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Article

Intensification of Human Land Use Decreases Taxonomic, Functional, and Phylogenetic Diversity of Macroinvertebrate Community in Weihe River Basin, China

by
Jixin Ma
1,
Xuwang Yin
1,*,
Gang Liu
1,* and
Jinxi Song
2
1
Liaoning Provincial Key Laboratory for Hydrobiology, College of Fisheries and Life Science, Dalian Ocean University, Dalian 116000, China
2
Shanxi Key Laboratory of Earth Surface System and Environmental Carrying Capacity, College of Urban and Environmental Sciences, Northwest University, Xi’an 710127, China
*
Authors to whom correspondence should be addressed.
Diversity 2024, 16(9), 513; https://doi.org/10.3390/d16090513
Submission received: 25 June 2024 / Revised: 23 August 2024 / Accepted: 23 August 2024 / Published: 26 August 2024
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Abstract

:
Recent anthropogenic activities have escalated human exploitation of riparian zones of river ecosystems, consequently diminishing aquatic biodiversity. This intensification of land use is also causing water quality degradation and changes in water environmental factors, evidenced by increased nutrient levels and adversely impacting the community structure and diversity of aquatic organisms. Notably, the Weihe River Basin, the largest tributary of the Yellow River, has demonstrated signs of significant anthropogenic pressure. Despite this, comprehensive investigations examining the effects of land-use intensity on aquatic organism diversity in this watershed remain limited. In this study, the environmental impacts and macroinvertebrate diversity under high-intensity and low-intensity land-use scenarios within the Weihe River Basin were investigated through field surveys conducted during the spring and autumn seasons. Our results demonstrated that areas under high-intensity land use exhibited elevated nutrient concentrations (e.g., total nitrogen) compared to those under low-intensity land use. These environmental changes significantly influenced the macroinvertebrate community structure, reducing functional and phylogenetic diversities in high-intensity land-use watersheds. Hydrological factors (water depth, river width, and discharge) have a significant impact on macroinvertebrate taxonomic diversity. Thus, understanding the effects of land-use intensity on aquatic biodiversity is essential for ecological assessments of impacted watersheds and developing management strategies for the sustainable use and planning of riparian lands in the Weihe River Basin.

1. Introduction

Land-use changes resulting from human activities are a principal cause of global biodiversity loss [1]. However, freshwater ecosystems are the most threatened ecosystems worldwide [2]. Global forest degradation [3,4], coupled with the expansion of agricultural and urban areas, is steadily worsening, with land-use intensity escalating annually [5]. The growing urbanization observed today disrupts the integrity of river ecosystems, resulting in habitat loss and degradation [6]. Consequently, this eradicates or diminishes the number of native species while introducing alien species, exacerbating biodiversity decline [7]. Moreover, increased land-use intensity alters water nutrient compositions, detrimentally impacting ecosystems and posing threats to their ecological sustainability [8,9]. Hence, it is important to implement effective management strategies to mitigate the adverse effects of human activities and restore ecosystems to the fullest extent possible [10].
Water resources are the focus of global concern, as water quality plays a vital role for all kinds of organisms on the Earth [11]. However, the intensification of land use has led to a degradation in water quality on a worldwide scale [12]. Numerous studies have demonstrated that intensive land use, particularly in agriculture and urban development, generates a range of pollutants, including industrial wastewater, pesticides, and chemical fertilizers, which are subsequently discharged into adjacent rivers [13,14], contributing to elevated levels of nutrients, organic matter, and toxic substances in river systems. For instance, an increase in total nitrogen content can occur and potentially lead to a decline in dissolved oxygen levels as organic matter accumulates. Furthermore, toxic compounds input can further compromise water quality [15], posing a significant threat to the stability of river ecosystems [16]. The intensity of land use also alters habitat conditions and hydrological parameters such as river width, discharge rates, and water depth, which vary in response to land-use patterns [17]. Thus, assessing the relationship between land-use intensity and water quality is important for preserving aquatic environments and the overall health of water ecosystems [18]. The community structure and biodiversity of aquatic organisms in river ecosystems are increasingly threatened by human activities, especially the change of land-use intensity [19]. Aquatic biodiversity will suffer as a result of the high-intensity land use that is typified by widespread urbanization and intensive agriculture. Increased impermeable surfaces in urban areas can lead to altered hydrological conditions and elevated river pollution levels. According to studies, urbanization decreases habitat quality, modifies hydrochemistry, and increases habitat fragmentation, all negatively affecting aquatic biodiversity [20]. Excessive use of agricultural practices such as fertilizers and pesticides can increase nutrients and water pollution. High levels of nutrition can lead to eutrophication, which destroys the balance of aquatic ecosystems and is conducive to the proliferation of some pollution-tolerant species. On the other hand, low-intensity land use tends to have a higher level of aquatic biodiversity because it has less interference and lower pollutant input. In this context, the aquatic biodiversity of sensitive and endangered species increases [21]. Therefore, understanding the impact of land-use intensity on aquatic biodiversity is essential to the effective protection and management strategy of the ecosystem. Macroinvertebrates in river ecosystems serve as highly sensitive indicators of habitat integrity and water quality, rendering them essential for biological monitoring and assessment [22,23]. Generally, intensive land use in watersheds impacts the biodiversity and community structure of macroinvertebrates (i.e., taxonomy, function, and phylogeny) by altering the quality of the water environment [24,25,26,27,28,29]. The richness of macroinvertebrate species is notably diminished under conditions of intensive land use, with high-intensity land use typically exhibiting lower biodiversity than low-intensity land use [30]. While taxonomic diversity is commonly utilized, it overlooks the relationship between environmental characteristics and macroinvertebrate traits [31]. In contrast, functional diversity provides insights into the distribution of species traits, linking species diversity to ecosystem function and serving as another biodiversity indicator [32]. Functional diversity often exhibits rapid and predictable responses to human-induced disturbances [33]. Phylogenetic diversity offers insights into the evolutionary history of species, their adaptation to past environmental conditions, and their unique roles within communities [34]. Combining phylogenetic and functional diversity helps compensate for shortcomings in species diversity assessment, providing a more comprehensive understanding of community biodiversity from evolutionary and functional perspectives [35]. Therefore, integrating taxonomic diversity (TD), functional diversity (FD), and phylogenetic diversity (PD) facilitates a comprehensive assessment of macroinvertebrate biodiversity.
The river ecosystem of the Weihe River Basin, the largest tributary of the Yellow River and also the fastest-growing region in northwest China, faces significant threats due to its dense population, rapid urbanization, industrial expansion, intensive agricultural practices, extensive human activities, and rising environmental pollution [17]. However, there remains a notable gap in research concerning the impact of land-use intensity and environmental factors on macroinvertebrate diversity within this region. Through field surveys conducted during both spring and autumn seasons in the Weihe River Basin, the following hypothesis was tested: Increased land-use intensity leads to changes in water quality, such as an increase in total nitrogen content. It also affects habitat conditions and hydrological parameters, such as river width, discharge, and water depth. This leads to a decrease in the classification, function, and phylogenetic diversity of macroinvertebrates.

2. Materials and Methods

2.1. Study Area

The Weihe River Basin is the largest tributary of the Yellow River, with a total area of approximately 134,766 km2 and an average annual runoff of 7.57 billion m3 [36]. It is located between 104–110° E and 34–37° N (Figure 1). The Weihe River System, the Jinghe River System, and the Beiluo River System and its tributaries comprise most of the entire river [37]. The Guanzhong Plain lies east of the Weihe River Basin, while loess hills and a gully zone lie to its west. The basin gradually rises in height from east to west, consists of arid to semi-humid regions, and is part of the continental climate. Winters are chilly, and summers are humid and muggy. The average annual temperature is 7.8 to 13.5 °C, with about 500 to 800 mm of precipitation. The sea surface evaporation fluctuates between 660 to 1600 mm, whereas continental plate evaporation is approximately 500 mm [38]. Notably, the Weihe River watershed carries significant silt due to its passage across the Loess Plateau. Predominant land uses within the basin include agriculture and forests, with urban development primarily concentrated along the lower reaches of the Weihe River.

2.2. Land-Use Data and Site Classification

Land-use and land-cover change (LUCC) data from 1990 to 2019 were obtained from the Wuhan University annual land-use and -cover dataset, accessed through the CLCD repository (https://zenodo.org/records/5816591; accessed on 11 November 2023), utilizing Landsat images from Google Earth Engine [39]. These data had a spatial resolution of 30 m. The sample site served as the center of a buffer that had a radius of one kilometer and was constructed using ArcGIS 10.5 software [40]. The percentage of each land-use type was computed following the extraction of the land-use grid data. Principal component analysis (PCA) was employed to investigate variations in land-usage percentages across sampling locations during spring and autumn [41]. According to the variance of each principal component interpretation, the components with larger variance are considered to be more influential in shaping land-use patterns and were used to determine their thresholds.

