Results
Comparison with no pest control
Overall, relative to farms without any pest control method, biocontrol
interventions had a strong negative effect on pest abundance and crop
damage, which were reduced by 55% (95% Confidence intervals (C.I.) =
-64.62 to -44.21, p< 0.0001) and 60% (C.I. = -71.44 to
-45.38, p< 0.0001), respectively (Fig. 1). Crops subject to
biocontrol exhibited a 62% increase in yield (C.I. = 38.58 to 91.57,
p< 0.0001). However, we found no significant overall effect of
biocontrol on natural enemy abundance (-19%, C.I. = 38.58 to 91.57)
(Fig. 1). There was substantial heterogeneity for all outcome measures,
suggesting unexplained variation (Pest abundance,I2 = 54,98%; Crop damage,
I2 = 51.35; Yield, I2= 69,20%, Natural enemy abundance, I2 = 92.35)
(Fig.1). Hence, we used meta-regression to elucidate the effect of
potential moderators.
Factors affecting biocontrol
effectives
Biocontrol intervention
technique
Overall, the most tested biocontrol approaches were botanical pesticides
(n = 244), followed by intercropping (n = 163) and push-pull (n = 46),
followed by both field margins (n = 38) and augmentation/introduction (n
= 38). We found that crop yield was significantly affected by the nature
of the biocontrol intervention (p=0.0001), with botanical pesticides and
push-pull increasing yield by 92% (C.I. = 50.48 to 147) and 80% (C.I.
= 52.13 to 114), respectively (Fig. 2c). In contrast, the specific
biocontrol technique adopted had no significant effect on pest abundance
(p=0.21), crop damage (p=0.30), or contrasting effects on natural enemy
abundance (p=0.35).
Crop type
Across all outcome measures, the impact of biocontrol was measured
predominantly in cereal crops (n = 457), followed by pulses (n = 155),
vegetables (n = 207), fruits (n = 28) and fibres (n = 43). Biocontrol
had an overall significant negative effect on pest abundance across all
crop types, with cereal pests showing a 61% reduction (C.I. = -77.84to
-34.66), followed by vegetable pests with a 54% reduction (C.I. =
-63.47 to -35.31) (Fig.3a). Pest abundance in pulses and fruits showed a
52% and 39% decrease in pests respectively (pulses: C.I. = -71.80 to
-20.29; fruits: C.I. = -62.79 to -2.59) (Fig.3a).
We found that biocontrol had a strong negative effect on crop damage in
all crop types tested (cereal: 60%, C.I. = -71.37 to -45.01;
vegetables: 46%, C.I. = -62.05 to -24.55; pulses: 44%, C.I. = -60.72
to -20.29; fruits: 38%, C.I. = -58.69 to -7.27) (Fig3b). Yield was
positively affected by biocontrol, but this varied according to crop
type; yields in vegetables increased by 57% (C.I. = 16.08 to 135) and
pulses by 61% (C.I. = 5.91 to 145), while cereals and fibres showed an
increase of 36% and 29% respectively (cereal: C.I. = 18.13 to 58.75;
fibres: C.I. = 25.55 to 33.26) (Fig.3c). The specific crop type in which
biocontrol interventions were tested did not influence the abundance of
natural enemies (NEA, p = 0.06, Fig.3d).
Target pest taxon
Biocontrol interventions had a significant negative effect on the
abundance of all pest taxa (p<0.0001), with lepidopteran pests
showing the greatest decline (-63%, C.I. =-73.47 to -49.30) (Fig.4a).
The crop damage of all taxa was strongly negatively affected by
biocontrol interventions (p=0.012), with damage caused by Blattodea
showing a 79% reduction (C.I. = -95.45 to -7.49) with biocontrol
implementation (Fig.4b). We found that exposure to biocontrol
interventions had a significant positive effect on yield where
Coleoptera, Lepidoptera and Blattodea were the targeted pests (Fig.4c,
Coleoptera: 157%, C.I.= 11.28 to 316; Lepidoptera: 65%, C.I. = 32.49
to 106.51; Blattodea 51%, C.I. = 17.62 to 94.37). There was no
detectable effect of pest taxon on NEA response to biocontrol (p = 0.60;
Fig.4d).
Comparison of research and farmers’
fields
Across all outcome measures, effect sizes did not differ significantly
between farming types. In terms of cropping systems, the size of the
negative effect of biocontrol on pest abundance was marginally higher in
smallholder farms (66%, C.I.: -78.14 to -47.21) than in research farms
(48%, C.I.= -59.62 to -33.64) (Fig.5a). Crop damage showed a similar
pattern, where reduction in small holder farms (-69%, C.I.: -81.83 to
-47.87) marginally exceeded that of research farms (45%, C.I.= -55.53
to -34.04) (Fig. 5b). With regards to yield, the proportional increase
was almost equal in the two cropping types (small farm: 59%, research
farm 67%). in neither case was NEA affected by biocontrol
interventions.
Comparison with synthetic
pesticides
The effectiveness of biocontrol interventions compared to synthetic
pesticides was measured mostly for botanical pesticides (n = 339),
followed by intercropping (n = 26) and augmentation/introduction (n =
23). We found no studies comparing the effect of field margins or
push-pull with pesticides on their ability to control crop pests.
Although biocontrol interventions showed marginally greater pest
abundance and damage, and reduced yield compared to synthetic
pesticides, we found no significant difference between the two
treatments (Fig.6, pest abundance: 23%, C.I. = -10.30 to 69.04; crop
damage: 87%, -2.06 to 246; yield: -7%, C.I. -24.04 to 11.48). NEA:
43%, C.I. = 5.26 to 116.62). Conversely, the abundance of natural
enemies was significantly greater following biocontrol implementation
compared to the application of synthetic pesticides (43%, C.I. = 5.26
to 116.62) (Fig.6).
Landscape composition
Our search yielded seven studies that explored the effect of landscape
composition on biocontrol delivered to crops in SSA. Four studies showed
a positive effect of proximity to natural habitat, or proportion of
natural habitat within a given buffer, on natural enemy activity (i.e.,
parasitism and predation) (Henri et al. 2015; Milligan et
al. 2016; Kebede et al. 2018; Soti et al. 2019). Only
three studies explored the interactive effects of landscape complexity
and farm management on pest control effectiveness (Tsafack et al.2013; Midega et al. 2014; Kebede et al. 2019). All studies
found an interactive effect of management and landscape composition,
though the low sample size did not allow for quantitative analysis here.