DOI: 10.5061/dryad.69p8cz9h4
title: Data from: The effects of land use on downstream water quality and biodiversity in a changing tropical mosaic landscape

description: Land use and other human activities often degrade downstream water
 quality, with consequences for ecosystem services and freshwater
 biodiversity. Understanding the relative effects of different land-use
 types across large spatial scales, however, remains challenging in
 heterogeneous landscapes. We investigated how landscape composition
 influences stream water quality and aquatic biodiversity in 46 catchments
 with perennial streams draining mosaic landscapes managed by smallholder
 farmers in southwest Ethiopia. Specifically, we assessed whether coffee
 agroforestry landscapes have intermediate effects on stream biodiversity
 compared to forests and agricultural lands. We measured multiple water
 quality parameters and sampled stream macroinvertebrates, while
 quantifying land-use proportions, settlement density, and an index
 representing the number and proximity of coffee washing stations within
 each catchment. Streams draining forest-dominated landscapes exhibited
 better water quality, characterized by higher dissolved oxygen and lower
 turbidity and nutrient concentrations, than those draining agroforestry-
 or agriculture-dominated landscapes. Elevated concentrations of
 Escherichia coli were detected in most streams, particularly in
 agroforestry landscapes. Macroinvertebrate community composition varied
 widely, with pollution-sensitive taxa dominating cleaner streams and
 tolerant taxa prevailing in more degraded systems. These patterns were
 more pronounced when considering the direct effects of settlement density
 and coffee washing stations, although some taxonomic groups showed
 inconsistent responses. Our results indicate that water chemistry alone
 does not fully capture land-use impacts on stream condition, underscoring
 the importance of incorporating biodiversity assessments. Given the
 reliance of local communities on these streams and the risks to freshwater
 biodiversity, our findings highlight the urgent need for mitigation
 measures, particularly in agriculture- and agroforestry-dominated
 landscapes, with a focus on reducing waste inputs from settlements and wet
 coffee washing stations.
description: # Data from: The effects of land use on downstream water quality and
 biodiversity in a changing tropical mosaic landscape Dataset DOI:
 [10.5061/dryad.69p8cz9h4](https://doi.org/10.5061/dryad.69p8cz9h4) ##
 Description of the data and file structure Here is the explanation for the
 archived data, Hirko et al., landscape ecology 2025, in the zipped file
 **dryad_files_OH.zip**. R-code file: **analysis_OH.R** archived data: This
 script combines biodiversity, water chemistry, and land-use data to
 analyze how landscape composition and human activities influence stream
 water quality and macroinvertebrate communities, using multivariate
 analyses, regressions, and structural equation models. It also produces
 figures and tables supporting relationships among land use, environmental
 variables, and aquatic biodiversity. **biodiviersity_OH.csv**: Species by
 site matrix of macroinvertebrate taxa and their abundance   **Columns** *
 tributarycode:  Stream unique ID - The other columns (columns 2 to 19)
 represent names of stream macroinvertebrate taxa (family) of mayflies,
 stoneflies and true flies **water_chemistry_local_envt1_OH.csv**: Water
 chemistry and local environmental variables; empty cells represent values
 were not determined. **Columns** * Tributarycode: Stream unique ID - DO:
 Dissolved oxygen (mg/l) * pH: pH values - Conductivity: Conductivity
 (μS/cm) * Turbidity: Turbidity (NTU) - Temperature: Water temperature (℃)
 * Altitude: Elevation (m.a.s.l) at the sampling reach - TotP: Total
 phosphorus (μg/l) * TotN: Total nitrogen (μg/l) - TOC: Total organic
 carbon (mg/l) * Canopycover: Canopy cover (%)  - depthm: Water depth at
 sample reach (m) * widthm: Water width in stream channel at sample reach
 (m) - substrateindex: Substrate index (see methods in the paper) * E coli:
 *Escherichia coli* (CFU/ml) - coliforms: Coliforms (CFU/ml)      *
 Watervolumeindex: Water volume index estimated from water depth and width
 (see methods in the paper) **land_use_OH.csv**: Land use and human
 activities data set * tributarycode: Stream unique ID   - Forest:
 Proportion of land use under natural forest (%)          * Agroforestry:
 Proportion of land use under agroforestry (%)   - Agriculture: Proportion
 of land use under agriculture (%)        * Urban: Proportion of land use
 under urban (%) - Wetland: Proportion of land use under wetland (%)     *
 TotalHHcount: Total number of households       - Settlementdensity:
 Density of households (number of households per ha)  * Tributaryareaha:
 Total catchment area in ha     - Forestbinary: Forest cover
 presence/absence (i.e forest cover present when the forest cover is &gt;
 30% and absence when it is &lt; 30%) * Coffeewashingindex: Coffee washing
 stations index    - Coffeewashingstation: Coffee washing station presence
 or absence **biodiviersity_metrix_OH.csv**: * tributarycode: Stream unique
 ID   - pooledabundance: Macroinvertebrate total abundance          *
 taxarichness: Taxa richness         - shannonindex: Shannon diversity
 index * leptophbnry: Leptophlebiidae presence/absence         -
 ceratopbnry: Ceratopogonidae presence/absence                 *
 muscidbnry: Muscidae presence/absence         - tabanbnry: Tabanidae *
 taxa_total_score: Taxa water quality index (see methods in the paper) ##
 Code/software See R-code in the archived files with the file name:
 **analysis_OH.R**