2.3. Sample Collection and Processing

Two sample surveys were conducted in October 2011 and April 2012. The two surveys selected 34 sampling points in the whole Weihe River Basin. However, due to the uncertainty of field sampling, there were several points in spring that did not completely coincide with autumn, but the land-use intensity of the points was consistent with that of the previous points. Only two field surveys were used as parallel experiments. The MAGELLAN Global Positioning System (eXplorist-200) was utilized to record each sampling site’s longitude, latitude, and elevation. Samples were collected using a Surber net with a mesh area of 30 cm × 30 cm and an aperture of 500 μm, with two parallel samples randomly taken within a 100 m radius of each designated spot. Subsequently, macroinvertebrates visible to the unaided eye were separated from stones, dirt, and other debris and preserved in 90% alcohol within a 100 mL sample bottle [42]. The samples were then further preserved with 95% alcohol, categorized, and enumerated under microscope. Whenever possible, macroinvertebrate specimens were identified at the genus or species level based on the relevant literature [43,44,45,46,47].
A water quality analyzer (YSI85) was employed to measure various parameters, including salinity (Sal), saturation (Satu), temperature (Temp), electrical conductivity (EC), and dissolved oxygen (DO), at each sampling site in the Weihe River Basin. River width was determined in the field using a meter ruler, while a portable pH indicator (HANNA instruments, model: HI 98130) was used to assess acidity levels. In situ measurements of water depth (Depth) and velocity (Velo) were conducted using a digital handheld water velocity meter (FP111). For more in-depth information about the measuring instrument, more strictly, see the following web pages: https://www.ysi.com/File%20Library/Documents/Specification%20Sheets/FP111-Flow-Probe-Specification-Sheet.pdf (accessed on 21 June 2024). Sediment concentration (Sand) was determined using a set of sediment sample sieves with pore diameters of 16, 8, 4, 2, and 1 mm. At each sampling site, two identical 2 L water samples were collected, stored in a low-temperature incubator, and transported to the laboratory within 48 h. In the laboratory, hydrochemical indices including suspended solids (SS), total dissolved solids (TDS), silicate (SiO24−), total nitrogen (TN), total phosphorus (TP), alkalinity (Alk), hardness (TD), and permanganate index (CODMn) were determined following relevant standards (Table S2) [48].

2.4. Macroinvertebrates Functional Traits

Nine traits with thirty-two different trait categories were considered for analysis (Table 1). According to our literature review, we selected the following traits: morphology (size and respiration), ecology (rheophilic, thermal preference, habit, and trophic habit), mobility (female dispersal and occurrence in drift), and life history (voltinism) [49,50]. These traits were chosen for their relevance to habitat preference, nutritional status, and their indication of the relationship between morphological adaptability and environmental conditions [51]. Additionally, these traits have been identified as responsive indicators to anthropogenic stressors, thereby serving as valuable tools for characterizing the functional response of macroinvertebrates in this region [52,53].

2.5. Data Analysis

Using PCA analysis conducted in Canoco 5 software [54], the land-use intensity within the Weihe River Basin was classified into low and high intensity. An Excel (Version 2402 Build 16.0.17328.20550 64-bit) able was utilized to compute the density and dominant species of macroinvertebrates under differing levels of human land-use intensity [55]. The dominance index (Y) was calculated using the following formula:
Y = ( ni / N ) × fi
where ni represents the number of individuals of the i species, N is the total number of individuals of all species, and fi is the occurrence frequency of species i, that is, the ratio of the sample number of species i occurrence to the total sample number under different land-use intensity. A species is considered dominant when its Y value exceeds 0.02. Macroinvertebrate diversity indices for each sampling site were then determined, including the Shannon–Wiener diversity index, Simpson diversity index, Pielou evenness index, and species richness index, serving as indicators of taxonomic diversity. These indices were computed using the vegdist function (vegan package) in R version 4.3 [56], known for its comprehensive approach to measuring ecosystem biodiversity.
The functional diversity index (FD) encompasses Rao’s quadratic entropy index (RaoQ), functional richness index (FRic), functional evenness index (FEve), functional divergence index (FDiv), and functional dispersion index (FDis). These indices were computed utilizing the “FD” package, integrated into the R package Vegetarian 4.3 [57]. Combining these indices provides a more comprehensive depiction of functional diversity, as each index captures a distinct aspect of it, offering a more realistic portrayal of the overall functional variety within the community [58,59,60,61].
Phylogenetic diversity (PD) encompasses four indicators: taxonomic diversity index (Δ), taxonomic distinctness index (Δ*), variation in taxonomic distinctness index (Λ+), and average taxonomic distinctness index (Δ+). At the genus level, the Linnean phylogenetic tree contains the following six taxonomic levels: genus, family, order, class, phylum, and kingdom. Classification distance based on path length was applied to compute these indices using the “taxondive” and “taxa2dist” functions in the R package Vegetarian (version 4.3). [62].
The IBM SPSS Statistics 26 software was utilized to conduct the Mann–Whitney U test and independent sample t-test to assess differences between different land-use types under varying human land-use intensities as well as the differences between environmental factors, taxonomic diversity, functional diversity, and phylogenetic diversity across different human land-use intensity levels. Environmental elements were included as explanatory variables in the analysis, and the obtained results were visualized using Origin 2019b 32Bit software.
The vegan package and ggplot2 package [63] in RStudio software (version 4.3) were used to conduct db-RDA and PERMANOVA analysis to explore the relationship between land-use intensity, environmental factors, and macroinvertebrate diversity and to plot it.

3. Results

3.1. Environmental Characteristics

In autumn, the first principal component (PC1) accounted for 49.57% of the variance (Figure 2A). In contrast, in spring, PC1 accounted for 50.83% of the variance (Figure 2B). It can be seen that the influence of PC1 axis is greater, about 50%, so the land-use intensity was divided into a low-intensity group (n = 17) and high-intensity group (n = 17) according to the PC1 axis. PC1 exhibited a negative correlation with the extent of grasslands and forests while demonstrating a positive correlation with the areas occupied by built-up land, croplands, and water bodies (Figure 2). To detect the differences in land use among different grades, the Mann–Whitney U test and the independent sample t-test were used (Figure 3 and Table S1), and the findings demonstrated that while the area of forest and grassland dramatically declined, the coverage of cropland, water area, and built-up land grew significantly with an increase in human land-use intensity.
The results indicate significant differences in environmental factors across varying land-use intensities (Table S2 and Figure 4). Specifically, in areas characterized by high and low land-use intensities, the total nitrogen content significantly increased in the high-intensity group, while the low-intensity group exhibited higher levels of dissolved oxygen. Furthermore, the total nitrogen content was observed to be higher during autumn compared to spring, while the dissolved oxygen content was lower during autumn compared to spring. Hydrological characteristics during the fall notably impacted both high- and low-intensity human land-use areas, with the low-intensity group demonstrating considerably narrower river width, reduced water depth, and slower flow rates compared to the high-intensity group. However, no significant differences were observed during the spring season (Figure 4).

3.2. Macroinvertebrates Community Characteristics

In autumn, a total of 77 genera, 3 phyla, and 6 classes of macroinvertebrate species were observed, while in spring, 31 genera, 3 phyla, and 4 classes were observed. The class Insecta predominated in both seasons, closely followed by Oligochaeta, while the other groups exhibited a lesser prevalence. During autumn, Insecta constituted 66.81% of the macroinvertebrate population, Oligochaeta accounted for 31.46%, and other groups represented 1.73%. In spring, Insecta comprised 55.12% of the macroinvertebrate community, while Oligochaeta constituted 44.58% (Figure 5A). The density of macroinvertebrates in the low-intensity group was higher during autumn (15,500 ind/m2) compared to the high-intensity group (6540 ind/m2). In autumn, the density of Insecta was highest in the low-intensity group (12,100 ind/m2), whereas Oligochaeta density was highest in the high-intensity group (3780 × 103 ind/m2). Conversely, during spring, the low-intensity group exhibited lower density (15,800 ind/m2) compared to the high-intensity group (25,700 ind/m2), with Insecta being the most abundant in the low-intensity group (15,400 ind/m2) and Oligochaeta in the high-intensity group (17,800 ind/m2) (Figure 5B). Relative abundance analysis revealed that Insecta dominated in both intensity groups during autumn, accounting for 78% in the low-intensity group and 40% in the high-intensity group. Oligochaeta exhibited a higher relative abundance in the high-intensity group during autumn (58%), while in spring, Insecta dominated the low-intensity group (98%), and Oligochaeta dominated the high-intensity group (71%) (Figure 5C). Notably, during autumn, Limnodrilus sp. and Branchiura sp. dominated the high-intensity group, while Baetis sp. and Chironomidae dominated the low-intensity group. In spring, Limnodrilus sp. prevailed in the high-intensity group, while Hydropsyche sp., Cricotopus sp., and Sympotthastia sp. were dominant in the low-intensity group (Table 2).

3.3. Taxonomic α Diversity Patterns

In both autumn and spring, the low-intensity group exhibited significantly higher species richness compared to the high-intensity group (p = 0.002, p = 0.024) (refer to Figure 6A). Moreover, the Shannon–Wiener diversity index of the low-intensity group was significantly higher than that of the high-intensity group during autumn (p = 0.01), although no significant difference was observed in spring (p = 0.086). Notably, the Shannon–Wiener diversity index was higher in autumn compared to spring (Figure 6B). There were no significant differences in the evenness index between the high-intensity and low-intensity groups, and this index remained consistent across spring and autumn (Figure 6C). Additionally, the Simpson diversity index of the low-intensity group was significantly higher than that of the high-intensity group during autumn (p = 0.041), but no significant difference was observed in spring (refer to Figure 6D) (Table S3).

