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The eco-evolutionary history of Madagascar presents unique challenges to tropical forest restoration

Citation

Culbertson, Katherine A. et al. (2022), The eco-evolutionary history of Madagascar presents unique challenges to tropical forest restoration, Dryad, Dataset, https://doi.org/10.6078/D1MQ6C

Abstract

High biodiversity and endemism combined with persistently high deforestation rates mark Madagascar as one of the hottest of biodiversity hotspots. Contemporary rising interest in large-scale reforestation, both globally and throughout Madagascar itself, presents a promising impetus for forest restoration and biodiversity conservation across the island. However, Madagascar may face unique restoration challenges due to its equally unique eco-evolutionary trajectory, which must be understood to enable successful ecological restoration. We conducted a systematic review of potential barriers to restoration for terrestrial forest biomes (rainforests, dry forests, subhumid highland forests) in Madagascar. Our results indicate that aboveground biomass recovery of Malagasy forests appears slower than other tropical forests. We suggest four key synergistic factors that inhibit restoration in Madagascar: (a) Lack of resilience to shifting nutrient and fire regimes arising from widespread high-intensity shifting cultivation; (b) Predominance of nutrient-poor, highly weathered ferralitic soils; (c) Vulnerability of regenerating native trees to competition with invasive species due to their evolutionary isolation; and (d) Low seed dispersal into regenerating forests due to the unique dependence of Malagasy trees on dispersal by forest-dependent endangered or extinct primates. However, we note that rigorous experimental study of regenerating forests in Madagascar is currently lacking. There is great opportunity and need for such research to disentangle drivers and interactions inhibiting forest restoration. These studies would enable reforestation practitioners to effectively capitalize on current global momentum to implement the large-scale restoration necessary for the conservation of Madagascar's numerous endemic species.

Methods

This dataset includes (1) a list of all references recovered in our literature search for the accompanying paper, and (2) data extracted from a subset of these papers.

(1) We compiled peer-reviewed literature on forest restoration in Madagascar primarily through a systematic literature search of all ISI Web of Science (WOS) databases on English-language publications between 1 Jan 1990-1 March 2022 using the following search string:

TS = (Madagascar AND forest AND (refor* OR restor* OR regen*))

Additional relevant papers (both in English and French) were added from the citations of the aforementioned studies, through expert referral, and through an additional search of WOS core collections using search terms related to our hypotheses, but not directly incorporating regeneration.

The first datasheet in the excel file, "Included Studies", lists all studies included in our review, and a variety of relevant site and study data extracted from these papers. The second datasheet, "MasterList", includes all studies returned through our search and documents our screening process.

(2) For papers included in our review, we extracted available quantitative data on aboveground biomass (AGB) recovery (eight unique datasets from nine studies - in the sheet "BiomassData") and sapling growth/survival (nine studies - in the sheet "SaplingData"). All biomass recovery data originated from naturally regenerating forests. For two studies reporting biovolume rather than biomass, we converted these values to biomass by multiplying by the average value for wood density across Madagascar (0.662 g cm-3; Chave et al. 2009, Zanne et al. 2009), as wood density was not reported for either study. We attempted to obtain supplementary data from authors when it was not available online.

Usage Notes

In addition to this dataset, a README text file is included detailing a key and including other metadata.

Funding

Bridge Collaborative, Award: SCI_Bridge_UV_200130