Multi-Scale Assessment of Relationships between Fragmentation of Riparian Forests and Biological Conditions in Streams

Riparian Landscape Change: A Spatial Approach for Quantifying Change and Development of a River Network Restoration Model

Natural river landscapes can be biodiversity hotspots but are one of the most human altered ecosystems with habitats significantly damaged around the world, and a third of fish populations threatened with extinction. While riparian ecosystems have been negatively altered by anthropogenic activities, effective planning and restoration strategies can reverse negative impacts by improving habitat quality. However, restoring rivers requires appropriate data on current riparian health while also considering priorities for different stakeholders. To address this, a Geographic Information System (GIS) was used to create a new and transferable restoration priority model based on a section of the river Linth in Switzerland as a case study. The restoration priority model is founded on connectivity, river condition, national priority species and species hotspots. Landscape change of the riparian zone was analyzed using aerial imagery and landscape metrics. Almost a quarter of rivers within the study area were considered high or very high restoration priority, with many aquatic species set to benefit from restoration. From 1946 to 2019, the riparian landscape became highly fragmented due to significant growth in impervious surfaces and a concomitant loss of agricultural land. The GIS model provides a tool by which environmental agencies can manage natural features over large scales, while also planning priorities and targeting conservation strategies to the areas of greatest need.

Environmental and ichthyofaunistic characteristics of Amazonian streams with and without fish farm

The environmental impacts caused by fish farming can lead to changes in aquatic ecosystems, especially in fish communities. In this study, we investigated possible changes in water quality, in the number of species and individuals of the same species caused by the construction of fish nurseries in dammed Amazonian streams. For this purpose, four streams located in the municipalities of Novo Airão and Presidente Figueiredo were selected. Samples were collected in streams without fish farming and in streams with stretches used for fish farming, where collections took place both downstream and upstream. The fish were captured, identified, quantified and the water was collected for physical and chemical analyses, in addition to the environmental characterization that was carried out. Comparisons were made using fish richness and abundance indices between the sampled points and correspondence analysis of the species identified at the collection sites, using the Mantel test and principal component analysis (PCA) for the environmental characteristics of the water and variables physical and chemical, and permutational multivariate analysis of variance (PERMANOVA) to verify the possible effects of species composition on the sampled conditions and on the analyzed environmental variables. In total, 2,302 fish belonging to 53 species, 15 families and six orders were found. We conclude that the Amazonian streams dammed for fish farming, under the analyzed conditions, can be characterized as environments with different and specific levels of richness and abundance, however, the data set analyzed in this study did not show that these characteristics are directly related to productive activity. We recommend that further studies be carried out following the current research.

Threats, biodiversity drivers and restoration in temperate floodplain forests related to spatial scales

Floodplain forests offer a diversity of habitats and resources for a very wide range of plant and animal species. They also offer many benefits to humankind and are considered essential to the mitigation of the effects of climate change. Nevertheless, throughout the world they are suffering the most intense of anthropogenic pressures so are, of all ecosystems, among the most endangered. Here, we bring together and synthesise existing ecological understanding of the mechanisms underlying the high heterogeneity and diversity of temperate floodplain forests and of the pressures threatening their high biological value due to habitat homogenisation. Floodplain forests depend on the periodic disturbances under which they evolved, including fluvial dynamics, traditional management practices and the activities of herbivores. However, they have been heavily degraded by climate change, invasion of exotic species, river-flow regulation, landscape fragmentation, eutrophication and the cessation of traditional management. We can now observe two general trends in temperate floodplain forests: (1) Due to intensive landscape exploitation, they are now more open and thus prone to the spread of competitive species, including of invasive exotics and (2) Due to the cessation of traditional management, along with modified hydrological conditions, they are composed of species in the later successional stages (i.e., more shade-tolerant and mesic) while light-demanding species are quickly vanishing. Restoration practices have brought about contrasting results when restoration of floodplains to their natural states has been problematic. This is likely because of interplay between various natural and artificial processes not previously taken into proper consideration. We would like to draw attention to the fact that restoration projects or the preservation of existing floodplain forest ecosystems should combine the restoration of watercourses with the mitigation of other important threats acting at different scales of the landscape (spread of invasive species, eutrophication of watersheds and inappropriate forest management).

Regression Tree Analysis for Stream Biological Indicators Considering Spatial Autocorrelation

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.

Evaluating the Relationships between Riparian Land Cover Characteristics and Biological Integrity of Streams Using Random Forest Algorithms

The relationships between land cover characteristics in riparian areas and the biological integrity of rivers and streams are critical in riparian area management decision-making. This study aims to evaluate such relationships using the Trophic Diatom Index (TDI), Benthic Macroinvertebrate Index (BMI), Fish Assessment Index (FAI), and random forest regression, which can capture nonlinear and complex relationships with limited training datasets. Our results indicate that the proportions of land cover types in riparian areas, including urban, agricultural, and forested areas, have greater impacts on the biological communities in streams than those offered by land cover spatial patterns. The proportion of forests in riparian areas has the greatest influence on the biological integrity of streams. Partial dependence plots indicate that the biological integrity of streams gradually improves until the proportion of riparian forest areas reach about 60%; it rapidly decreases until riparian urban areas reach 25%, and declines significantly when the riparian agricultural area ranges from 20% to 40%. Overall, this study highlights the importance of riparian forests in the planning, restoration, and management of streams, and suggests that partial dependence plots may serve to provide insightful quantitative criteria for defining specific objectives that managers and decision-makers can use to improve stream conditions.