3.4. Functional α Diversity Patterns

According to the proportion of functional groups, there were differences in functional groups between the high-intensity group and the low-intensity group. In autumn, the low-intensity group primarily exhibited univoltine life history (Volt2), high female dispersal (Disp2), and abundant drift (Drft3) in mobility. The respiratory mode was predominantly gills (Resp2), while ecological rheology leaned towards sedimentary or erosion habitats, with most of the group classified as swimmers (Habit5). Conversely, the high-intensity group in autumn showed a predominantly multivoltine life history (Volt3), non-dispersive mobility (Disp3), and weak drifting (Drft1). Morphologically, tegument (Resp1) was the primary respiratory mode, and ecological rheology favored deposition habitats, with a preference for cold/warm eurythermal thermal conditions (Ther2). The trophic habit leaned towards shredder (detritivore) behavior, with a prevalence of clingers (Habit4) (Trop5) (Figure 7). In spring, the low-intensity group predominantly displayed univoltine life history (Volt2), strong female dispersal (Disp2), and abundant drift (Drft3) in mobility. Morphologically, small size (Size1) and gills (Resp2) were the primary respiratory modes. Thermal preference tended towards chilly stenothermal or cool eurythermal conditions (Ther1), while ecological rheology favored sedimentary or erosion habitats (Rheo2), with a trophic habit primarily as collector-gatherers (Trop1). Conversely, the high-intensity group in spring exhibited a mostly multivoltine life history (Volt3), non-dispersive mobility (Disp3), and weak drifting (Drft1). Morphologically, tegument (Resp1) and small size (Size1) predominated. Ecologically, the preference was for deposition habitats (Rheo1) and cold/warm eurythermal thermal conditions (Ther2), with trophic behavior inclined towards burrowing (Habit1) and shredder (detritivore) habits (Trop5) (Figure 7).
Significant differences existed in the functional richness index between the high-intensity and low-intensity groups. The functional richness index of the low-intensity group was significantly higher than that of the high-intensity group in both spring and autumn, with slightly higher values observed in autumn compared to spring (Figure 8A). Notably, there was a significant difference between the low-intensity and high-intensity groups in terms of functional dispersion index and Rao’s quadratic entropy index during autumn, with the low-intensity group exhibiting higher indices compared to the high-intensity group, while no significant differences were observed in spring, although the low-intensity group’s indices were slightly higher than those of the high-intensity group (Figure 8B,C) (Table S3).

3.5. Phylogenetic Diversity α Diversity Patterns

In spring and autumn, no significant difference was observed in the taxonomic diversity index between the high-intensity and low-intensity groups, although the index of the low-intensity group marginally exceeded that of the high-intensity group, with slightly higher values noted in autumn compared to spring (Figure 9A). Conversely, the low-intensity group exhibited a considerably greater taxonomic distinctness index in both spring and autumn compared to the high-intensity group, with slightly higher values observed in autumn compared to spring (Figure 9B). Additionally, the variation in taxonomic distinctness index of the low-intensity group was significantly higher than that of the high-intensity group in spring and autumn, with slightly higher values noted in autumn compared to spring (Figure 9C). Furthermore, in spring, the low-intensity group’s average taxonomic distinctness index significantly exceeded that of the high-intensity group (Figure 9D) (Table S3).

3.6. Relationship between Land-Use Intensity, Environmental Factors, and Macroinvertebrate Diversity

According to db-RDA and PERMANOVA results in autumn 2011 and spring 2012, there were significant differences in the taxonomic, functional, and phylogenetic diversity of macroinvertebrates in intensive human land use (Figure 10). In autumn, the effect of land use on community classification composition (R2 = 0.125) was greater than that on functional composition (R2 = 0.075). However, the effect of land use on the phylogenetic composition of the community was not significant (Figure 10A–C). The key factors of taxonomic diversity of macroinvertebrates under different land-use intensities were Depth (p = 0.002), Velo (p = 0.018), and WT (p = 0.024), while the key factors of functional diversity were TN (p = 0.001), DO (p = 0.012), and TP (p = 0.016). Depth (p = 0.001) and Velo (p = 0.037) were the key factors in the difference of phylogenetic diversity of the community. In spring, the effect of land use on community classification composition (R2 = 0.427) was greater than that on phylogenetic composition (R2 = 0.102) and functional composition (R2 = 0.065). However, the effect of land use on the functional composition of the community was not significant (Figure 10D–F). The key factors of taxonomic diversity of macroinvertebrates under different land use intensities were River width (p = 0.001), Flow (p = 0.004), and Altitude (p = 0.004), while the key factors of functional diversity are Altitude (p = 0.001), TN (p = 0.01), and TP (p = 0.012). TN (p = 0.001), River width (p = 0.005), and Flow (p = 0.002) were the key factors in the difference of phylogenetic diversity of the community.

4. Discussion

4.1. Environmental Factors and Macroinvertebrates Community Characteristics under the Different Human Land-Use Intensities

Human activities and the intensity of land use are primary factors influencing changes in water quality [64]. It is consistent with the results of previous studies: The greater the intensity of land use, the more nitrogen pollution is caused by agricultural fertilization and the inflow of domestic and industrial wastewater. However, the Weihe River Basin has heavy rainfall in autumn, and the higher total nitrogen content in autumn may be caused by nitrogen pollutants from farmland being washed into the river. The content of aerobic pollutants such as nitrogen is negatively correlated with the content of dissolved oxygen, and the higher the pollution level, the lower the concentration of dissolved oxygen [65,66]. Dissolved oxygen levels significantly impact the behavior and physiology of macroinvertebrate species, thereby influencing benthic community dynamics [67]. We also observed a difference in hydrological factors under different human land-use intensities in autumn [68]. The reasons for the difference may include that the Weihe River watershed is a significant industrial hub in China, characterized by high silt concentration and substantial soil and water loss rates in the Yellow River Basin [69]. There is heavy rainfall in autumn and strong human interference, and the river embankment is seriously broken. The above factors combined lead to increase in flow and increase in river width. In spring, the rainfall is low, and the hydrological factors are reduced, so there is no significant difference [70]. These findings indicate that the increase in land-use intensities will augment the concentration of total nitrogen and may also decrease the dissolved oxygen level.
Macroinvertebrate communities are extremely sensitive to human disturbance in many ways, and these pressures affect the biological integrity of freshwater ecosystems through changes in species abundance and diversity. Sensitivity to environmental change makes macroinvertebrates a good indicator of environmental degradation [71]. In the Weihe River Basin, the major macroinvertebrate groups observed in both fall and spring were Insecta and Oligochaeta. In the high-intensity group, Limnodrilus sp. and Branchiura sp. emerged as dominant species, indicative of elevated water pollution levels [72], whereas Baetis sp. and Chironomidae dominated the low-intensity group, suggesting nutrient deficiencies within the water body as per the dominance degree formula. Notably, no significant difference between spring and autumn was observed in the dominant species. Previous studies confirmed the tolerance of Oligochaeta to adverse conditions such as eutrophication and hypoxia [73], while it was demonstrated that high-intensity human land use fosters the proliferation of polluting macroinvertebrate species, reflecting the severity of water pollution [74]. These findings support the hypothesis that intensified land use exacerbates water quality degradation, consequently impacting changes in macroinvertebrate community structure.

4.2. Intensive Human Land-Use Decreases Taxonomic Diversity

Compared with the low-intensity group, the high-intensity group exhibited decreased species richness, Shannon–Wiener diversity index, and Simpson diversity index in autumn. In spring, only species richness significantly declined in the high-intensity group. This pattern suggests that increased human activity adversely affects the diversity of macroinvertebrates, which are sensitive to environmental changes [75]. The low-intensity group, characterized by abundant natural vegetation, provides a variety of supplies, niches, and shelters, supporting higher biodiversity [76,77]. These observations confirm our hypothesis that increased human land-use intensity reduces taxonomic diversity and alterations in species composition [78,79].

