants was
particularly striking when plants were trans-
ferred to repeated light-dark cycles, whereas
executer1/flu continued to grow like wild-type
plants (Fig. 1E). All three plant lines grew
equally well under continuous light (fig. S2).
As a first step toward the functional char-
acterization of EXECUTER1, we used a
map-based cloning strategy to isolate the
EXECUTER1 gene. EXECUTER1 was ge-
netically mapped on chromosome IV on a
genomic fragment of about 90 kb (Fig. 2A).
A contig consisting of 11 cosmid clones that
encompassed this chromosomal region was
generated (Fig. 2A), and the ability to com-
plement the executer1 mutation was tested
(7). Seedlings of the double mutant trans-
formed with the genomic DNA of the cosmid
clone 44 that contained a wild-type copy of
EXECUTER1 died like flu seedlings when
grown under nonpermissive dark-light con-
ditions, whereas seedlings of plants trans-
formed with genomic DNA of other cosmid
clones grew like seedlings of the original
executer1/flu parental line (Fig. 2B).
The second test was done with mature T2
plants transformed with DNA of cosmid
1Institute of Plant Sciences, Plant Genetics, Swiss Fed-
eral Institute of Technology (ETH), CH-8092 Zurich,
search Center, Hungarian Academy of Sciences, H-6701
2Institute of Plant Biology, Biological Re-
*These authors contributed equally to this work.
.Deceased 24 February 2004.
-To whom correspondence should be addressed. E-
R E P O R T S
www.sciencemag.org SCIENCE VOL 306 12 NOVEMBER 2004