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Rojas-Castillo OA, Kepfer-Rojas S, Vargas N, Jacobsen D. Forest buffer-strips mitigate the negative impact of oil palm plantations on stream communities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 873:162259. [PMID: 36801315 DOI: 10.1016/j.scitotenv.2023.162259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 02/07/2023] [Accepted: 02/11/2023] [Indexed: 06/18/2023]
Abstract
The global area cultivated with oil palm has doubled in the past two decades, causing deforestation, land-use change, freshwater pollution, and species loss in tropical ecosystems worldwide. Despite the palm-oil industry been linked to severe deterioration of freshwater ecosystems, most studies have focused on terrestrial environments, while freshwaters have been significantly less studied. We evaluated these impacts by contrasting freshwater macroinvertebrate communities and habitat conditions in 19 streams from primary forests (7), grazing lands (6), and oil palm plantations (6). In each stream, we measured environmental characteristics, e.g., habitat composition, canopy cover, substrate, water temperature, and water quality; and we identified and quantified the assemblage of macroinvertebrates. Streams in oil palm plantations lacking riparian forest strips showed warmer and more variable temperatures, higher turbidity, lower silica content, and poorer macroinvertebrate taxon richness than primary forests. Grazing lands showed higher conductivity and temperature, and lower dissolved oxygen and macroinvertebrate taxon richness than primary forests. In contrast, streams in oil palm plantations that conserved a riparian forest, showed a substrate composition, temperature, and canopy cover more similar to the ones in primary forests. These habitat improvements by riparian forests in the plantations increased macroinvertebrate taxon richness and maintained a community resembling more the one in primary forests. Therefore, the conversion of grazing lands (instead of primary forests) to oil palm plantations can increase freshwater taxon richness only if riparian native forests are safeguarded.
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Affiliation(s)
- O A Rojas-Castillo
- Freshwater Biology Section, Department of Biology, University of Copenhagen, Universitetsparken 4, third floor, 2100 Ø, CPH, Denmark; Escuela de Biología, Universidad de San Carlos, Ciudad Universitaria zona 12, Edificios T-10 y T-12, Guatemala.
| | - S Kepfer-Rojas
- Forest, Nature and Biomass Section, Department of Geosciences and Natural Resource Management, University of Copenhagen, Rolighedsvej, 23 1958 Frederiksberg C, Denmark
| | - N Vargas
- Centro de Estudios del Mar y Acuicultura, Universidad de San Carlos, Ciudad Universitaria zona 12, Edificio T-14, Guatemala; Escuela de Biología, Universidad de San Carlos, Ciudad Universitaria zona 12, Edificios T-10 y T-12, Guatemala
| | - D Jacobsen
- Freshwater Biology Section, Department of Biology, University of Copenhagen, Universitetsparken 4, third floor, 2100 Ø, CPH, Denmark
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Watershed Ecohydrological Processes in a Changing Environment: Opportunities and Challenges. WATER 2022. [DOI: 10.3390/w14091502] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Basin ecohydrological processes are essential for informing policymaking and social development in response to growing environmental problems. In this paper, we review watershed ecohydrology, focusing on the interaction between watershed ecological and hydrological processes. Climate change and human activities are the most important factors influencing water quantity and quality, and there is a need to integrate watershed socioeconomic activities into the paradigm of watershed ecohydrological process studies. Then, we propose a new framework for integrated watershed management. It includes (1) data collection: building an integrated observation network; (2) theoretical basis: attribution analysis; (3) integrated modeling: medium- and long-term prediction of ecohydrological processes by human–nature interactions; and (4) policy orientation. The paper was a potential solution to overcome challenges in the context of frequent climate extremes and rapid land-use change.