4.3. Intensive Human Land-Use Decreases Functional Diversity

The results indicated that the functional group predominating in the high-intensity group exhibited greater tolerance. Macroinvertebrates in areas of high-intensity land use often exhibit traits such as multivoltine and tegument respiration, which enable survival in polluted habitats. Conversely, traits like univoltinism and gill respiration are more vulnerable to disruption [80]. The enhanced resilience (e.g., increased number of reproductive cycles per year) and resistance (e.g., tolerance to adverse conditions) observed among macroinvertebrates are responses to elevated nutrient levels (total nitrogen) and reduced dissolved oxygen levels in the watershed, stemming from intense human activity [81]. These characteristics provide significant refuge and adaptability in disturbed environments. Therefore, it is crucial to consider not only the taxonomic composition but also the relationship between macroinvertebrates’ functional traits and the level of human land use [82]. This evidence supports the notion that the functional groups of macroinvertebrates gradually shift towards species that are resistant to environmental changes as the intensity of human land use escalates.
Specifically, the FRic value for functional diversity under high-intensity human land use was significantly reduced. The decreases in FRic and FDis suggest that an increase in human land-use intensity correlates with reduced utilization of ecological space and niche differentiation. The RaoQ value, integrating aspects of FRic and FDiv, is an important metric for addressing various functional diversity issues. A reduction in RaoQ value implies that greater human land-use intensity is associated with decreased ecosystem water quality and enhanced habitat degradation [32]. These findings support the initial hypothesis, which posited a significant decline in functional diversity with increasing land-use intensity [83]. Thus, an escalation in land-use intensity precipitates a filtration of community biological traits and alterations in community composition, culminating in diminished functional diversity in the macroinvertebrate community.

4.4. Intensive Human Land-Use Decreases Phylogenetic Diversity

High-intensity land use in autumn resulted in a notable reduction in Δ* and Λ+, while in spring, high-intensity land use caused significant decreases in Δ*, Δ+, and Λ+. The reduction in the values of Δ*, Δ+, and Λ+ indicates a decrease in phylogenetic diversity [84]. These outcomes validate the hypothesis, which suggested that phylogenetic diversity declines as human land-use intensity increases [85]. The results also highlight that the taxonomic approach alone is insufficient for effectively monitoring and evaluating the impact of land-use intensity on macroinvertebrate habitats. Instead, incorporating measures of functional and phylogenetic diversity provides more robust tools for assessing how variations in land-use intensity influence macroinvertebrates within ecosystems.

4.5. Land-Use Intensity and Environmental Factors Affect the Diversity of Macroinvertebrates

We found that intensive land use had a greater impact on the taxonomic diversity of macroinvertebrate communities than functional diversity and phylogenetic diversity. Two surveys found that hydrological factors such as river width, water depth, and discharge under different land-use intensities significantly affected the taxonomic diversity of macroinvertebrate communities. The result is consistent with the previous research stating that strong man-made interference will cause hydrological changes that will impact the river ecosystem. In the study area with great human disturbance, hydrological factors such as discharge and depth reduce the richness and diversity of the macroinvertebrate community [86]. In addition to the above factors, the point distribution of the high-intensity group is close to the main river compared with that of the low-intensity group. River width, water depth, and discharge are large. Therefore, the topography and hydrological factors of the study area may also have a direct impact on the taxonomic diversity of large invertebrates [87]. Nutrients (TN) can be used as filters to select macroinvertebrates with specific functional characteristics. The high-intensity group had a high content of total nitrogen and a high nutrition level concerning water quality, and most of them were macroinvertebrates with tolerable functional characteristics, while sensitive species decreased or were lost, which led to the decrease in functional diversity of macroinvertebrates [88].
The phylogenetic diversity of macroinvertebrates was significantly affected by total nitrogen. The content of total nitrogen was higher and the phylogenetic diversity decreased in the high-intensity group. The width and depth of the river also have significant effects on the phylogenetic diversity.
The above research results show that the high-intensity group is affected by strong man-made interference on its hydrological factors and total nitrogen content. Dissolved oxygen and total phosphorus may also have an impact, resulting in the decrease in taxonomic diversity, functional diversity, and phylogenetic diversity of macroinvertebrates. And the diversity of macroinvertebrates may also be directly affected by the habitat, topography, or hydrological factors around the study area.
In addition to the impact of land-use intensity on macroinvertebrates communities and their biodiversity, there are other potential factors such as river reconstruction and water conservancy projects that may change the hydrodynamic and ecological characteristics of rivers and then affect the habitat and living conditions of macroinvertebrates, thus significantly affecting their diversity. In recent years, climate change has become a hot topic. Many studies have confirmed that climate change affects the water temperature, water level, and precipitation patterns of rivers and has a significant impact on the survival and distribution of macroinvertebrates. These factors may interact with each other and jointly affect the biodiversity of macroinvertebrates. Therefore, in the study of river ecology, it is necessary to comprehensively consider these factors and take comprehensive protection and management measures to maintain and restore the health of the river ecosystem.

4.6. Limitations and Suggestions

In this study, only two sampling surveys were carried out in autumn and spring in the Weihe River Basin, but no long-term observation and study were carried out. Therefore, it may only reflect the impact of land-use intensity on macroinvertebrate diversity at that time and cannot fully explain the long-term trend of change, and the interpretation of long-term effects may be limited by time scales. Previous studies have confirmed that changes in land-use intensity in the short term may directly affect the survival and habitat of macroinvertebrates, thus reducing the living space and food resources of animals [29]. Over time, these effects are likely to be further intensified or mitigated. For example, macroinvertebrates may gradually adapt to new environmental conditions or migrate to suitable areas. This may lead to the extinction of macroinvertebrates and a significant reduction in the number of populations [89]. Therefore, to predict the development trend of this impact, it is necessary to consider both natural and human factors and carry out long-term monitoring and evaluation. The method of collecting field survey data will also deviate from the results. Different species may respond differently to land-use intensity, and even the same species may respond differently in different regions or environmental conditions. As a result, single-species taxa surveys may not capture the full range of responses across all species. These limitations and deviations may lead to uncertainty in the interpretation of high land-use intensity reducing the diversity of macroinvertebrates. Considering these sources of uncertainty, the interpretation of the survey results needs to be carried out carefully and combined with other evidence and data for comprehensive analysis.
Our study elucidated the interplay between environmental changes and increased human land use and its consequential impact on macroinvertebrate community structures. We found that macroinvertebrates’ taxonomic, functional, and phylogenetic diversities all diminish as land use intensifies. These insights are pivotal for formulating enhanced conservation and restoration policies for urban river ecosystems. Therefore, it is necessary to implement regular biodiversity monitoring and survey projects to understand the status, distribution, and habitat preferences of macroinvertebrates communities so as to provide a scientific basis for the formulation of conservation strategies and protect and restore rivers, wetlands, forests, and other important habitats to ensure that macroinvertebrates have adequate living space and food resources. This can be achieved by restricting land development, implementing ecological restoration projects and ecological restoration, formulating and implementing land-use plans, balancing the relationship between economic development and ecological protection, encouraging farmers to adopt sustainable agricultural practices, reducing the use of chemical fertilizers and pesticides, and avoiding destructive acts such as overgrazing and deforestation. Through the comprehensive implementation of the above strategies and measures, we can effectively protect the biodiversity of macroinvertebrates in the Weihe River Basin and maintain the health and stability of the river ecosystem. This also requires the joint efforts and cooperation of the government, social organizations, scientific research institutions, and local communities. Focus should be directed toward restoring key habitats and damaged ecosystems, establishing ecological corridors and natural connecting channels, and promoting ecosystem connectivity, establishing a sound ecological monitoring system, etc. These measures can provide guidance and support for the restoration of macroinvertebrate diversity in areas with land-use intensity change in the future and promote the protection and restoration of biodiversity.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d16090513/s1, Table S1: Comparing 5 types of landuse coverage (%) among the low-intensity and high-intensity human land uses, including cropland, forest, grassland, water, and built-up area; Table S2: Comparative summary of two groups of environmental variables in autumn and winter (results of independent sample t-test (mean ± SD) and Mann-Whitney U test [M (P25, P75)]); Table S3: Summary description of the taxonomic, functional and phylogenetic diversity of α at different land use intensities in autumn and spring (results of independent sample t-tests (mean ± SD and Mann-Whitney U test [M (P25, P75)]); Table S4. Classification of macroinvertebrate communities under different land use intensities in autumn in Weihe River Basin; Table S5. Classification of macroinvertebrate communities under different land use intensities in spring in Weihe River Basin.

Author Contributions

Individual contributions of authors were as follows: Conceptualization, X.Y. and J.M.; methodology, J.M.; software, J.M.; formal analysis, J.M.; data curation, J.M.; writing—original draft preparation, J.M.; writing—review and editing, X.Y. and G.L.; project administration, X.Y. and J.S.; funding acquisition, X.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the National Natural Science Foundation of China (42230513, 41977193).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

The data is contained within the manuscript and Supplementary Materials.

