Content area
The Shiquan River National Wetland Park in Tibet is an integrated high-elevation wetland ecosystem. This wetland park also serves as a demonstration site for international river conservation and the ‘conservation–utilization–sustainable enhancement’ of wetland resources in alpine desert zones. This study supplements the research on bird community structure and ecological function to fill the gap in basic data on birds in the Shiquan River National Wetland Park. From May 2023 to October 2024, a sampling point method was used to conduct four systematic surveys during the breeding and non-breeding periods of birds in four habitats—grass land, marsh land, bare land, and water bodies—in the Shiquan River National Wetland Park to explore the effects of different habitat types on bird communities from the perspective of species and functional diversity. A total of 56 bird species, representing 23 families and 11 orders, were documented in this survey. Species diversity was highest in the marsh habitat during the breeding season, followed sequentially by grassland, bare land, and water bodies, with consistent results in the non-breeding period. The functional richness (FRic) results revealed a pattern of marsh land > grass land > bare land > water bodies, indicating that birds utilized the ecological space within the marsh habitat to the greatest extent. The functional differentiation (FDiv) results followed a pattern of bare land > water bodies > grass land > marsh land, suggesting stronger niche complementarity and weaker competition in bare ground habitats. Finally, the functional dispersion (FDis) results demonstrated a pattern of grass land > marsh land > bare land > water bodies, indicating a greater number of species with similar functional traits in grass habitats. This study addresses the research gap concerning bird communities in the Shiquan River National Wetland Park through the lens of both species and functional diversity, thereby providing a scientific foundation and critical support for the conservation of avian biodiversity in the Shiquan River Basin and high-elevation regions.
Full text
1. Introduction
Wetlands, as ‘kidneys of the earth’, perform unique roles in water purification and flood and drought mitigation, and provide essential habitats for diverse plant and animal species [1,2]. High-elevation wetlands are one of the most important productive mountain ecosystems worldwide, being hotspots of biodiversity and relevant for the regional water cycle, and provide fundamental ecosystem benefits such as freshwater for many human settlements and livestock, and refuge for plants and animals [3]. The unique geographical and climatic conditions of the high-elevation wetlands have given rise to diverse and distinctive ecosystem types, as well as rare species of flora and fauna, serving as both a critical area for global biodiversity conservation and a natural germplasm repository for organisms of the Plateau [4]. However, the ecosystem of the high-elevation wetlands is extremely fragile and highly sensitive to global climate change and human activities [5], attracting global concern for its ecological status [6]. Birds maintain close connections with human production and daily life, serving as a critical indicator for assessing the health and integrity of regional ecosystems and natural environments [7]. Environmental changes have a direct effect on bird survival and population dynamics [8]. Consequently, bird species diversity and population abundance are widely regarded as biological indicators of wetland environmental changes [9].
Furthermore, functional diversity serves as a critical driver of ecosystem services and resilience, having emerged as a prominent research focus in contemporary ecological studies [7,10]. Through complementary resource utilization connecting species to ecosystem functions, functional diversity can serve as a tool to solve many important ecological problems [11]. It is commonly represented by an index that considers several trait measures simultaneously, expressing how species are distributed in a multidimensional functional space, where the number of axes is determined by the number of traits, and the position of species is determined by their trait values [12,13]. Simultaneously, the position and amount of functional space occupied by species are associated with their resource use in the environment [14]. Furthermore, functional diversity metrics can outperform species richness for predicting biomass production [15]. Therefore, with its own functional identity and ecological importance, functional diversity provides a more direct link to ecosystem functioning than the number of species [16,17,18].
In this study, the Shiquan River National Wetland Park in Tibet (hereinafter referred to as the Shiquan River) was selected as the study area. It is classified as an integrated wetland ecosystem of plateau rivers, lakes, marshes, and reservoirs in an alpine desert region. It also serves as a demonstration site for international river conservation and the ‘conservation–utilization–sustainable enhancement’ of wetland resources in alpine desert zones. The Shiquan River, as a critical ecological security barrier in China, is not only a microcosm of the structure and functions of high-elevation wetland ecosystems but is also a representative high-elevation wetland ecosystems. Existing research on functional diversity in the high-elevation wetlands has predominantly focused on soil microorganisms [19], gut microbiota [20], and alpine meadows [21], while studies addressing avian functional diversity remain conspicuously absent. While ornithological investigations have been conducted in adjacent regions, such as Ngari Prefecture and Serling Tso National Nature Reserve [22], there is a lack of fundamental research on the avian diversity, community architecture, and ecological functionality of the Shiquan River—characterized as a plateau cryo-arid desert wetland complex—indicating an urgent need for systematic investigations to establish baseline datasets.
Therefore, this study aims to fill in the gaps in basic data on birds in the Shiquan River while complementing the study of bird community structure and ecological function to reflect the actual situation for birds in the plateau alpine ecosystem. Improving the species and functional diversity of bird communities in different habitats in the Shiquan River National Park provides a scientific basis for protecting birds and their diversity in the Shiquan River Basin and other high-elevation areas and maintaining the stability of the plateau alpine ecosystem.
