Effect of Water Chemistry, Land Use Patterns, and Geographic Distances on the Spatial Distribution of Bacterioplankton Communities in an Anthropogenically Disturbed Riverine Ecosystem

The spatial distribution of bacterioplankton communities in rivers is driven by multiple environmental factors, including local and regional factors. Local environmental condition is associated with effect of river water chemistry (through species sorting); ecological process in region is associated with effects of land use and geography. Here, we investigated variation in bacterioplankton communities (free-living, between 0.22 and 5 μm) in an anthropogenically disturbed river using high-throughput DNA sequencing of community 16S rRNA genes in order to investigate the importance of water chemistry, land use patterns, and geographic distance. Among environmental factors, sulfate (SO42–), manganese (Mn), and iron (Fe) concentrations were the water chemistry parameters that best explained bacterioplankton community variation. In addition, forest and freshwater areas were the land use patterns that best explained bacterioplankton community variation. Furthermore, cumulative dendritic distance was the geographic distance parameter that best explained bacterial community variation. Variation partitioning analysis revealed that water chemistry, land use patterns, and geographic distances strongly shaped bacterioplankton communities. In particular, the direct influence of land use was prominent, which alone contributed to the highest proportion of variation (26.2% in wet season communities and 36.5% in dry season communities). These results suggest that the mechanisms of species sorting and mass effects together control bacterioplankton communities, although mass effects exhibited higher contributions to community variation than species sorting. Given the importance of allochthonous bacteria input from various land use activities (i.e., mass effects), these results provide new insights into the environmental factors and determinant mechanisms that shape riverine ecosystem communities.

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Nutrients and sestonic chlorophyll dynamics in Asian lotic ecosystems and ecological stream health in relation to land-use patterns and water chemistry

Ecological Engineering ◽

10.1016/j.ecoleng.2015.03.006 ◽

2015 ◽

Vol 79 ◽

pp. 15-31 ◽

Cited By ~ 19

Author(s):

Ji-Woong Choi ◽

Jeong-Ho Han ◽

Chan-Seo Park ◽

Dae-Geun Ko ◽

Han-Il Kang ◽

...

Keyword(s):

Land Use ◽

Water Chemistry ◽

Stream Health ◽

Land Use Patterns ◽

Lotic Ecosystems ◽

Use Patterns

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Urban stream syndrome in a small, lightly developed watershed: a statistical analysis of water chemistry parameters, land use patterns, and natural sources

Environmental Monitoring and Assessment ◽

10.1007/s10661-014-3625-9 ◽

2014 ◽

Vol 186 (6) ◽

pp. 3391-3414 ◽

Cited By ~ 27

Author(s):

Judith A. Halstead ◽

Sabrina Kliman ◽

Catherine White Berheide ◽

Alexander Chaucer ◽

Alicea Cock-Esteb

Keyword(s):

Land Use ◽

Statistical Analysis ◽

Water Chemistry ◽

Urban Stream ◽

Land Use Patterns ◽

Urban Stream Syndrome ◽

Natural Sources ◽

Use Patterns

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Changing Traditional Land use Patterns in the Great Himalayas: A Case Study of Lahaul Valley

Journal of Environmental Systems ◽

10.2190/6451-t2jn-0n11-r0j1 ◽

1996 ◽

Vol 25 (2) ◽

pp. 195-211 ◽

Cited By ~ 9

Author(s):

G. S. Singh ◽

S. C. Ram ◽

J. C. Kuniyal

Keyword(s):

Land Use ◽

Land Use Patterns ◽

Use Patterns ◽

Traditional Land Use

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Conducting “Siteless Survey”: Results from Coastal New England

North American Archaeologist ◽

10.2190/rxce-py1q-pr1e-93m5 ◽

1993 ◽

Vol 14 (1) ◽

pp. 25-42 ◽

Cited By ~ 1

Author(s):

Jordan E. Kerber

Keyword(s):

Land Use ◽

New England ◽

Rhode Island ◽

Careful Consideration ◽

Archaeological Survey ◽

Land Use Patterns ◽

Use Patterns ◽

Statistical Validity ◽

Survey Results ◽

Survey Strategy

Selecting an effective archaeological survey takes careful consideration given the interaction of several variables, such as the survey's goals, nature of the data base, and budget constraints. This article provides justification for a “siteless survey” using evidence from a project on Potowomut Neck in Rhode Island whose objective was not to locate sites but to examine the distribution and density of prehistoric remains to test an hypothesis related to land use patterns. The survey strategy, random walk, was chosen because it possessed the advantages of probabilistic testing, as well as the ease of locating sample units. The results were within the limits of statistical validity and were found unable to reject the hypothesis. “Siteless survey” may be successfully applied in similar contexts where the distribution and density of materials, as opposed to ambiguously defined sites, are sought as evidence of land use patterns, in particular, and human adaptation, in general.

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The effects of different land use patterns on the microclimate and ecosystem services in the agro-pastoral ecotone of Northern China

Ecological Indicators ◽

10.1016/j.ecolind.2019.105522 ◽

2019 ◽

Vol 106 ◽

pp. 105522 ◽

Cited By ~ 3

Author(s):

Yuejuan Yang ◽

Kun Wang

Keyword(s):

Land Use ◽

Ecosystem Services ◽

Northern China ◽

Land Use Patterns ◽

Use Patterns

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Modeling Community-Scale Natural Resource Use in a Transboundary Southern African Landscape: Integrating Remote Sensing and Participatory Mapping

Remote Sensing ◽

10.3390/rs13040631 ◽

2021 ◽

Vol 13 (4) ◽

pp. 631

Author(s):

Kyle D. Woodward ◽

Narcisa G. Pricope ◽

Forrest R. Stevens ◽

Andrea E. Gaughan ◽

Nicholas E. Kolarik ◽

...

Keyword(s):

Remote Sensing ◽

Land Use ◽

Resource Use ◽

Training Data ◽

Systems Science ◽

Participatory Mapping ◽

Land Use Patterns ◽

Modeling Framework ◽

Use Patterns ◽

Human Habitation

Remote sensing analyses focused on non-timber forest product (NTFP) collection and grazing are current research priorities of land systems science. However, mapping these particular land use patterns in rural heterogeneous landscapes is challenging because their potential signatures on the landscape cannot be positively identified without fine-scale land use data for validation. Using field-mapped resource areas and household survey data from participatory mapping research, we combined various Landsat-derived indices with ancillary data associated with human habitation to model the intensity of grazing and NTFP collection activities at 100-m spatial resolution. The study area is situated centrally within a transboundary southern African landscape that encompasses community-based organization (CBO) areas across three countries. We conducted four iterations of pixel-based random forest models, modifying the variable set to determine which of the covariates are most informative, using the best fit predictions to summarize and compare resource use intensity by resource type and across communities. Pixels within georeferenced, field-mapped resource areas were used as training data. All models had overall accuracies above 60% but those using proxies for human habitation were more robust, with overall accuracies above 90%. The contribution of Landsat data as utilized in our modeling framework was negligible, and further research must be conducted to extract greater value from Landsat or other optical remote sensing platforms to map these land use patterns at moderate resolution. We conclude that similar population proxy covariates should be included in future studies attempting to characterize communal resource use when traditional spectral signatures do not adequately capture resource use intensity alone. This study provides insights into modeling resource use activity when leveraging both remotely sensed data and proxies for human habitation in heterogeneous, spectrally mixed rural land areas.

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