Acknowledgments

We thank T. Pu for providing the code of R language’s phylogenetic diversity.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Newbold, T.; Hudson, L.N.; Hill, S.L.; Contu, S.; Lysenko, I.; Senior, R.A.; Börger, L.; Bennett, D.J.; Choimes, A.; Collen, B.J.N.; et al. Global effects of land use on local terrestrial biodiversity. Nature 2015, 520, 45–50. [Google Scholar] [CrossRef] [PubMed]
  2. Nieto, C.; Ovando, X.M.; Loyola, R.; Izquierdo, A.; Romero, F.; Molineri, C.; Rodríguez, J.; Rueda Martín, P.; Fernández, H.; Manzo, V.; et al. The role of macroinvertebrates for conservation of freshwater systems. Ecol. Evol. 2017, 7, 5502–5513. [Google Scholar] [CrossRef]
  3. Hansen, M.C.; Potapov, P.V.; Moore, R.; Hancher, M.; Turubanova, S.A.; Tyukavina, A.; Thau, D.; Stehman, S.V.; Goetz, S.J.; Loveland, T.R.; et al. High-resolution global maps of 21st-century forest cover change. Science 2013, 342, 850–853. [Google Scholar] [CrossRef] [PubMed]
  4. Williams, M. Deforesting the Earth: From Prehistory to Global Crisis; University of Chicago Press: Chicago, IL, USA, 2003. [Google Scholar]
  5. Radwan, T.M.; Blackburn, G.A.; Whyatt, J.D.; Atkinson, P.M. Global land cover trajectories and transitions. Sci. Rep. 2021, 11, 12814. [Google Scholar] [CrossRef] [PubMed]
  6. Miserendino, M.L.; Casaux, R.; Archangelsky, M.; Di Prinzio, C.Y.; Brand, C.; Kutschker, A.M. Assessing land-use effects on water quality, in-stream habitat, riparian ecosystems and biodiversity in Patagonian northwest streams. Sci. Total Environ. 2011, 409, 612–624. [Google Scholar] [CrossRef] [PubMed]
  7. Tilman, D.; Clark, M.; Williams, D.R.; Kimmel, K.; Polasky, S.; Packer, C. Future threats to biodiversity and pathways to their prevention. Nature 2017, 546, 73–81. [Google Scholar] [CrossRef]
  8. Arantes, C.C.; Winemiller, K.O.; Petrere, M.; Castello, L.; Hess, L.L.; Freitas, C.E. Relationships between forest cover and fish diversity in the Amazon River floodplain. J. Appl. Ecol. 2018, 55, 386–395. [Google Scholar] [CrossRef]
  9. Cheng, X.; Chen, L.; Sun, R.; Kong, P. Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China. Sci. Total Environ. 2018, 616–617, 376–385. [Google Scholar] [CrossRef]
  10. Li, Z.; García-Girón, J.; Zhang, J.; Jia, Y.; Jiang, X.; Xie, Z. Anthropogenic impacts on multiple facets of macroinvertebrate α and β diversity in a large river-floodplain ecosystem. Sci. Total Environ. 2023, 874, 162387. [Google Scholar] [CrossRef]
  11. Giri, S.; Qiu, Z. Understanding the relationship of land uses and water quality in Twenty First Century: A review. J. Environ. Manag. 2016, 173, 41–48. [Google Scholar] [CrossRef]
  12. de Mello, K.; Taniwaki, R.H.; de Paula, F.R.; Valente, R.A.; Randhir, T.O.; Macedo, D.R.; Leal, C.G.; Rodrigues, C.B.; Hughes, R.M. Multiscale land use impacts on water quality: Assessment, planning, and future perspectives in Brazil. J. Environ. Manag. 2020, 270, 110879. [Google Scholar] [CrossRef]
  13. de Mello, K.; Valente, R.A.; Randhir, T.O.; dos Santos, A.C.A.; Vettorazzi, C.A. Effects of land use and land cover on water quality of low-order streams in Southeastern Brazil: Watershed versus riparian zone. Catena 2018, 167, 130–138. [Google Scholar] [CrossRef]
  14. Schäfer, R.B.; Kühn, B.; Malaj, E.; König, A.; Gergs, R. Contribution of organic toxicants to multiple stress in river ecosystems. Freshw. Biol. 2016, 61, 2116–2128. [Google Scholar] [CrossRef]
  15. Palt, M.; Le Gall, M.; Piffady, J.; Hering, D.; Kail, J. A metric-based analysis on the effects of riparian and catchment landuse on macroinvertebrates. Sci. Total Environ. 2022, 816, 151590. [Google Scholar] [CrossRef] [PubMed]
  16. Simonetti, V.C.; Frascareli, D.; Gontijo, E.S.; Melo, D.S.; Friese, K.; Silva, D.C.; Rosa, A.H. Water quality indices as a tool for evaluating water quality and effects of land use in a tropical catchment. Int. J. River Basin Manag. 2021, 19, 157–168. [Google Scholar] [CrossRef]
  17. Wu, J.; Mao, R.; Li, M.; Xia, J.; Song, J.; Cheng, D.; Sun, H. Assessment of aquatic ecological health based on determination of biological community variability of fish and macroinvertebrates in the Weihe River Basin, China. J. Environ. Manag. 2020, 267, 110651. [Google Scholar] [CrossRef] [PubMed]
  18. Rodrigues, V.; Estrany, J.; Ranzini, M.; de Cicco, V.; Martín-Benito, J.M.T.; Hedo, J.; Lucas-Borja, M.E. Effects of land use and seasonality on stream water quality in a small tropical catchment: The headwater of Córrego Água Limpa, São Paulo (Brazil). Sci. Total Environ. 2018, 622–623, 1553–1561. [Google Scholar] [CrossRef]
  19. Reidsma, P.; Tekelenburg, T.; Van den Berg, M.; Alkemade, R. Impacts of land-use change on biodiversity: An assessment of agricultural biodiversity in the European Union. Agric. Ecosyst. Environ. 2006, 114, 86–102. [Google Scholar] [CrossRef]
  20. Wang, J.; Soininen, J.; Heino, J. Ecological indicators for aquatic biodiversity, ecosystem functions, human activities and climate change. Ecol. Indic. 2021, 132, 108250. [Google Scholar] [CrossRef]
  21. Junior, R.F.V.; Varandas, S.G.; Pacheco, F.A.; Pereira, V.R.; Santos, C.F.; Cortes, R.M.; Fernandes, L.F.S. Impacts of land use conflicts on riverine ecosystems. Land Use Policy 2015, 43, 48–62. [Google Scholar] [CrossRef]
  22. Gallacher, D. The application of rapid bioassessment techniques based on benthic macroinvertebrates in East Asian rivers (a review). Int. Ver. Für Theor. Und Angew. Limnol. Verhandlungen 2001, 27, 3503–3509. [Google Scholar] [CrossRef]
  23. Kimmel, W.; Argent, D. Community concordance between fishes and benthic macroinvertebrates among adventitious and ordinate tributaries of a major river system. Ecol. Indic. 2016, 70, 15–22. [Google Scholar] [CrossRef]
  24. El-Naggar, H.A.; Salem, E.S.S.; El-Kafrawy, S.B.; Bashar, M.A.; Shaban, W.M.; El-Gayar, E.E.; Ahmed, H.O.; Ashour, M.; Abou-Mahmoud, M.E. An integrated field data and remote sensing approach for impact assessment of human activities on epifauna macrobenthos biodiversity along the western coast of Aqaba Gulf. Ecohydrology 2022, 15, e2400. [Google Scholar] [CrossRef]
  25. Fierro, P.; Bertrán, C.; Tapia, J.; Hauenstein, E.; Peña-Cortés, F.; Vergara, C.; Cerna, C.; Vargas-Chacoff, L. Effects of local land-use on riparian vegetation, water quality, and the functional organization of macroinvertebrate assemblages. Sci. Total Environ. 2017, 609, 724–734. [Google Scholar] [CrossRef]
  26. Johnson, S.; Ringler, N. The response of fish and macroinvertebrate assemblages to multiple stressors: A comparative analysis of aquatic communities in a perturbed watershed (Onondaga Lake, NY). Ecol. Indic. 2014, 41, 198–208. [Google Scholar] [CrossRef]
  27. Li, S.; Yang, W.; Wang, L.; Chen, K.; Xu, S.; Wang, B. Influences of environmental factors on macroinvertebrate assemblages: Differences between mountain and lowland ecoregions, Wei River, China. Environ. Monit. Assess. 2018, 190, 152. [Google Scholar] [CrossRef] [PubMed]
  28. Liu, H.; Brosse, S.; Qu, X.; Xia, W.; Li, X.; Chen, Y. Land use outweighs other stressors in declining fish biodiversity in lakes of Eastern China during the 1980s–2010s. Ecol. Indic. 2023, 152, 110390. [Google Scholar] [CrossRef]
  29. Liu, Z.; Li, Z.; Castro, D.M.; Tan, X.; Jiang, X.; Meng, X.; Ge, Y.; Xie, Z. Effects of different types of land-use on taxonomic and functional diversity of benthic macroinvertebrates in a subtropical river network. Environ. Sci. Pollut. Res. 2021, 28, 44339–44353. [Google Scholar] [CrossRef]
  30. Zhang, Y.; Dudgeon, D.; Cheng, D.; Thoe, W.; Fok, L.; Wang, Z.; Lee, J.H. Impacts of land use and water quality on macroinvertebrate communities in the Pearl River drainage basin, China. Hydrobiologia 2010, 652, 71–88. [Google Scholar] [CrossRef]
  31. Lu, A.; Li, J.; Zheng, B.; Yin, X. Effect of Different Land Use Types on the Taxonomic and Functional Diversity of Macroinvertebrates in an Urban Area of Northern China. Water 2022, 14, 3793. [Google Scholar] [CrossRef]
  32. Morelli, F.; Benedetti, Y.; Perna, P.; Santolini, R. Associations among taxonomic diversity, functional diversity and evolutionary distinctiveness vary among environments. Ecol. Indic. 2018, 88, 8–16. [Google Scholar] [CrossRef]
  33. Mouillot, D.; Graham, N.A.; Villéger, S.; Mason, N.W.; Bellwood, D.R. A functional approach reveals community responses to disturbances. Trends Ecol. Evol. 2013, 28, 167–177. [Google Scholar] [CrossRef]
