Land use influences stream bacterial communities in lowland tropical watersheds

Abstract

Land use is known to affect water quality yet the impact it has on aquatic microbial communities in tropical systems is poorly understood. We used 16S metabarcoding to assess the impact of land use on bacterial communities in the water column of four streams in central Panama. Each stream was influenced by a common Neotropical land use: mature forest, secondary forest, silvopasture and traditional cattle pasture. Bacterial community diversity and composition were significantly influenced by nearby land uses. Streams bordered by forests had higher phylogenetic diversity (Faith’s PD) and similar community structure (based on weighted UniFrac distance), whereas the stream surrounded by traditional cattle pasture had lower diversity and unique bacterial communities. The silvopasture stream showed strong seasonal shifts, with communities similar to forested catchments during the wet seasons and cattle pasture during dry seasons. We demonstrate that natural forest regrowth and targeted management, such as maintaining and restoring riparian corridors, benefit stream-water microbiomes in tropical landscapes and can provide a rapid and efficient approach to balancing agricultural activities and water quality protection.

Landscape Context for Forest Transition Success in Central Panama

“…The Panama Canal Authority is promoting silvo-pastoral (SP) system in the PCW, where riparian forest completely surrounds the streams and is protected with fencing to restrict cattle access to a single point. Nevertheless, even though biodiversity would bene t from it, this system could lead to degraded water quality in dry season, caused by increased congregation of cattle to drink and avoid heat through shade (Chavarria et al 2021). This could be mitigated by the provision of additional tree shade, further away from the streams.…”

Bacterial communities in a neotropical full-scale drinking water system including intermittent piped water supply, from sources to taps

“…Amplification of the V4 variable region of the 16S rRNA gene and subsequent sequencing was performed following the protocols described in Chavarria et al (2021). 51…”

“…Quantitative Insights Into Microbial Ecology 2 (QIIME2) platform v2020.11 and the statistical software R were used for data analysis of 16S rRNA gene data analysis of paired-end sequence reads 53 following Chavarria et al (2021). 51 Alpha- and beta-diversity were calculated using the diversity core-metrics function in QIIME2 from the resulting ASV table, standardized to a sequencing depth of 2200 sequences per sample. Differences in alpha diversity (Shannon diversity and Inverse Simpson) by categorical metadata variables were tested by Kruskal–Wallis, with pairwise differences between types of sample also tested in QIIME2 using pairwise Wilcox tests with Benjamini–Hochberg corrections.…”

Mapping a conservation research network to the Sustainable Development Goals

“…The results of these projects go beyond the protection and restoration of Panamanian forests and have numerous co‐benefits, mapping to 11 SDGs and 36 targets (Figure 1, Table S1). These include increased climate resilience (Hall et al, 2022), with a focus on reduced flooding (Ogden et al, 2013) (SDGs 1.5, 11.5, 13.1, 13.2), improved water quality (Chavarria et al, 2021) and security (dos Reis Oliveira et al, 2019) (SDGs 6.3, 6.5), and natural heritage protection (SDG 11.4). This research is designed to improve the efficient use of natural resources (SDG 12.2), reinforce land tenure claims and provide economic benefits to landowners through carbon credits and sustainable forest management (Adamowicz et al, 2019; Hall, Kirn, et al, 2015; Sinacore et al, 2022) (SDG 1.4).…”