Deciphering the enigma of undetected species, phylogenetic, and functional diversity based on Good-Turing theory.

Estimating the species, phylogenetic, and functional diversity of a community is challenging because rare species are often undetected, even with intensive sampling. The Good-Turing frequency formula, originally developed for cryptography, estimates in an ecological context the true frequencies of rare species in a single assemblage based on an incomplete sample of individuals. Until now, this formula has never been used to estimate undetected species, phylogenetic, and functional diversity. Here, we first generalize the Good-Turing formula to incomplete sampling of two assemblages. The original formula and its two-assemblage generalization provide a novel and unified approach to notation, terminology, and estimation of undetected biological diversity. For species richness, the Good-Turing framework offers an intuitive way to derive the non-parametric estimators of the undetected species richness in a single assemblage, and of the undetected species shared between two assemblages. For phylogenetic diversity, the unified approach leads to an estimator of the undetected Faith's phylogenetic diversity (PD, the total length of undetected branches of a phylogenetic tree connecting all species), as well as a new estimator of undetected PD shared between two phylogenetic trees. For functional diversity based on species traits, the unified approach yields a new estimator of undetected Walker et al.'s functional attribute diversity (FAD, the total species-pairwise functional distance) in a single assemblage, as well as a new estimator of undetected FAD shared between two assemblages. Although some of the resulting estimators have been previously published (but derived with traditional mathematical inequalities), all taxonomic, phylogenetic, and functional diversity estimators are now derived under the same framework. All the derived estimators are theoretically lower bounds of the corresponding undetected diversities; our approach reveals the sufficient conditions under which the estimators are nearly unbiased, thus offering new insights. Simulation results are reported to numerically verify the performance of the derived estimators. We illustrate all estimators and assess their sampling uncertainty with an empirical dataset for Brazilian rain forest trees. These estimators should be widely applicable to many current problems in ecology, such as the effects of climate change on spatial and temporal beta diversity and the contribution of trait diversity to ecosystem multi-functionality.

Would protecting tropical forest fragments provide carbon and biodiversity cobenefits under REDD+?

Tropical forests store vast amounts of carbon and are the most biodiverse terrestrial habitats, yet they are being converted and degraded at alarming rates. Given global shortfalls in the budgets required to prevent carbon and biodiversity loss, we need to seek solutions that simultaneously address both issues. Of particular interest are carbon-based payments under the Reducing Emissions from Deforestation and Forest Degradation (REDD+) mechanism to also conserve biodiversity at no additional cost. One potential is for REDD+ to protect forest fragments, especially within biomes where contiguous forest cover has diminished dramatically, but we require empirical tests of the strength of any carbon and biodiversity cobenefits in such fragmented systems. Using the globally threatened Atlantic Forest landscape, we measured above-ground carbon stocks within forest fragments spanning 13 to 23 442 ha in area and with different degrees of isolation. We related these stocks to tree community structure and to the richness and abundance of endemic and IUCN Red-listed species. We found that increasing fragment size has a positive relationship with above-ground carbon stock and with abundance of IUCN Red-listed species and tree community structure. We also found negative relationships between distance from large forest block and tree community structure, endemic species richness and abundance, and IUCN Red-listed species abundance. These resulted in positive congruence between carbon stocks and Red-listed species, and the abundance and richness of endemic species, demonstrating vital cobenefits. As such, protecting forest fragments in hotspots of biodiversity, particularly larger fragments and those closest to sources, offers important carbon and biodiversity cobenefits. More generally, our results suggest that macroscale models of cobenefits under REDD+ have likely overlooked key benefits at small scales, indicating the necessity to apply models that include finer-grained assessments in fragmented landscapes rather than using averaged coarse-grained cells.

Defaunation affects carbon storage in tropical forests.

Carbon storage is widely acknowledged as one of the most valuable forest ecosystem services. Deforestation, logging, fragmentation, fire, and climate change have significant effects on tropical carbon stocks; however, an elusive and yet undetected decrease in carbon storage may be due to defaunation of large seed dispersers. Many large tropical trees with sizeable contributions to carbon stock rely on large vertebrates for seed dispersal and regeneration, however many of these frugivores are threatened by hunting, illegal trade, and habitat loss. We used a large data set on tree species composition and abundance, seed, fruit, and carbon-related traits, and plant-animal interactions to estimate the loss of carbon storage capacity of tropical forests in defaunated scenarios. By simulating the local extinction of trees that depend on large frugivores in 31 Atlantic Forest communities, we found that defaunation has the potential to significantly erode carbon storage even when only a small proportion of large-seeded trees are extirpated. Although intergovernmental policies to reduce carbon emissions and reforestation programs have been mostly focused on deforestation, our results demonstrate that defaunation, and the loss of key ecological interactions, also poses a serious risk for the maintenance of tropical forest carbon storage.