  34. Aguirre-Gutiérrez, J.; Malhi, Y.; Lewis, S.L.; Fauset, S.; Adu-Bredu, S.; Affum-Baffoe, K.; Baker, T.R.; Gvozdevaite, A.; Hubau, W.; Moore, S.; et al. Long-term droughts may drive drier tropical forests towards increased functional, taxonomic and phylogenetic homogeneity. Nat. Commun. 2020, 11, 3346. [Google Scholar] [CrossRef] [PubMed]
  35. Qin, H.; Wang, Y.; Zhang, F.; Chen, J.; Zhang, G.; Dong, G. Application of species, phylogenetic and functional diversity to the evaluation on the effects of ecological restoration on biodiversity. Ecol. Inform. 2016, 32, 53–62. [Google Scholar] [CrossRef]
  36. Su, P.; Wang, X.; Lin, Q.; Peng, J.; Song, J.; Fu, J.; Wang, S.; Cheng, D.; Bai, H.; Li, Q. Variability in macroinvertebrate community structure and its response to ecological factors of the Weihe River Basin, China. Ecol. Eng. 2019, 140, 105595. [Google Scholar] [CrossRef]
  37. Chang, J.; Li, Y.; Wei, J.; Wang, Y.; Guo, A. Dynamic changes of sediment load and water discharge in the Weihe River, China. Environ. Earth Sci. 2016, 75, 1042. [Google Scholar] [CrossRef]
  38. Zhao, A.; Zhu, X.; Liu, X.; Pan, Y.; Zuo, D. Impacts of land use change and climate variability on green and blue water resources in the Weihe River Basin of northwest China. Catena 2016, 137, 318–327. [Google Scholar] [CrossRef]
  39. Yang, J.; Huang, X. The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019. Earth Syst. Sci. Data 2021, 13, 3907–3925. [Google Scholar] [CrossRef]
  40. Li, F.; Altermatt, F.; Yang, J.; An, S.; Li, A.; Zhang, X. Human activities’ fingerprint on multitrophic biodiversity and ecosystem functions across a major river catchment in China. Glob. Chang. Biol. 2020, 26, 6867–6879. [Google Scholar] [CrossRef]
  41. Liu, Y.; Jiang, X.; Li, D.; Shen, J.; An, S.; Leng, X. Intensive human land uses cause the biotic homogenization of algae and change their assembly process in a major watershed of China. Sci. Total Environ. 2023, 871, 162115. [Google Scholar] [CrossRef]
  42. Yin, X.-W.; Xu, Z.-X.; Gao, X.; Bai, H.-F.; Wu, W.; Song, J.-X. Macrobenthos community structure and its relationships with environmental factors in Weihe River basin, Northwest China. Ying Yong Sheng Tai Xue Bao = J. Appl. Ecol. 2013, 24, 218–226. [Google Scholar]
  43. Chen, D.; Zhang, G. Fauna Sinica Phylum Mollusca Class Gastropoda; Science Press: Beijing, China, 2002. [Google Scholar]
  44. Merritt, R.W.; Cummins, K.W. An Introduction to the Aquatic Insects of North America; Kendall Hunt: Dubuque, IA, USA, 1996. [Google Scholar] [CrossRef]
  45. Thorp, J.H.; Covich, A.P. Ecology and Classification of North American Freshwater Invertebrates; Academic Press: Cambridge, MA, USA, 2009. [Google Scholar]
  46. Wang, Z. Fauna sinica Phylum Mollusca Class Bivalvia; Science Press: Beijing, China, 2002. [Google Scholar]
  47. Yang, T. Fauna Sinica Annelida Hiruclinea; Science Press: Beijing, China, 2002. [Google Scholar]
  48. China SE Monitoring and Determination Methods for Water and Wastewater; China Environmental Science Press: Beijing, China, 2002.
  49. Poff, N.L.; Olden, J.D.; Vieira, N.K.; Finn, D.S.; Simmons, M.P.; Kondratieff, B.C. Functional trait niches of North American lotic insects: Traits-based ecological applications in light of phylogenetic relationships. J. N. Am. Benthol. Soc. 2006, 25, 730–755. [Google Scholar] [CrossRef]
  50. Zheng, B.; Yin, X. Assembly mechanism of macroinvertebrate metacommunities and ecological factors of multiple aspects of beta diversity in a boreal river basin, China. Front. Ecol. Evol. 2023, 11, 1131403. [Google Scholar] [CrossRef]
  51. Ding, N.; Yang, W.; Zhou, Y.; González-Bergonzoni, I.; Zhang, J.; Chen, K.; Vidal, N.; Jeppesen, E.; Liu, Z.; Wang, B. Different responses of functional traits and diversity of stream macroinvertebrates to environmental and spatial factors in the Xishuangbanna watershed of the upper Mekong River Basin, China. Sci. Total Environ. 2017, 574, 288–299. [Google Scholar] [CrossRef]
  52. Li, Z.; Liu, Z.; Heino, J.; Jiang, X.; Wang, J.; Tang, T.; Xie, Z. Discriminating the effects of local stressors from climatic factors and dispersal processes on multiple biodiversity dimensions of macroinvertebrate communities across subtropical drainage basins. Sci. Total Environ. 2020, 711, 134750. [Google Scholar] [CrossRef] [PubMed]
  53. Li, Z.; Wang, J.; Liu, Z.; Meng, X.; Heino, J.; Jiang, X.; Xiong, X.; Jiang, X.; Xie, Z. Different responses of taxonomic and functional structures of stream macroinvertebrate communities to local stressors and regional factors in a subtropical biodiversity hotspot. Sci. Total Environ. 2019, 655, 1288–1300. [Google Scholar] [CrossRef]
  54. Šmilauer, P.; Lepš, J. Multivariate Analysis of Ecological Data Using CANOCO 5; Cambridge University Press: Cambridge, UK, 2014. [Google Scholar]
  55. Khudhair, N.; Yan, C.; Liu, M.; Yu, H. Effects of habitat types on macroinvertebrates assemblages structure: Case study of sun island bund wetland. BioMed Res. Int. 2019, 2019, 2650678. [Google Scholar] [CrossRef] [PubMed]
  56. Oksanen, J.; Blanchet, F.G.; Kindt, R.; Legendre, P.; Minchin, P.R.; O’Hara, R.B.; Simpson, G.L.; Sólymos, P.; Stevens, M.H.H.; Wagner, H. Vegan: Community Ecology Package; Academic Press: Oulu, Finland, 2012; Available online: http://CRAN.R-project.org/package=vegan (accessed on 25 June 2024).
  57. Laliberté, E.; Legendre, P.; Shipley, B.; Laliberté, M.E. Package ‘fd’, Measuring Functional Diversity from Multiple Traits, and Other Tools for Functional Ecology; Academic Press: Québec, QC, Canada, 2014. [Google Scholar]
  58. Legras, G.; Loiseau, N.; Gaertner, J.-C. Functional richness: Overview of indices and underlying concepts. Acta Oecologica 2018, 87, 34–44. [Google Scholar] [CrossRef]
  59. Mason, N.W.; Mouillot, D.; Lee, W.G.; Wilson, J.B. Functional richness, functional evenness and functional divergence: The primary components of functional diversity. Oikos 2005, 111, 112–118. [Google Scholar] [CrossRef]
  60. Mouchet, M.A.; Villéger, S.; Mason, N.W.; Mouillot, D. Functional diversity measures: An overview of their redundancy and their ability to discriminate community assembly rules. Funct. Ecol. 2010, 24, 867–876. [Google Scholar] [CrossRef]
  61. Pavoine, S.; Dolédec, S. The apportionment of quadratic entropy: A useful alternative for partitioning diversity in ecological data. Environ. Ecol. Stat. 2005, 12, 125–138. [Google Scholar] [CrossRef]
  62. Liu, Y.; Zhang, M.; Peng, W.; Qu, X.; Zhang, Y.; Du, L.; Wu, N. Phylogenetic and functional diversity could be better indicators of macroinvertebrate community stability. Ecol. Indic. 2021, 129, 107892. [Google Scholar] [CrossRef]
  63. Wickham, H.; Chang, W.; Wickham, M.H. Package ‘ggplot2’. Create Elegant Data Visualisations Using the Grammar of Graphics; Academic Press: Houston, TX, USA, 2016; Volume 1, pp. 1–189. [Google Scholar]
  64. Liu, L.; Xu, Z.; Yang, F.; Yin, X.; Wu, W.; Li, J. Comparison of Fish, Macroinvertebrates and Diatom Communities in Response to Environmental Variation in the Wei River Basin, China. Water 2020, 12, 3422. [Google Scholar] [CrossRef]
  65. Xu, J.; Jin, G.; Tang, H.; Mo, Y.; Wang, Y.-G.; Li, L. Response of water quality to land use and sewage outfalls in different seasons. Sci. Total Environ. 2019, 696, 134014. [Google Scholar] [CrossRef]
  66. Dębska, K.; Rutkowska, B.; Szulc, W.; Gozdowski, D. Changes in Selected Water Quality Parameters in the Utrata River as a Function of Catchment Area Land Use. Water 2021, 13, 2989. [Google Scholar] [CrossRef]
  67. Martien, R.F.; Benke, A.C. Distribution and production of two crustaceans in a wetland pond. Am. Midl. Nat. 1977, 98, 162–175. [Google Scholar] [CrossRef]
  68. Gebremicael, T.; Mohamed, Y.; Van der Zaag, P. Attributing the hydrological impact of different land use types and their long-term dynamics through combining parsimonious hydrological modelling, alteration analysis and PLSR analysis. Sci. Total Environ. 2019, 660, 1155–1167. [Google Scholar] [CrossRef]
  69. Zhang, Y.; Chao, Y.; Fan, R.; Ren, F.; Qi, B.; Ji, K.; Xu, B. Spatial-temporal trends of rainfall erosivity and its implication for sustainable agriculture in the Wei River Basin of China. Agric. Water Manag. 2021, 245, 106557. [Google Scholar] [CrossRef]