Identifying Key Watershed Characteristics That Affect the Biological Integrity of Streams in the Han River Watershed, Korea

Understanding the complex human and natural processes that occur in watersheds and stream ecosystems is critical for decision makers and planners to ensure healthy stream ecosystems. This study aims to characterize the Han River watershed in Korea and extract key relationships among watershed attributes and biological indicators of streams using principal component analysis (PCA) and self-organizing maps (SOM). This study integrated watershed attributes and biological indicators of streams to delineate the watershed and stream biological status. Results from PCA strongly suggested that the proportions of watershed and riparian land use are key factors that explain the total variance in the datasets. Forest land in the watershed appeared to be the most significant factor. Furthermore, SOM planes showed that the biological indicators of streams have strong positive relationships with forest land, well-drained soil, and slope, whereas they have inverse relationships with urban areas, agricultural areas, and poorly drained soil. Hierarchical clustering classified the watersheds into three clusters, exclusively located in the study areas depending on the degree of forest, urban, and agricultural areas. The findings of this study suggest that different management strategies should be established depending on the characteristics of a cluster to improve the biological condition of streams.

Integrating Diverse Perspectives for Managing Neighborhood Trees and Urban Ecosystem Services in Portland, OR (US)

Municipalities worldwide are increasingly recognizing the importance of urban green spaces to mitigate climate change’s extreme effects and improve residents’ quality of life. Even with extensive earlier research examining the distribution of tree canopy in cities, we know little about human perceptions of urban forestry and related ecosystem services. This study aims to fill this gap by examining the variations in socioeconomic indicators and public perceptions by asking how neighborhood trees and socioeconomic indicators mediate public perceptions of ecosystem services availability. Using Portland, Oregon (USA) as our case study, we assessed socioeconomic indicators, land cover data, and survey responses about public perceptions of neighborhood trees. Based on over 2500 survey responses, the results indicated a significant correlation among tree canopy, resident income, and sense of ownership for urban forestry. We further identified the extent to which the absence of trees amplifies environmental injustices and challenges for engaging communities with landscape management. The results suggested that Portland residents are aware of tree maintenance challenges, and the inclusion of cultural ecosystem services can better address existing environmental injustices. Our assessment of open-ended statements suggested the importance of conducting public outreach to identify specific priorities for a community-based approach to urban forestry.

Landscape Dynamics in an Iconic Watershed of Northwestern Mexico: Vegetation Condition Insights Using Landsat and PlanetScope Data

Natural vegetation in arid and semi-arid environments of Northwestern Mexico has been subject to transformation due to extensive and intensive human occupation related mostly to primary activities. Keystone habitats such as riparian ecosystems are extremely sensitive to land use changes that occur in their surrounding landscape. In this study, we developed remote sensing-based land cover classifications and post-classification fragmentation analysis, by using data from Landsat’s moderate resolution sensors Thematic Mapper and Operational Land Imager (TM and OLI) to assess land use changes and the shift in landscape configuration in a riparian corridor of a dynamic watershed in central Sonora during the last 30 years. In addition, we derived a high spatial resolution classification (using PlanetScope-PS2 imagery) to assess the “recent state” of the riparian corridor. According to our results, riparian vegetation has increased by 40%, although only 9% of this coverage corresponds to obligate riparian species. Scrub area shows a declining trend, with a loss of more than 17,000 ha due to the expansion of mesquite and buffelgrass-dominated areas. The use of moderate resolution Landsat data was essential to register changes in vegetation cover through time, however, higher resolution PlanetScope data were fundamental for the detection of limited aerial extent classes such as obligate riparian vegetation. The unregulated development of anthropogenic activities is suggested to be the main driver of land cover change processes for arid ecosystems in this region. These results highlight the urgent need for alternative management and restoration projects in an area where there is almost a total lack of protection regulations or conservation efforts.

Spatially Varying and Scale-Dependent Relationships of Land Use Types with Stream Water Quality

Understanding the complex relationships between land use and stream water quality is critical for water pollution control and watershed management. This study aimed to investigate the relationship between land use types and water quality indicators at multiple spatial scales, namely, the watershed and riparian scales, using the ordinary least squares (OLS) and geographically weighted regression (GWR) models. GWR extended traditional regression models, such as OLS to address the spatial variations among variables. Our results indicated that the water quality indicators were significantly affected by agricultural and forested areas at both scales. We found that extensive agricultural land use had negative effects on water quality indicators, whereas, forested areas had positive effects on these indicators. The results also indicated that the watershed scale is effective for management and regulation of watershed land use, as the predictive power of the models is much greater at the watershed scale. The maps of estimated local parameters and local R² in GWR models showcased the spatially varying relationships and indicated that the effects of land use on water quality varied over space. The results of this study reinforced the importance of watershed management in the planning, restoration, and management of stream water quality. It is also suggested that planners and managers may need to adopt different strategies, considering watershed characteristics—such as topographic features and meteorological conditions—and the source of pollutants, in managing stream water quality.