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CIFOR’s Robert Nasi to U.S. congressional staff: wildlife trade, ecosystem degradation and climate change, major drivers of emerging infectious diseases

Wildmeat database on hunting offtakes, consumption, market sales and more to launch in 2021
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Robert Nasi, Director General, Center for International Forestry Research (CIFOR), speaks during the Opening Plenary at the Global Landscapes Forum, Nairobi in this file picture from August 2018. CIFOR

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Ample evidence exists to show that landscape changes resulting from ecosystem fragmentation and degradation are major drivers of the emergence or re-emergence of zoonotic diseases such as malaria, dengue fever, Ebola or Lyme disease, the director general of the Center for International Forestry Research (CIFOR) said in a briefing to U.S. congressional staff and Washington-based agencies on Friday.

“Different mechanisms are involved, but landscape change and biodiversity loss cause major shifts in the ecology of pathogens and their vectors,” said Robert Nasi, who was invited to serve as a panelist at the educational briefing organized by the International Conservation Caucus Foundation (ICCF).

“These favor the expansion of hosts or vectors, increase pressure for virulence or resistance selection and/or for the evolution into more genetically diverse pathogens’ strains, increasing the probability that one of these strains can spill-over to humans.”

He spoke about assessing risk factors in bushmeat trade, habitat destruction, and biodiversity loss with two other environmental experts on a panel moderated by Bill Millan, global policy director of ICCF, which raises awareness of conservation concerns among policymakers.

Through the  Sustainable Wildlife Management (SWM) Programme, CIFOR works in partnership with the U.N. Food and Agriculture Organization (FAO), Wildlife Conservation Society (WCS) and the French Agricultural Research Centre for International Development (CIRAD) to develop models that aim to conserve wildlife and protect ecosystems, while improving living conditions and food security of people dependent on these resources.

Eight models are being developed in 13 countries where SWM partners work closely with national authorities and other local institutions.

Nasi’s full remarks follow:

  • Bushmeat (wild meat) trade

Wild meat is a critical source of protein, fat, micronutrients and a key element in income diversification, for millions of people across the tropics and subtropics. In rural areas, Indigenous Peoples and Local Communities depend on wild meat because they have no other source of meat or cannot afford alternative sources. For families living in provincial towns located close to sources of wild animals, eating wildlife may also still be a dietary necessity. Dependence on wild meat increases at places and times where other food supplies and sources of livelihoods are disrupted, such as during economic hardship, civil unrest or drought or the current pandemic.

Up to 11 million tons of wild meat are harvested per year in rainforests only; much more if we add other biomes (savannas, temperate and boreal forests). This makes wild meat harvesting and trade a major biodiversity threat for hundreds of species, including non-human primates and emblematic large mammal species. As animals progress along wildlife meat value chains, spill-over risks increase with the opportunity for human contacts (hunters, traders, butchers, cooks, and consumers).  It is therefore of the utmost importance to document this thoroughly.

CIFOR and partners funded by USAID (U.S. Agency for International Development) and USFWS (U.S. Fish and Wildlife Service), are developing the WILDMEAT database (launch in 2021). This will provide data to policy makers and practitioners on hunting offtakes, household consumption and market sales. This becomes extremely timely, given the covid-19 pandemic. The database can be used to identify areas where there is intensive use and trade of key vector species (i.e. bats, primates, pangolins), and, in conjunction with other global data layers (such as forest loss, agricultural intensification, and human population density) to analyse and predict where ‘hotspots’ for spill-over risk might occur.

In the broadly prevalent view, the co-evolution of new capacities creates new opportunities for pathogens but given that mutations are both rare and undirected, the highly specialized nature of pathogen-host relationships should produce an evolutionary firewall limiting dissemination; EID events should be rare. Well, Emerging Infectious Disease (EID) events increased 5-fold between 1940-2010. The authors of the “Stockholm Paradigm” state indeed “Pathogens, however, have become far better at finding us than our traditional understanding predicts.” Why?

  • Environmental degradation; land use changes

There is ample evidence that both permanent and temporary landscape changes resulting from ecosystem fragmentation and degradation are major drivers of the emergence or re-emergence of zoonotic diseases such as malaria, dengue fever, Ebola or Lyme disease.

Different mechanisms are involved but landscape change and biodiversity loss cause major shifts in the ecology of pathogens and their vectors. These favour the expansion of hosts or vectors, increase pressure for virulence/resistance selection and/or for the evolution into more genetically diverse pathogens’ strains, increasing the probability that one of these strains can spill-over to humans.