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Forio MAE, Burdon FJ, De Troyer N, Lock K, Witing F, Baert L, De Saeyer N, Rîșnoveanu G, Popescu C, Kupilas B, Friberg N, Boets P, Johnson RK, Volk M, McKie BG, Goethals PLM. A Bayesian Belief Network learning tool integrates multi-scale effects of riparian buffers on stream invertebrates. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 810:152146. [PMID: 34864036 DOI: 10.1016/j.scitotenv.2021.152146] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Revised: 11/26/2021] [Accepted: 11/29/2021] [Indexed: 06/13/2023]
Abstract
Riparian forest buffers have multiple benefits for biodiversity and ecosystem services in both freshwater and terrestrial habitats but are rarely implemented in water ecosystem management, partly reflecting the lack of information on the effectiveness of this measure. In this context, social learning is valuable to inform stakeholders of the efficacy of riparian vegetation in mitigating stream degradation. We aim to develop a Bayesian belief network (BBN) model for application as a learning tool to simulate and assess the reach- and segment-scale effects of riparian vegetation properties and land use on instream invertebrates. We surveyed reach-scale riparian conditions, extracted segment-scale riparian and subcatchment land use information from geographic information system data, and collected macroinvertebrate samples from four catchments in Europe (Belgium, Norway, Romania, and Sweden). We modelled the ecological condition based on the Average Score Per Taxon (ASPT) index, a macroinvertebrate-based index widely used in European bioassessment, as a function of different riparian variables using the BBN modelling approach. The results of the model simulations provided insights into the usefulness of riparian vegetation attributes in enhancing the ecological condition, with reach-scale riparian vegetation quality associated with the strongest improvements in ecological status. Specifically, reach-scale buffer vegetation of score 3 (i.e. moderate quality) generally results in the highest probability of a good ASPT score (99-100%). In contrast, a site with a narrow width of riparian trees and a small area of trees with reach-scale buffer vegetation of score 1 (i.e. low quality) predicts a high probability of a bad ASPT score (74%). The strengths of the BBN model are the ease of interpretation, fast simulation, ability to explicitly indicate uncertainty in model outcomes, and interactivity. These merits point to the potential use of the BBN model in workshop activities to stimulate key learning processes that help inform the management of riparian zones.
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Affiliation(s)
- Marie Anne Eurie Forio
- Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology, Ghent University, 9000 Ghent, Belgium.
| | - Francis J Burdon
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden; Te Aka Mātuatua - School of Science, University of Waikato, Hamilton, New Zealand.
| | - Niels De Troyer
- Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology, Ghent University, 9000 Ghent, Belgium.
| | - Koen Lock
- Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology, Ghent University, 9000 Ghent, Belgium
| | - Felix Witing
- Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research-UFZ, 04318 Leipzig, Germany.
| | - Lotte Baert
- Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology, Ghent University, 9000 Ghent, Belgium.
| | - Nancy De Saeyer
- Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology, Ghent University, 9000 Ghent, Belgium.
| | - Geta Rîșnoveanu
- Department of Systems Ecology and Sustainability, University of Bucharest, 050095 Bucharest, Romania; Research Institute of the University of Bucharest, 050663 Bucharest, Romania.
| | - Cristina Popescu
- Department of Systems Ecology and Sustainability, University of Bucharest, 050095 Bucharest, Romania.
| | - Benjamin Kupilas
- Norwegian Institute for Water Research (NIVA), 0349 Oslo, Norway; Institute of Landscape Ecology, University of Münster, 48149 Münster, Germany.
| | - Nikolai Friberg
- Norwegian Institute for Water Research (NIVA), 0349 Oslo, Norway; Freshwater Biological Section, Department of Biology, Universitetsparken 4, 3rd floor, 2100 Copenhagen, Denmark; water@leeds, School of Geography, Leeds LS2 9JT, UK.
| | - Pieter Boets
- Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology, Ghent University, 9000 Ghent, Belgium; Provincial Centre of Environmental Research, Godshuizenlaan 95, B-9000 Ghent, Belgium.
| | - Richard K Johnson
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden
| | - Martin Volk
- Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research-UFZ, 04318 Leipzig, Germany.
| | - Brendan G McKie
- Department of Aquatic Sciences and Assessment, Swedish University of Agricultural Sciences, 75007 Uppsala, Sweden.
| | - Peter L M Goethals
- Aquatic Ecology Research Unit, Department of Animal Sciences and Aquatic Ecology, Ghent University, 9000 Ghent, Belgium.
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Regression Tree Analysis for Stream Biological Indicators Considering Spatial Autocorrelation. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18105150. [PMID: 34067950 PMCID: PMC8152292 DOI: 10.3390/ijerph18105150] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/20/2021] [Revised: 05/07/2021] [Accepted: 05/10/2021] [Indexed: 11/17/2022]
Abstract
Multiple studies have been conducted to identify the complex and diverse relationships between stream ecosystems and land cover. However, these studies did not consider spatial dependency inherent from the systemic structure of streams. Therefore, the present study aimed to analyze the relationship between green/urban areas and topographical variables with biological indicators using regression tree analysis, which considered spatial autocorrelation at two different scales. The results of the principal components analysis suggested that the topographical variables exhibited the highest weights among all components, including biological indicators. Moran′s I values verified spatial autocorrelation of biological indicators; additionally, trophic diatom index, benthic macroinvertebrate index, and fish assessment index values were greater than 0.7. The results of spatial autocorrelation analysis suggested that a significant spatial dependency existed between environmental and biological indicators. Regression tree analysis was conducted for each indicator to compensate for the occurrence of autocorrelation; subsequently, the slope in riparian areas was the first criterion of differentiation for biological condition datasets in all regression trees. These findings suggest that considering spatial autocorrelation for statistical analyses of stream ecosystems, riparian proximity, and topographical characteristics for land use planning around the streams is essential to maintain the healthy biological conditions of streams.
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