  70. Ding, J.; Jiang, Y.; Fu, L.; Liu, Q.; Peng, Q.; Kang, M. Impacts of land use on surface water quality in a subtropical River Basin: A case study of the Dongjiang River Basin, Southeastern China. Water 2015, 7, 4427–4445. [Google Scholar] [CrossRef]
  71. Zhang, Y.; Cheng, L.; Tolonen, K.E.; Yin, H.; Gao, J.; Zhang, Z.; Li, K.; Cai, Y. Substrate degradation and nutrient enrichment structuring macroinvertebrate assemblages in agriculturally dominated Lake Chaohu Basins, China. Sci. Total Environ. 2018, 627, 57–66. [Google Scholar] [CrossRef] [PubMed]
  72. Du, X.; Song, D.; Ming, K.; Jin, X.; Wang, H.; Wang, L.; Liu, H.; Zhao, C.; Huo, T. Response of macroinvertebrate communities to land use and water quality in Wudalianchi Lake. Ecol. Evol. 2021, 11, 1368–1377. [Google Scholar] [CrossRef]
  73. Kim, D.-K.; Jo, H.; Park, K.; Kwak, I.-S. Assessing spatial distribution of benthic macroinvertebrate communities associated with surrounding land cover and water quality. Appl. Sci. 2019, 9, 5162. [Google Scholar] [CrossRef]
  74. Abubakr, A.; Gojar, A.A.; Balkhi, M.; Malik, R. Macro-invertebrates (Annelida; Oligochaeta) as bio-Indicator of water quality under temperate climatic conditions. Int. J. Pure Appl. Biosci. 2018, 6, 726–737. [Google Scholar] [CrossRef]
  75. Mackintosh, T.J.; Davis, J.A.; Thompson, R.M. The influence of urbanisation on macroinvertebrate biodiversity in constructed stormwater wetlands. Sci. Total Environ. 2015, 536, 527–537. [Google Scholar] [CrossRef] [PubMed]
  76. Ellis, E.C.; Gauthier, N.; Klein Goldewijk, K.; Bliege Bird, R.; Boivin, N.; Díaz, S.; Fuller, D.Q.; Gill, J.L.; Kaplan, J.O.; Kingston, N.; et al. People have shaped most of terrestrial nature for at least 12,000 years. Proc. Natl. Acad. Sci. USA 2021, 118, e2023483118. [Google Scholar] [CrossRef] [PubMed]
  77. Katsiapi, M.; Mazaris, A.D.; Charalampous, E.; Moustaka-Gouni, M. Watershed land use types as drivers of freshwater phytoplankton structure. In Phytoplankton Responses to Human Impacts at Different Scales; Springer: Dordrecht, The Netherlands, 2012; pp. 121–131. [Google Scholar] [CrossRef]
  78. Davison, C.W.; Rahbek, C.; Morueta-Holme, N. Land-use change and biodiversity: Challenges for assembling evidence on the greatest threat to nature. Glob. Chang. Biol. 2021, 27, 5414–5429. [Google Scholar] [CrossRef]
  79. Rurangwa, M.L.; Aguirre-Gutiérrez, J.; Matthews, T.J.; Niyigaba, P.; Wayman, J.P.; Tobias, J.A.; Whittaker, R.J. Effects of land-use change on avian taxonomic, functional and phylogenetic diversity in a tropical montane rainforest. Divers. Distrib. 2021, 27, 1732–1746. [Google Scholar] [CrossRef]
  80. Paz, L.; Rodriguez, M.; Gullo, B.; Capítulo, A.R. Impacts of urban and industrial pollution on functional traits of benthic macroinvertebrates: Are some traits advantageous for survival? Sci. Total Environ. 2022, 807, 150650. [Google Scholar] [CrossRef] [PubMed]
  81. de Castro, D.M.P.; Dolédec, S.; Callisto, M. Land cover disturbance homogenizes aquatic insect functional structure in neotropical savanna streams. Ecol. Indic. 2018, 84, 573–582. [Google Scholar] [CrossRef]
  82. Le Provost, G.; Thiele, J.; Westphal, C.; Penone, C.; Allan, E.; Neyret, M.; Van Der Plas, F.; Ayasse, M.; Bardgett, R.D.; Birkhofer, K.; et al. Contrasting responses of above-and belowground diversity to multiple components of land-use intensity. Nat. Commun. 2021, 12, 3918. [Google Scholar] [CrossRef]
  83. Yadamsuren, O.; Morse, J.C.; Hayford, B.; Gelhaus, J.K.; Adler, P.H. Macroinvertebrate community responses to land use: A trait-based approach for freshwater biomonitoring in Mongolia. Hydrobiologia 2020, 847, 1887–1902. [Google Scholar] [CrossRef]
  84. Zintzen, V.; Anderson, M.J.; Roberts, C.D.; Diebel, C.E. Increasing variation in taxonomic distinctness reveals clusters of specialists in the deep sea. Ecography 2011, 34, 306–317. [Google Scholar] [CrossRef]
  85. Ge, Y.; Liu, Z.; García-Girón, J.; Chen, X.; Yan, Y.; Li, Z.; Xie, Z. Human-induced loss of functional and phylogenetic diversity is mediated by concomitant deterministic processes in subtropical aquatic insect communities. Ecol. Indic. 2022, 136, 108600. [Google Scholar] [CrossRef]
  86. Marino, A.; Bona, F.; Fenoglio, S.; Bo, T. Functional Traits Drive the Changes in Diversity and Composition of Benthic Invertebrate Communities in Response to Hydrological Regulation. Water 2024, 16, 989. [Google Scholar] [CrossRef]
  87. Rolls, R.J.; Heino, J.; Ryder, D.S.; Chessman, B.C.; Growns, I.O.; Thompson, R.M.; Gido, K.B. Scaling biodiversity responses to hydrological regimes. Biol. Rev. 2018, 93, 971–995. [Google Scholar] [CrossRef]
  88. Ashton, M.J.; Morgan, R.P.; Stranko, S. Relations between macroinvertebrates, nutrients, and water quality criteria in wadeable streams of Maryland, USA. Environ. Monit. Assess. 2014, 186, 1167–1182. [Google Scholar] [CrossRef]
  89. Mouton, T.L.; Leprieur, F.; Floury, M.; Stephenson, F.; Verburg, P.; Tonkin, J.D. Climate and land-use driven reorganisation of structure and function in river macroinvertebrate communities. Ecography 2022, 2022, e06148. [Google Scholar] [CrossRef]
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Figure 1. The spatial distribution of sampling sites in the study region. (The green and red represent low and high human land-use intensity, respectively. The red area on the map of China at the top left represents the study region).
Figure 1. The spatial distribution of sampling sites in the study region. (The green and red represent low and high human land-use intensity, respectively. The red area on the map of China at the top left represents the study region).
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Figure 2. Principal component analysis of the coverage of land-use area in autumn (A) and spring (B). The green points represent the sample sites. The blue arrows represent the direction of the increases for different land−use coverage.
Figure 2. Principal component analysis of the coverage of land-use area in autumn (A) and spring (B). The green points represent the sample sites. The blue arrows represent the direction of the increases for different land−use coverage.
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Figure 3. Boxplots comparing 5 types of land-use coverage (%) among the low- and high-intensity human land uses, including cropland, forest, grassland, water, and build-up area in autumn (A) and spring (B). (The line in the middle of the box represents the median of the data, and the top and bottom of the box are the upper and lower quartiles of the data, respectively. The upper and lower edges represent the maximum and minimum values of the set of data. Points above the maximum and below the minimum are outliers in the data. Asterisks denote significant differences: ** p < 0.01; *** p < 0.001. ns indicates that there is no significant difference).
Figure 3. Boxplots comparing 5 types of land-use coverage (%) among the low- and high-intensity human land uses, including cropland, forest, grassland, water, and build-up area in autumn (A) and spring (B). (The line in the middle of the box represents the median of the data, and the top and bottom of the box are the upper and lower quartiles of the data, respectively. The upper and lower edges represent the maximum and minimum values of the set of data. Points above the maximum and below the minimum are outliers in the data. Asterisks denote significant differences: ** p < 0.01; *** p < 0.001. ns indicates that there is no significant difference).
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Figure 4. Boxplot comparison of environmental factors of low-intensity and high-intensity human land use ((A) DO, (B) TN, (C) River Width, (D) Depth, and (E) Flow). Mann–Whitney U test and independent sample t-test were used for pairwise comparison. (The line in the middle of the box represents the median of the data, and the top and bottom of the box are the upper and lower quartiles of the data, respectively. The upper and lower edges represent the maximum and minimum values of the set of data. Points above the maximum and below the minimum are outliers in the data. Asterisks denote significant differences: * p ≤ 0.05; ** p < 0.01. ns indicates that there is no significant difference).
