Discussion
Our study encompassed a large timespan (60 weeks) and a variable
spectrum of bushmeat site categories including small to large urban
bushmeat markets and chop chop bars (maquis ). Although more
accurate proxies of the trade dynamics were not investigated (e.g.,
trends in biomass and income), our unprecedented survey design allows,
for the first time, to assess African bushmeat trade dynamics during and
after a national ban.
Trade dynamics in Côte d’Ivoire as measured per number of sellers was
strongly, negatively impacted by the COVID-19 lockdown and bushmeat ban,
as all bushmeat sites went down to a null number of sellers right before
or after the first governmental decisions were taken. This is in line
with our original expectation on the efficiency of governmental
measures. A significant reduction in carcass numbers was also observed
in Nigeria after lockdown (Funk et al., 2021). The COVID-19 pandemic has
shown that African states can be efficient in mitigating the bushmeat
trade when resources are duly mobilized, a notable point considering the
ongoing bushmeat crisis and the zoonotic outbreaks to come (D’Cruze et
al., 2020; Reynolds et al., 2019).
However, we observed significant differences in the dynamics of bushmeat
sites both during and after the strongest measures taken against the
COVID-19 pandemic, deviating from our posited expectation on trends
being similar between market types (as a measure of the effectiveness of
government interventions). We speculate that bushmeat trade dynamics are
affected by a combination of intrinsic market characteristics and
dissimilar levels of governmental interventions. For instance, Toumodi
restaurants were first to be fully closed (mid-March 2020, concomitantly
with the announcement on the bushmeat ban) and first to start
re-opening, at a time when all the bushmeat markets in Abidjan were
closing (early June 2020). This suggests that predicting bushmeat trade
dynamics under bans or restrictions is geographically and typologically
(i.e., type of market) dependent. State authorities may have been more
zealous in Toumodi by quickly applying the bushmeat ban before the
decision on closing maquis one week later, but prompt to release
pressure on sellers from a zone not affected by the lockdown (which was
restricted to Abidjan).
The Ivorian state was permissive with the resumption of the bushmeat
trade, as we observed a progressive return of sellers on the bushmeat
sites before the sanitary measures were lifted. Although global
trajectories among bushmeat sites were similar throughout the survey
period, significant trend differences were observed during the
constrained period. This reinforces our view that the dynamics of the
bushmeat trade are site-specific and shaped by multiple factors. In our
case, small (Abobo Grand Marché) or poorly accessible (Adjamé) markets
could have been less controlled than the largest bushmeat market of
Abidjan, Yopougon Siporex. The latter is clearly identified as the main
hub of the bushmeat trade in Côte d’Ivoire (Gossé et al., 2022) and was
the last to show sign of resumption, after the end of the sanitary
measures against COVID-19 (October 2020).
The COVID-19 lockdown and bushmeat ban had a long-term impact on the
bushmeat trade dynamics, as three months after the end of governmental
measures all the bushmeat sites in Côte d’Ivoire exhibited lower numbers
of sellers than before (c. 63 to 91% of the initial numbers). This
effect was still prevailing in three of the bushmeat markets from
Abidjan during our control survey eight months later (c. 56 to 91% of
the initial numbers), despite stronger growth rate in large markets such
as Yopougon Siporex. This clearly violates our initial assumption of
market network resilience to the lockdown.
Forecasting predictions after 92 weeks since the start of sanitary
measures in Côte d’Ivoire showed contrasting outputs relative to
observed number of sellers. Most of the bushmeat sites were not
optimally modelled due to their heterogeneity in growth, especially
Toumodi restaurants. Random Forest algorithms performed better in the
case of Yopougon and Abobo Mairie markets, where predicted values from
both models converged closer to observed values. Convergence between
constrained and unconstrained models may serve as an additional
confidence estimate of model performance, coupled with the intrinsic
estimates already available (RMSE and variance). Further investigations
on Random Forest algorithms as applied to bushmeat trade dynamics over
longer periods of time will have to be undertaken before the benefits of
such predictive approach can be considered (e.g., as in finance
research; Ghosh et al., 2022).
We conclude that neglecting the socio-geographical specificities of the
different types of bushmeat sites could lead to erroneous projections of
bushmeat trade dynamics. Eleven months after the end of governmental
measures in Côte d’Ivoire, most of the bushmeat sites had not fully
recovered in terms of number of sellers. Whether regular controls have
slowed down the resumption of the trade requires further investigations.
The social and economic implications behind the lack of the full
recovery of certain markets at the time of our study, including that of
the largest bushmeat market of Côte d’Ivoire, is unknown. Given the
possible precariousness of certain bushmeat sellers (see Falola et al.,
2015), it is likely that some could not economically support the
consequences of a national ban for several months. However, with the
data at hand, it remains hazardous to discuss the deleterious economic
shockwave foreseen by some authors in relation to wildlife trade bans
(e.g., McNamara et al., 2020), especially since future disease outbreaks
and reduction in resources through over-harvesting will likely influence
market dynamics under the current tolerated market scenario.
Understanding bushmeat trade dynamics in the context of mitigation
measures will require a multi-dimensional approach where the
characteristics of the different markets (e.g., type of markets,
socio-demography of vendors, ban record, species hunted and places
sourced) are clearly identified. Our study showed that wildlife trade
bans can have a long-lasting impact on bushmeat trade dynamics, and that
state power when guided by a clearly defined objective can efficiently
setup trade mitigation, at least in the short-term. Actual mitigation of
the bushmeat trade, whether conservation- or health-driven, will depend
on a comprehensive understanding of its specific dynamics and the
economic reliance of involved actors. To reach this objective, less
talk, and more on-the-ground data with comprehensive modelling will be
required.