CIFOR, supported by U.S. Agency for International Development funding, demonstrated that deforestation accelerates the spread of Ebola in the rainforests of West and Central Africa by increasing human-bat interactions. When the flying frugivores are unsettled by human activities leading to deforestation, their habitats expand, increasing their contact with people and influencing the spread of disease. And there are many other examples in the scientific literature.

  • Climate change

Global warming has triggered modifications in the density and distribution of wildlife host species and disease reservoirs, expanding the geographic occurrence of infectious diseases and resulting in EID events in areas previously free of vectors and associated pathogens: malaria, yellow fever, chikungunya, zika, dengue (mosquitoes); Lyme (tick).

Extreme events (flooding, drought, heatwaves) increase the risks of EID outbreaks (e.g. malaria and hantavirus) creating optimal conditions for host or vectors, leading to their congregation (wild migratory birds for avian influenza viruses) or over abundance (mosquitoes or ticks).

  • Globalized trade and travel

Whether for curiosity, commerce or conflict, we move ourselves and associated species throughout the world to unprecedented degrees at unprecedented rates, increasing the diversity and frequency of pathogen encounters. Flying pigs from Russia to China using 747 is probably not a good idea in EID risk and GHG emission terms and this is only an example.

  • Increasing urbanization

Cities are warm – more than surrounding areas — ideal incubators for pathogens and vectors. Urban dwellers depend on a constant flow of materials from outside sources, increasing the chances for pathogen introduction. Cities harbor large number of animals (rodents, birds, insects) themselves vectors for diseases and high-density concentrations of people increasing chances of exposure. Every city includes poorly educated, nourished, and paid people exposed to physical exhaustion, stressful, unsanitary, conditions, invisible to the public health and social services networks. They cannot afford to stay at home when they are ill and become the Achilles Heel for EID.

Then, climate change interacts in synergy with land use/cover change, ecological changes and/or social inequities weakening marginal and poor population immune systems to influence disease patterns by creating new human-wildlife interfaces or leading to more intense interactions.

Finally, I would like to thank again USAID and USFWS support to CIFOR work on bushmeat, biodiversity and resilience and ICCF for offering me the opportunity to present this testimony.

Full details about the SWM Programme:

The Sustainable Wildlife Management Programme is an initiative of the African, Caribbean and Pacific (ACP) Group of States and is funded by the European Union through the 11th European Development Fund (EDF). The SWM Programme mobilizes an international group of partner organizations with experience and expertise in wildlife conservation, food security and policy development. It is implemented through a consortium partnership, which includes the Food and Agriculture Organization of the United Nations (FAO), the Centre for International Forestry Research (CIFOR), Wildlife Conservation Society (WCS) and the French Agricultural Research Centre for International Development (CIRAD).  

The SWM Programme is developing innovative, collaborative and scalable new models that aim to conserve wildlife and protect ecosystems, while at the same time improving the living conditions and food security of the people who depend on these resources. Eight models are being developed in 13 pilot countries, of which 12 are ACP countries. In each country, the SWM partners are working closely with national authorities and other local institutions. Through these practical experiences, the SWM Programme will achieve the following six results:  

– “The institutional and legal framework for the sustainable use of meat from wild species resilient to hunting or fishing is improved” (Result 1) led by FAO;

– “Management of wild species resilient to hunting or fishing is improved” (Result 2) led by CIRAD; 

– “Supply of alternative protein is improved” (Result 3) led by WCS; 

– “Consumption of wild meat becomes sustainable” (Result 4) led by CIFOR; 

– “Monitoring, evaluation and learning” (Result 5) led by CIFOR;  

– “Knowledge is generated to support the development and adoption of public policies that reconcile conservation issues and food and nutrition security” (Result 6) led by CIRAD.  

The SWM Programme directly contributes to the 2030 Agenda for Sustainable Development, including the Sustainable Development Goals (SDGs). It supports governments in their work to achieve Goal 2 on Zero Hunger; Goal 12 on Responsible Consumption and Production; and Goal 15 on Life on Land. It also indirectly contributes to Goal 3 on Good Health and Well-Being; Goal 5 on Gender Equality; Goal 11 on Sustainable Cities and Communities and Goal 16 on Peace, Justice and Strong Institutions.

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For more information on this topic, please contact Robert Nasi at r.nasi@cgiar.org.
This research forms part of the CGIAR Research Program on Forests, Trees and Agroforestry, which is supported by CGIAR Fund Donors.
This research was supported by USAID, USFWS
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