Mapping tree diversity in the tropical forest region of Chocó-Colombia

Abstract

Understanding spatial patterns of diversity in tropical forests is indispensable for their sustainable use and conservation. Recent studies have reported relationships between forest structure and α-diversity. While tree α-diversity is difficult to map via remote sensing, large-scale forest structure models are becoming more common, which would facilitate mapping the relationship between tree α-diversity and forest structure, contributing to our understanding of biogeographic patterns in the tropics. We developed a methodology to map tree α-diversity in tropical forest regions at 50 m spatial resolution using α-diversity estimates from forest inventories as response variables and forest structural metrics and environmental variables as predictors. To include forest structural metrics in our modelling, we first developed a method to map seven of these metrics integrating discrete light detection and ranging (LiDAR), multispectral, and synthetic aperture radar imagery (SAR). We evaluated this methodology in the Chocó region of Colombia, a tropical forest with high tree diversity and complex forest structure. The relative errors (REs) of the random forest models used to map the seven forest structural variables ranged from low (6%) to moderate (35%). The α-diversity maps had moderate RE; the maps of Simpson and Shannon diversity indices had the lowest RE (9% and 13%), followed by richness (17%), while Shannon and Simpson effective number of species indices had the highest RE, 27% and 47%, respectively. The highest concentrations of tree α-diversity are located along the Pacific Coast from the centre to the northwest of the Chocó Region and in non-flooded forest along the boundary between the Chocó region and the Andes. Our results reveal strong relationships between canopy structure and tree α-diversity, providing support for ecological theories that link structure to diversity via niche partitioning and environmental conditions. With modification, our methods could be applied to assess tree α-diversity of any tropical forest where tree α-diversity field observations coincident with LiDAR data.

Giants of the Amazon: How does environmental variation drive the diversity patterns of large trees?

“…These regions also have the greatest potential for the growth of very tall trees (Gorgens et al, 2021). This strong relationship between well-drained upland areas and large tree diversity has also been observed in other forests in the tropics and has been associated with ecologically stable environmental conditions for tree establishment and growth (Duivenvoorden, 1995;Fagua et al, 2021;Slik et al, 2009;Ter Steege et al, 2003;Venter et al, 2017).…”

Floristic Composition and Life Forms of Plant Species in Nwamba Forest Reserve in Nigeria

“…The results also indicated that the Fabaceae family had the highest number of plant species (24) followed by Rubiaceae (14), Apocynaceae (10) The results in Table 1 also showed that the species with the highest percentage frequency of occurrence are Napoleona vogelii and Cola argentina with 84.4% of occurrence closely followed by Cola hispida, Icacina trichantha, Cnestis ferruginea and Newbouldia laevis with 81.3% of occurrence whereas the least frequent species were Ipomea involucrata, Ipomea batata, Dioscorea dumetorum, Dioscorea bulbifera, Dracaena fragrans, Bambusa vulgaris, Oxymitra incrassata, Nephrolepis biserrata and Platycerium coronarium with 3.1% of the frequency of occurrence. with a known range of 1700-3200 mm) similar to that in Nwamba forest reserve [17][18][19] . The results showed that the Fabaceae family had the highest number of species (most dominant families) in the Nwamba forest reserve and this observation is in line with several reports of Fabaceae dominating in forests with similar climatic predispositions [20][21][22] .…”

Assessing canopy structure in Andean (agro)forests using 3D UAV remote sensing

“…For this reason, a valuation of their potential as a carbon sink and their positive effect on habitat conservation can serve to include them into frameworks for payments for ecosystem services (Bhagwat et al, 2008) . Ecosystem structure is considered one of the Essential Biodiversity Variables (EBV) (Pereira et al, 2013) and is related to the complexity of vegetation and its canopy structure which are measured to study, monitor and manage biodiversity change (Fagua et al, 2021). Moreover, canopy structure is an indicator for the structural heterogeneity and habitat availability (Meyer et al, 2020;Deere et al, 2020;Cooper et al, 2020), both of which have been shown to correlate with species diversity (e.g.…”

“…Moreover, canopy structure is an indicator for the structural heterogeneity and habitat availability (Meyer et al, 2020;Deere et al, 2020;Cooper et al, 2020), both of which have been shown to correlate with species diversity (e.g. Fagua et al, 2021, Farwell et al, 2021. In other words, AFS can provide multiple bene ts to nature and people, while their canopy structure seems to be a key variable for providing these bene ts.…”