Effects of forest cover pattern on water quality of low-order streams in an agricultural landscape in the Pirapora river basin, Brazil

Abstract

Low-order streams are important regions for river formation and are highly vulnerable to changes in terrestrial systems. Thus, the land-use/land-cover plays an important role in the maintenance of water quality. However, only its composition may not explain the spatial variation in water quality, because it does not consider landscape con gurations. In this context, the study aimed to evaluate the forest cover pattern effects on water quality on low-order streams, which integrated an agricultural landscape. Applying a paired watershed method, we selected watersheds classi ed according to their morphometry and average slope to discard other physical factors that could in uence the water quality. Land-use/landcover pattern was analyzed for composition and forest cover con guration using landscape metrics, including the riparian zone composition. Water quality variables were obtained every two weeks during the hydrological year. This way, watersheds had similar morphometry, slope, and land-use/land-cover composition but differed in landscape con guration. Watershed with more aggregated forest cover had a better water quality than the other one. The results show that forest cover contributes to water quality maintenance, while forest fragmentation in uences the water quality negatively, especially in sediment retention. Agricultural practices are sources of sediment and nutrients to the river, especially in steep relief. Thus, in addition to land-use/land-cover composition, landscape pattern must be considered in management of low-order streams in tropical agricultural watersheds.

A century of anthropogenic river alterations in a highly diverse river coastal basin: Effects on fish assemblages

“…As such, rivers have natural productivity pulses to which communities respond by trophic interactions and abundance adjustments (Connell and Ghedini, 2015). In the Andalién River basin, productivity may have increased due to the continuous nutrient inputs from agriculture and forestry and the increased frequency of non-natural forest fires resulting from monoculture with highly inflammable exotic species like Pinus and Eucalyptus (Arriagada et al, 2019;de Mello et al, 2022). Recruitment mechanism includes both habitat connectivity and species dispersal ability.…”

Estimating Thresholds of Natural Vegetation for the Protection of Water Quality in South African Catchments

“…Furthermore, while this study dealt with simple compositional land cover metrics (e.g., proportions natural vegetation at various scales), several studies have found that the arrangement of land cover (i.e., landscape configuration) may also influence water quality. It is commonly assumed, for instance, that as natural vegetation cover becomes increasingly fragmented, its ability to trap and intercept surface runoff is reduced (Gergel et al, 2002;Ding et al, 2016;Lintern et al, 2018;Liu & Yang, 2018;Yirigui et al, 2019;Zhang et al, 2019;Cole et al, 2020;Thomas et al, 2020;de Mello et al, 2022;Bowes et al, 2023;Xu et al, 2023a). Therefore, when designing and implementing strategies to protect water quality by maintaining sufficient areas of natural vegetation within riparian areas and across catchments, it is recommended that the potential effects of landscape fragmentation be given due consideration.…”

“…To this end, decades of research and literally hundreds of independent studies have demonstrated that relatively simple statistical models can be effective tools that support informed decision-making when developing integrated management plans (du Plessis et al, 2015;Giri & Qiu, 2016;Rodríguez-Romero et al, 2018;Ullah et al, 2018;Lacher et al, 2019;Cheng et al, 2022;Li et al, 2022a;Gobry et al, 2023). These studies show that while the relationship between LULC and water quality is undeniably complex and often regionally specific, certain anthropogenic classes of LULC (e.g., built-up areas, farmland, mines, and forestry plantations) tend to be sources of diffuse pollution, whereas most classes of natural vegetation (e.g., indigenous forests, grasslands, and wetlands) serve as sinks by intercepting, filtering, and remediating contaminated runoff (Lintern et al, 2018;Fernandes et al, 2021;Wang et al, 2021;Cheng et al, 2022;de Mello et al, 2022;Li et al, 2022b;Caldwell et al, 2023;Qiu et al, 2023;Siqueira et al, 2023;Xu et al, 2023a;Zhang et al, 2023).…”

“…Alternatively, the influence of extraneous variables can be dealt with ex ante in the design of cross-sectional studies by minimising variation within the sample so that LULC is, as far as possible, the only factor that varies between sites (Klein, 1979;Lenat & Crawford, 1994;Grimstead et al, 2018;de Mello et al, 2022). A common approach is to conduct studies within regions that are relatively homogeneous in terms of local geology, ecology, and climate, thereby minimising differences in these variables within the sample (Slaughter & Mantel, 2017;Grimstead et al, 2018;de Mello et al, 2022).…”

The Impact of Various Types of Cultivation on Stream Water Quality in Central Poland

“…Studies focusing on land cover effects on water quality have been conducted at several spatial scales, mainly to evaluate different predictors of water contaminants for management purposes [94]. Catchment scale [100], buffer zones [101], circular buffers [28], and distance-weighted approaches [27] have been adopted in numerous studies, which have modeled the spatial variability of biogenic compounds, oxygen indices, and trace metals [53,94]. There are no unified conclusions about the most informative spatial scale, as in some studies the whole catchment is the key to understanding some of the water quality parameters [102,103].…”