Figure 4. Boxplot comparison of environmental factors of low-intensity and high-intensity human land use ((A) DO, (B) TN, (C) River Width, (D) Depth, and (E) Flow). Mann–Whitney U test and independent sample t-test were used for pairwise comparison. (The line in the middle of the box represents the median of the data, and the top and bottom of the box are the upper and lower quartiles of the data, respectively. The upper and lower edges represent the maximum and minimum values of the set of data. Points above the maximum and below the minimum are outliers in the data. Asterisks denote significant differences: * p ≤ 0.05; ** p < 0.01. ns indicates that there is no significant difference).
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Figure 5. Histogram of differences in community composition (A,C), community composition (A), density (B) and relative abundance (C) of macroinvertebrates under different human land-use intensities in Weihe River Basin in spring and autumn.
Figure 5. Histogram of differences in community composition (A,C), community composition (A), density (B) and relative abundance (C) of macroinvertebrates under different human land-use intensities in Weihe River Basin in spring and autumn.
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Figure 6. Boxplot comparison of low-intensity and high-intensity human land-use taxonomic α diversity ((A) species richness, (B) Shannon–Wiener diversity index, (C) Pielou evenness index, and (D) Simpson diversity index). Analyses were performed using Mann–Whitney U tests and independent sample t-tests for pairwise comparisons. (Asterisks denote significant differences: * p ≤ 0.05; ** p < 0.01. ns indicates that there is no significant difference).
Figure 6. Boxplot comparison of low-intensity and high-intensity human land-use taxonomic α diversity ((A) species richness, (B) Shannon–Wiener diversity index, (C) Pielou evenness index, and (D) Simpson diversity index). Analyses were performed using Mann–Whitney U tests and independent sample t-tests for pairwise comparisons. (Asterisks denote significant differences: * p ≤ 0.05; ** p < 0.01. ns indicates that there is no significant difference).
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Figure 7. The proportion of functional groups of macroinvertebrate community among different human land-use intensities in the Wei River Basin in autumn and spring.
Figure 7. The proportion of functional groups of macroinvertebrate community among different human land-use intensities in the Wei River Basin in autumn and spring.
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Figure 8. Boxplot comparison of low-intensity and high-intensity human land-use functional α diversity ((A) FRic, functional richness; (B) FDis, functional dispersion index; and (C) RaoQ, Rao’s quadratic entropy index). Mann–Whitney U test and independent sample t-test were used for pairwise comparison. (Asterisks denote significant differences: * p ≤ 0.05; ** p < 0.01; *** p <0.001. ns indicates that there is no significant difference).
Figure 8. Boxplot comparison of low-intensity and high-intensity human land-use functional α diversity ((A) FRic, functional richness; (B) FDis, functional dispersion index; and (C) RaoQ, Rao’s quadratic entropy index). Mann–Whitney U test and independent sample t-test were used for pairwise comparison. (Asterisks denote significant differences: * p ≤ 0.05; ** p < 0.01; *** p <0.001. ns indicates that there is no significant difference).
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Figure 9. Boxplot comparison of low-intensity and high-intensity human land-use phylogenetic α diversity ((A) Δ: taxonomic diversity index; (B) Δ*: taxonomic distinctness index; (C) Λ+: variation in taxonomic distinctness index; and (D) Δ+: average taxonomic distinctness index). Mann–Whitney U test and independent sample t-test were used for pairwise comparison. (Asterisks denote significant differences: * p ≤ 0.05. ns indicates that there is no significant difference).
Figure 9. Boxplot comparison of low-intensity and high-intensity human land-use phylogenetic α diversity ((A) Δ: taxonomic diversity index; (B) Δ*: taxonomic distinctness index; (C) Λ+: variation in taxonomic distinctness index; and (D) Δ+: average taxonomic distinctness index). Mann–Whitney U test and independent sample t-test were used for pairwise comparison. (Asterisks denote significant differences: * p ≤ 0.05. ns indicates that there is no significant difference).
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Figure 10. db-RDA and PERMANOVA analyses of land-use intensity and environmental factors and macroinvertebrate diversity in autumn (A–C) and spring (D–F).
Figure 10. db-RDA and PERMANOVA analyses of land-use intensity and environmental factors and macroinvertebrate diversity in autumn (A–C) and spring (D–F).
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Table 1. Classification of 32 characteristics of macroinvertebrate community species in the Weihe River Basin, which were divided into 4 characteristic groups. The letters in each code represent the feature, and the number represents the feature state.
Table 1. Classification of 32 characteristics of macroinvertebrate community species in the Weihe River Basin, which were divided into 4 characteristic groups. The letters in each code represent the feature, and the number represents the feature state.
Trait Group TraitTrait State (Modality)Code
Life history
VoltinismSemivoltine (<1 generation/y)Volt1
Univoltine (1 generation/y)Volt2
Bi- or multivoltine (>1 generation/y)Volt3
Mobility
Female dispersalLow (<1 km flight before laying eggs)Disp1
High (>1 km flight before laying eggs)Disp2
NoDisp3
Occurrence in driftRare (catastrophic only)Drft1
Common (typically observed)Drft2
Abundant (dominant in drift samples)Drft3
Morphology
RespirationTegumentResp1
GillsResp2
Plastron, spiracle (aerial)Resp3
Size at maturitySmall (<9 mm)Size1
Medium (9–16 mm)Size2
Large (>16 mm)Size3
Ecology
RheophilyDepositional onlyRheo1
Depositional and erosionalRheo2
ErosionalRheo3
Thermal preferenceCold stenothermal or cool eurythermalTher1
Cool/warm eurythermalTher2
Warm eurythermalTher3
HabitBurrowHabi1
ClimbHabi2
SprawlHabi3
ClingHabi4
SwimHabi5
SkateHabi6
Trophic habitCollector-gathererTrop1
Collector-filtererTrop2
Herbivore (scraper, piercer, and shedder)Trop3
Predator (piercer and engulfer)Trop4
Shredder (detritivore)Trop5
Table 2. Dominant species within macroinvertebrate communities across various intensities of human land use in the Weihe River Basin during autumn and spring.
Table 2. Dominant species within macroinvertebrate communities across various intensities of human land use in the Weihe River Basin during autumn and spring.
AutumnSpring
PhylumClassOrderFamilyGenusLowHighLowHigh
ArthropodaInsectaEphemeropteraBaetidaeBaetis0.1410.045--
ArthropodaInsectaTrichopteraHydropsychidaeHydropsyche0.0510.0990.041-
ArthropodaInsectaDipteraChironomidaeOrthocladius0.2690.047--
ArthropodaInsectaDipteraChironomidaeCricotopus--0.3050.05
ArthropodaInsectaDipteraChironomidaeSympotthastia--0.042-
AnnelidaOligocheataTubificidaTubificidaeLimnodrilus0.1290.208-0.124
AnnelidaOligocheataTubificidaTubificidaeBranchiura-0.024--
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Ma, J.; Yin, X.; Liu, G.; Song, J. Intensification of Human Land Use Decreases Taxonomic, Functional, and Phylogenetic Diversity of Macroinvertebrate Community in Weihe River Basin, China. Diversity 2024, 16, 513. https://doi.org/10.3390/d16090513

AMA Style

Ma J, Yin X, Liu G, Song J. Intensification of Human Land Use Decreases Taxonomic, Functional, and Phylogenetic Diversity of Macroinvertebrate Community in Weihe River Basin, China. Diversity. 2024; 16(9):513. https://doi.org/10.3390/d16090513

Chicago/Turabian Style

Ma, Jixin, Xuwang Yin, Gang Liu, and Jinxi Song. 2024. "Intensification of Human Land Use Decreases Taxonomic, Functional, and Phylogenetic Diversity of Macroinvertebrate Community in Weihe River Basin, China" Diversity 16, no. 9: 513. https://doi.org/10.3390/d16090513

APA Style

Ma, J., Yin, X., Liu, G., & Song, J. (2024). Intensification of Human Land Use Decreases Taxonomic, Functional, and Phylogenetic Diversity of Macroinvertebrate Community in Weihe River Basin, China. Diversity, 16(9), 513. https://doi.org/10.3390/d16090513

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