sciencemag.org SCIENCE 360 28 JULY 2017 • VOL 357 ISSUE 6349
and input companies, and public extension
programs. Such linkages would detect bottlenecks to adoption of new technologies.
Common standards are required if data are
to be comparable across experimental variables, including germplasm, environments,
and other research interventions. High-throughput phenotyping and genotyping
protocols have some agreed standards (9,
13). Standardized protocols also add value in
modeling studies where core data sets drive
simulations, permitting alternative interventions to be evaluated and prioritized. Crop
models have been used to estimate impacts
of climate change on crop performance (4,
10), yet many breeding and agronomy data
sets do not fulfill core needs to drive models.
Research institutions and funding bodies could facilitate more timely data sharing
by prioritizing publication of results linked
to open-access data. Data sharing will drive
standardization toward more precise descriptions of environments and experimental treatments, and more “searchable” databases (14).
Although intellectual property (IP) rights are
necessary incentives for private investment,
greater access to data benefits all sectors. It
would be mutually beneficial to carefully define “precompetitive” research so that private
entities are encouraged to share nonsensitive
data more routinely in precompetitive mode
and when engaged in public-private partnerships (PPPs). Some transforming technologies could be made more accessible through
nonexclusive licenses, while ensuring that industry received returns on investments.
Networks like IWIN that have brought to-
gether a broad spectrum of partners—from
the CGIAR system, academia, NARS, and
the private sector—are now largely funded
by competitive (as opposed to core) funds,
with the attendant transaction costs and un-
predictability of funding that limits a longer-
term vision. Whereas the CGIAR has moved
its core agenda in other directions (includ-
ing upstream), many Western academic in-
stitutions are forging new bilateral projects
with traditional CGIAR partners (i.e., NARS
in LDCs). This reinforces the value of well-
coordinated multilateral partnerships to ac-
celerate impacts, the kind of role a GCIN can
provide. The expectation for crop research
programs to deliver positive outcomes on the
livelihoods of resource-poor people—another
dimension of the CGIAR’s expanded remit
(15)—is complex, as new crop technologies
are just one part of an equation that includes
factors such as credit, market forces, national
policy, etc. New collaborative paradigms en-
compassing a broader range of stakeholders,
as proposed here, would bolster such out-
comes, e.g., in the context of microfinanc-
ing and other PPPs. Yet a 2015 international
workshop on the promotion of PPPs orga-
nized by 10 international agencies—including
the CGIAR—identified uncertainty in fund-
ing of international programs as a key risk for
improved resilience of agri-food systems (15).
Increasingly high transaction costs associ-
ated with IPG work must also be addressed.
These are partly driven by liability and IP is-
sues, and partly by the prioritization of full
accountability and risk minimization, which
favor short-term, project-driven research over
longer-term, multilateral research programs.
One way to initiate and finance a GCIN
would be through structural re-arrangement
within the CGIAR, whose annual budget is
approximately US$900 million. For 2017, the
total budget expected for crop research—in-
cluding trait discovery, variety development,
and seed systems—is approximately $200
million, covering the major cereals, legumes,
roots, and tubers. These crop networks would
constitute the major components of a GCIN,
while additional investment would underpin
and improve NARS infrastructure, encompass underutilized crops—e.g., quinoa (16)—
and achieve cohesion and a strategic vision.
Some costs would be offset by economies of
scale, including shared infrastructure, data,
and best practices across crops. IWIN and
other crop-testing networks rely heavily on
voluntary data return, in exchange for shared
germplasm and other technologies generated
from initial investment in CGIAR programs.
A GCIN would thus count on substantial leverage of a massive body of human, physical,
and scientific capital from existing crop networks in return for shared benefits of multilateral collaboration and improved research
infrastructure. Recently established crosscutting CGIAR platforms, including one to
harness big data and another for modernization of breeding methods within CGIAR centers, would also contribute to a GCIN’s goals.
Some multinational seed companies
have invested heavily in infrastructure at
key research locations, and the model is no
less compelling for achieving food security
through provision of IPGs (e.g., Feed the
Future, CGIAR, Bill & Melinda Gates Foundation). Some elements of a GCIN could be
supported by hybrid funding mechanisms
such as the Foundation for Food and Agriculture Research model that requires 50%
private industry investment to receive government funding, or the Phytobiome Alliance PPP. There is an IP challenge when
private entities join forces, but many are
moving in the direction of cooperating at the
precompetitive level to share risks and costs
associated with basic research. With clear
definitions and agreements, investment by
industry in precompetitive areas would allow private companies to develop products
further down the line, while raising the technology bar for all. The notion that private entities would invest in a GCIN (with its LDC
focus) is supported by two key facts. First, the
G20 research priorities and those of LDCs
served by the CGIAR often overlap, providing
opportunities for international collaboration.
Second, future markets for crop commodities
will be dominated by current LDCs where
population is growing fastest and diets are
rapidly changing. The IWYP model is one
example where IP arrangements involving
global access to new germplasm have been
agreed across a global PPP.
A successful GCIN would likely require
a consortium of funding bodies to set the
agenda and put governance in place according to their own criteria. An evaluation process should be designed to estimate ex ante
and ex post returns to the network, and precedents are extremely favorable (3, 6, 7). At
this stage, the best way to promote a GCIN
is to elaborate a scientific rationale based on
precedents and opportunities. j
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The authors acknowledge support from the U.S. Agency for
International Development (USAID), the Bill & Melinda Gates
Foundation (OPP1052535), and the CGIAR Platform for Big
Data in Agriculture. The views and opinions in this paper are
those of the authors and not necessarily those of USAID. This
work is licensed under a Creative Commons Attribution 4.0
International (CC BY 4.0) license, which permits unrestricted
use, distribution, and reproduction in any medium, provided
the original work is properly cited. To view a copy of this license,
visit http://creativecommons.org/licenses/by/4.0/. This
license does not apply to figures/photos/artwork or other content included in the article that is credited to a third party; obtain
authorization from the rights holder before using such material.
“A successful GCIN would
likely require a consortium
of funding bodies...”
INSIGHTS | POLICY FORUM