Correction to: Towards estimating the economic cost of invasive alien species to African crop and livestock production (CABI Agriculture and Bioscience, (2021), 2, 1, (18), 10.1186/s43170-021-00038-7)

Abstract

Eschen et al. (2021) estimated the annual cost of invasive alien species (IAS) to African agriculture, separated into the cost due to yield loss, the cost of weeding, the loss of livestock-based income and the cost of research. The paper revealed the vast cost of IAS to the continent and estimated the total cost to be USD 3.66 Tn, with by far the largest part of the estimated cost (USD 3.63 Tn) due to weeding. The study concluded that there is a need for pre-emptive measures to reduce future costs, as well as measures that contribute to the control of widely established IAS to reduce losses and improve livelihoods. After publication, it was brought to our attention that the estimated cost of weeding was much higher than can reasonably be expected although the input data and general approach to calculating the estimate were not disputed. We therefore revisited our calculations and found a scaling error that occurred during the application of wages to the harvested area for each of the five crop types. As described in the original article, we calculated the cost of weeding IAS in five crop types based on the harvested area in each African country, calculated from data in the SPAM database, the average abundance of alien species as a fraction of the weed community in African agricultural fields as deducted from the published literature. The average time spent weeding a hectare of each of the five crop types was taken from the published literature, and wages paid in each country for agricultural labour or similar jobs as reported on. We erroneously applied costs per square kilometre instead of the cost of weeding per hectare, resulting in substantially overestimated weeding costs. The calculations of the estimates of yield loss, the loss of livestock-based income and research costs were not affected by this error. We corrected this error in our calculations and have updated the results, specifically Table 3, which presents to total estimate, and Table 4, which presents the estimates for each country. These corrected Tables are presented here. We have updated the numbers stated in the Abstract and in the Results section of the manuscript text to reflect the corrected results. We also modified the discussion where these estimates are put into context. While the total estimate of IAS cost to African agriculture are now significantly lower, the conclusions and recommendations have not changed. (Table presented.) (Table presented.) The absolute and relative contribution of labour, yield loss, lost livestock derived income and research to the annual cost of IAS to African agriculture in billions USD Damage component Annual cost contribution in USD Percentage Yield loss 29.06 44.31 Weeding 36.34 55.42 Lost livestock derived income 0.17 0.26 Research 0.00 0.00 Total 65.58 Summary of estimated costs by country (in millions USD). For the yield losses by individual species, the values are the middle estimates, based on the literature and survey responses. A dash indicate that no estimate was made, whereas a zero indicates a small estimated value Country Annual-weeding-costs (million USD) Reduced-grazing-potential Damage caused (in millions USD) by Total (million USD) BBTV Algeria 608 2 – – – – – – – 611 Angola 1066 1 368 – – – 2 96 185 1717 Benin 452 0 376 – – – 36 0 18 883 Botswana 26 0 1 – 1 – 2 – 0 31 Burkina-Faso 874 1 186 – – – 12 – 2 1075 Burundi 6 0 11 – – 192 5 92 204 510 Côte-d'Ivoire 1212 1 211 – – 495 – – 64 1984 Cameroon 725 0 2237 – 363 79 24 17 1 3446 Central-African-Republic 125 1 137 – – 21 – 1 18 304 Chad 1052 2 51 – – – – – 21 1126 Congo,-Republic-of-the 272 0 12 – – 1163 1 24 100 1573 Congo,-Democratic-Republic-of-the 3166 0 418 – – 0 – 16 451 4053 Djibouti – 0 – – – – – – – 0 Egypt 520 9 – – – – 967 – – 1496 Equatorial-Guinea – – – – – – 0 2 14 16 Eritrea 32 3 16 – 10 – – – 16 78 Ethiopia 442 22 209 – 427 – 17 – 80 1197 Gabon 148 0 9 – – 0 – 0 1 159 Gambia,-The 21 1 4 – – 0 – – 13 40 Ghana 703 0 277 14 – 0 – – 94 1088 Guinea 427 0 37 – – 0 – – 35 500 Guinea-Bissau 0 0 4 1 – 3 – – 24 33 Kenya 917 33 719 41 304 155 222 – 184 2576 Lesotho 69 – – – 8 – 8 – – 85 Liberia 12 – – – – 0 – – 21 34 Libya 178 0 – – – – – – – 178 Malawi 457 1 31 59 127 1231 119 204 – 2288 Mali 1099 3 252 – – 2 – – 421 1776 Mauritania 5 0 – – – – – – 13 18 Morocco 1442 5 – – – – 211 – – 1658 Mozambique 868 3 421 30 71 1587 58 36 107 3212 Namibia 365 1 9 – – – 5 – 13 392 Niger 2477 1 5 – – 5 – – 34 2522 Nigeria 10,194 2 500 – – 238 1854 79 2202 15,069 Rwanda 13 1 17 6 – 59 – 0 47 143 South-Sudan 174 15 26 – – – – – – 214 Senegal 589 0 25 3 – 7 284 – 42 950 Sierra-Leone 115 0 0 – – 0 – – 94 210 Somalia 16 5 16 – 9 – – – – 46 South-Africa 2275 33 1082 – 599 – – – – 3989 Sudan 542 7 5 – 7 – – – 256 816 Eswatini 8 1 – – 7 – – – 54 70 Tanzania 1268 4 644 64 144 613 175 – 526 3438 Togo 303 0 13 13 – 3 – – 1 334 Tunisia 228 1 – – – – 118 – – 348 Uganda 391 5 609 30 233 0 1 – 371 1639 Zambia 375 4 307 9 217 399 29 0 10 1350 Zimbabwe 89 1 144 11 65 0 – – 80 390 Total 36,342 173 9394 282 2592 6254 4149 568 5820 65,573 We have also corrected the value for the yield loss due to Phthorimaea absoluta based on the literature and a survey in Table 5. The value in the previous version of the manuscript was wrong due to a transcription error. The new value is corrected for abundance within each country, like the other values in the Table. This species was deleted from the abstract as the most costly species and minor changes to the Results and Discussion were made to align the text with the correct number. A reference made to an article ‘in press’ during publication has also been updated with the article’s final reference detail. (Table presented.) Estimated yield loss caused by individual IAS in Africa Host plant IAS Yield loss values (billions USD) estimated by Literature only Literature + survey Maize 6.9 (–)* 9.4 (7.7–12.1) 0.2 (0.1–0.3) 0.3 (0.2–0.5) 2.6 (2.1–3.1) 2.6 (2.1–3.1) Cassava 0.0 (0.0–0.0) 6.3 (5.5–7.3) Tomato 4.8 (3.6–6.7) 4.1 (3.2–5.6) Banana BBTV 0.2 (–) 0.6 (0.5–0.6) Mangoes (and citrus in survey) 3.5 (1.7–10.6) 5.8 (4.4–10.0) Total 18.2 29.1 *Numbers in brackets indicate high and low estimates We apologise for the errors and any confusion they may have caused.The original article has been updated.