Multi-taxa environmental DNA inventories reveal distinct taxonomic and functional diversity in urban tropical forest fragments

Coupling remote sensing and eDNA to monitor environmental impact: A pilot to quantify the environmental benefits of sustainable agriculture in the Brazilian Amazon

Monitoring is essential to ensure that environmental goals are being achieved, including those of sustainable agriculture. Growing interest in environmental monitoring provides an opportunity to improve monitoring practices. Approaches that directly monitor land cover change and biodiversity annually by coupling the wall-to-wall coverage from remote sensing and the site-specific community composition from environmental DNA (eDNA) can provide timely, relevant results for parties interested in the success of sustainable agricultural practices. To ensure that the measured impacts are due to the environmental projects and not exogenous factors, sites where projects have been implemented should be benchmarked against counterfactuals (no project) and control (natural habitat) sites. Results can then be used to calculate diverse sets of indicators customized to monitor different projects. Here, we report on our experience developing and applying one such approach to assess the impact of shaded cocoa projects implemented by the Instituto de Manejo e Certificação Florestal e Agrícola (IMAFLORA) near São Félix do Xingu, in Pará, Brazil. We used the Continuous Degradation Detection (CODED) and LandTrendr algorithms to create a remote sensing-based assessment of forest disturbance and regeneration, estimate carbon sequestration, and changes in essential habitats. We coupled these remote sensing methods with eDNA analyses using arthropod-targeted primers by collecting soil samples from intervention and counterfactual pasture field sites and a control secondary forest. We used a custom set of indicators from the pilot application of a coupled monitoring framework called TerraBio. Our results suggest that, due to IMAFLORA's shaded cocoa projects, over 400 acres were restored in the intervention area and the community composition of arthropods in shaded cocoa is closer to second-growth forests than that of pastures. In reviewing the coupled approach, we found multiple aspects worked well, and we conclude by presenting multiple lessons learned.

Metabarcoding data reveal vertical multitaxa variation in topsoil communities during the colonization of deglaciated forelands

Ice-free areas are expanding worldwide due to dramatic glacier shrinkage and are undergoing rapid colonization by multiple lifeforms, thus representing key environments to study ecosystem development. It has been proposed that the colonization dynamics of deglaciated terrains is different between surface and deep soils but that the heterogeneity between communities inhabiting surface and deep soils decreases through time. Nevertheless, tests of this hypothesis remain scarce, and it is unclear whether patterns are consistent among different taxonomic groups. Here, we used environmental DNA metabarcoding to test whether community diversity and composition of six groups (Eukaryota, Bacteria, Mycota, Collembola, Insecta, and Oligochaeta) differ between the surface (0-5 cm) and deeper (7.5-20 cm) soil at different stages of development and across five Alpine glaciers. Taxonomic diversity increased with time since glacier retreat and with soil evolution. The pattern was consistent across groups and soil depths. For Eukaryota and Mycota, alpha-diversity was highest at the surface. Time since glacier retreat explained more variation of community composition than depth. Beta-diversity between surface and deep layers decreased with time since glacier retreat, supporting the hypothesis that the first 20 cm of soil tends to homogenize through time. Several molecular operational taxonomic units of bacteria and fungi were significant indicators of specific depths and/or soil development stages, confirming the strong functional variation of microbial communities through time and depth. The complexity of community patterns highlights the importance of integrating information from multiple taxonomic groups to unravel community variation in response to ongoing global changes.

The Influence of Cone Age and Urbanisation on the Diversity and Community Composition of Culturable Seed Fungal Endophytes within Native Australian Banksia ericifolia L.f. subsp. ericifolia

Seed fungal endophytes play a crucial role in assisting the overall health and success of their host plant; however, little is known about the factors that influence the diversity and composition of these endophytes, particularly with respect to how they change over time and within urban environments. Using culturing techniques, morphological analyses, and Sanger sequencing, we identified the culturable seed fungal endophytes of Banksia ericifolia at two urban and two natural sites in Sydney, New South Wales, Australia. A total of 27 Operational Taxonomic Units were obtained from 1200 seeds. Older cones were found to contain, on average, more colonised endophytes than younger cones. Species richness was also significantly influenced by cone age, with older cones being more speciose. Between urban and natural sites, the overall community composition did not change, although species richness and diversity were greatest at urban sites. Understanding how these endophytes vary in time and space may help provide an insight into the transmission pathways used and the potential role they play within the development and survival of the seed. This knowledge may also be crucial for restoration purposes, especially regarding the need to consider endophyte viability in ex situ seed collection and storage in seed-banking practices.

Soil microbial communities shift along an urban gradient in Berlin, Germany

The microbial communities inhabiting urban soils determine the functioning of these soils, in regards to their ability to cycle nutrients and support plant communities. In an increasingly urbanized world these properties are of the utmost importance, and the microbial communities responsible are worthy of exploration. We used 53 grassland sites spread across Berlin to describe and explain the impacts of urbanity and other environmental parameters upon the diversity and community composition of four microbial groups. These groups were (i) the Fungi, with a separate dataset for (ii) the Glomeromycota, (iii) the Bacteria, and (iv) the protist phylum Cercozoa. We found that urbanity had distinct impacts on fungal richness, which tended to increase. Geographic distance between sites and soil chemistry, in addition to urbanity, drove microbial community composition, with site connectivity being important for Glomeromycotan communities, potentially due to plant host communities. Our findings suggest that many microbial species are well adapted to urban soils, as supported by an increase in diversity being a far more common result of urbanity than the reverse. However, we also found distinctly separate distributions of operational taxonomic unit (OTU)s from the same species, shedding doubt of the reliability of indicator species, and the use of taxonomy to draw conclusion on functionality. Our observational study employed an extensive set of sites across an urbanity gradient, in the region of the German capital, to produce a rich microbial dataset; as such it can serve as a blueprint for other such investigations.

Constructing ecological indices for urban environments using species distribution models

In an increasingly urbanized world, there is a need to study urban areas as their own class of ecosystems as well as assess the impacts of anthropogenic impacts on biodiversity. However, collecting a sufficient number of species observations to estimate patterns of biodiversity in a city can be costly. Here we investigated the use of community science-based data on species occurrences, combined with species distribution models (SDMs), built using MaxEnt and remotely-sensed measures of the environment, to predict the distribution of a number of species across the urban environment of Los Angeles. By selecting species with the most accurate SDMs, and then summarizing these by class, we were able to produce two species richness models (SRMs) to predict biodiversity patterns for species in the class Aves and Magnoliopsida and how they respond to a variety of natural and anthropogenic environmental gradients.

We found that species considered native to Los Angeles tend to have significantly more accurate SDMs than their non-native counterparts. For all species considered in this study we found environmental variables describing anthropogenic activities, such as housing density and alterations to land cover, tend to be more influential than natural factors, such as terrain and proximity to freshwater, in shaping SDMs. Using a random forest model we found our SRMs could account for approximately 54% and 62% of the predicted variation in species richness for species in the classes Aves and Magnoliopsida respectively. Using community science-based species occurrences, SRMs can be used to model patterns of urban biodiversity and assess the roles of environmental factors in shaping them.