Successful protected area networks must represent biodiversity across taxonomic groups. However, too often plant species are overlooked in conservation planning, and the resulting protected areas may, as a result, fail to encompass the most important sites for plant diversity. The Mozambique Tropical Important Plant Areas project sought to promote the conservation of Mozambique's flora through the identification of Important Plant Areas (IPAs). Here, we use the Weighted Endemism including Global Endangerment (WEGE) index to identify the richest areas for rare and endemic plants in Mozambique and subsequently evaluate how well represented these hotspots are within the current protected area and IPA networks. We also examine the congruence between IPA and protected areas to identify opportunities for strengthening the conservation of plants in Mozambique. We found that high WEGE scores, representing areas rich in endemic/near‐endemic and threatened species, predict the presence of IPAs in Mozambique, but do not predict the presence of protected areas. We also find that there is limited overlap between IPAs and protected areas in Mozambique. We demonstrate how IPAs could be an important tool for ensuring priority sites for plant diversity are included within protected area network expansions, particularly following the adoption of the “30 by 30” target agreed within the post‐2020 Convention on Biological Diversity framework, with great potential for this method to be replicated elsewhere in the global tropics.

We produced a raster layer of the WEGE scores using the spat_ras function in the WEGE R package (Farooq, Azevodo, et al., 2020). Cell size within this raster is 25 × 25 km and the extent encompassed the entirety of Mozambique. WEGE is calculated using the following formula:

WEGE value for each cell represents the sum of the square root of the partial weighted endemism value (WE_i) multiplied by the probability of extinction (ER_i) for each species recorded within a given cell. Further details of this calculation are outlined by Farooq, Azevedo, et al. (2020). Weighted endemism here is inversely proportional to the number of grid cells in which a species occurs within. For extinction risk, the IUCN50 transformation from Davis et al. (2018) was used with the following probabilities: LC = 0.0009, NT = 0.0071, VU = 0.0513, EN = 0.4276, and CR = 0.9688. Davis et al. (2018) used projected extinction probabilities based on the Red List Criterion E (IUCN, 2012) which they subsequently transformed, assuming exponential decay of a species, to reflect extinction risk over 50 years. Extinction risk values for Near Threatened and Least Concern species were calculated by extrapolating from the decay constants of threatened species. For DD species, the probability of VU was used (0.0513) following Bland et al. (2015).

The species occurrence data used to calculate WEGE index were derived from a georeferenced dataset of 4591 records from 446 plant taxa, of which 206 were endemic and 240 were near-endemic (including infraspecies; taxa following Darbyshire et al. (2019, 2023)) curated as part of the Mozambique TIPAs project. Inputting plant taxa into the WEGE calculation where there is not complete and accurate occurrence data for these taxa across their ranges could result in inaccurate weighted endemism scores that do not truly reflect the distributions of these taxa. Therefore, the species within this dataset were limited to endemic and near-endemic plant taxa, for which we had reliable occurrence data in the dataset. Species also had to be assessed for the Red List, including assessments that are yet to be published but have been entered into the IUCN Species Information Service. The dataset also contained records from the years 1843 to 2020. Due to a lack of recent collecting effort in parts of Mozambique, we included all records so as not to underestimate the biodiversity value of these parts of the country. Where there is no occurrence data within a cell, the WEGE value cannot be calculated.

For near-endemics, occurrence points from outside of Mozambique were included to calculate WEGE scores. However, the WEGE raster was subsequently clipped to include only cells that fall fully or partially within the borders of Mozambique.