2. Materials and Methods
2.1. Overview of the Study Area
The Shiquan River Wetland Park is situated in Ngari Prefecture, Tibet Autonomous Region, spanning administrative jurisdictions including Gar County, Ritu County, and Geji County. The area spans a total of 12,666.8 hm2, with geographical coordinates ranging from 80°07′43″ E to 80°56′07″ E in longitude and 32°12′32″ N to 32°33′30″ N in latitude. With an average elevation exceeding 4500 m, the region is characterized by thin air, prolonged sunshine duration, intense solar radiation, delayed spring warming, brief summers, rapid autumn cooling, and prolonged winters. This results in extended cold periods, short temperate intervals, indistinct seasonal differentiation, and significant diurnal temperature variations.
2.2. Survey Methods
From May 2023 to October 2024, systematic avian surveys were conducted using point-count methods across four distinct habitats—grass land (3330.4 hm2), marsh land (3160.9 hm2), bare land (3564.4 hm2), and water bodies (2611.5 hm2)—during both breeding (May) and non-breeding (October) seasons for four survey sessions in total. Sampling points were established using the fixed-radius method [23], with a total of 35 points distributed across the four habitat types: 10 in grass lang, 9 in marsh land, 9 in water bodies, and 7 in bare land; each sampling point was surveyed 4 times, totaling 140 times. A sampling point had a 50 m radius with a minimum spacing of 500 m between points. Each point was observed for 15–20 min, during which data on location, elevation, and habitat characteristics were systematically recorded (Figure 1). The surveys were conducted within 3 h after sunrise, avoiding midday periods and inclement weather conditions, when avian activity levels are typically reduced. During the surveys, observations were conducted using 8 × 42 Asika binoculars and DSLR cameras to identify, photograph, and record avian species and their abundances. Bird species were identified according to the guidelines outlined in A Field Guide to the Birds of China [24]. The taxonomic classification, residency status, and identification of endemic bird species in China were determined in accordance with the Catalogue of the Classification and Distribution of Birds in China [25]. The protection status of species was strictly determined in accordance with the List of National Key Protected Wild Animals (2021 Edition) jointly issued by the China Forestry and Grassland Administration and the Ministry of Agriculture and Rural Affairs [26]. The threat status of species was assessed according to the China Biodiversity Red List: Volume II Birds [27] and aligned with the IUCN Red List of Threatened Species [28]. The zoogeographical division was determined according to the principles outlined in Zoogeography of China [29].
2.3. Data Analysis
In this study, standard methods were used to test the adequacy of the samples, and sparse extrapolation curves of bird species richness were constructed based on the results of four observations to test the adequacy of the bird surveys and ensure the feasibility of subsequent operational analyses [30]. Species diversity across the different habitats was assessed using the Shannon–Wiener, Simpson [31], and Pielou indices [32], which have been adopted in many ecological studies. Functional trait data for birds were obtained from the Dataset of Life History and Ecological Characteristics of Chinese Birds [33]. Morphological data (including body length, body mass, bill length, wing length, tail length, and tarsus length), feeding habits, nest type, nest location, and habitat type (grass, marshes, bare grounds, and water areas) were selected for analysis. Among these, morphological data were treated as continuous variables, and dietary characteristics, nest type, nest location, and habitat type were analyzed as categorical variables [34]. Functional diversity indices, including functional richness (FRic) [13], functional divergence (FDiv) [35], and functional dispersion (FDis) [36], were calculated to assess avian community structure. FRic measures the size of the functional space occupied by an organism in a community. FDiv measures the degree of niche differentiation and resource competition among the organisms in a community. FDis measures the number of species with the same functional traits in a community.
All calculations and statistical analyses were conducted using R version 4.3.0 [20]. A sparse extrapolation curve analysis of bird diversity was performed using the R language iNEXT package [30]. The diversity function in the Vegan package was used to calculate the bird species diversity in different habitats [37]. Functional diversity across different habitats was calculated using the pd function in the Picante package [35]. The relationship between species diversity and functional diversity indices was analyzed using Pearson’s linear correlation [13].
3. Results
3.1. Sample Adequacy Results
The estimated species richness of birds in the Shiquan River was calculated using the sample size sparsification and extrapolation (R/E) method based on the four observations, and interpolation/extrapolation curves of species richness with the number of surveyed birds were drawn. The results showed that the sample coverage of each survey was above 0.97, indicating that the sampling was relatively sufficient (Figure 2). In addition, the species accumulation curve (Figure 2) demonstrates an initial rapid increase in avian species richness, followed by a gradual leveling off and, finally, a plateau, indicating a sufficient sampling effort.
3.2. Species Composition
Field surveys resulted in a total of 9887 bird observations (5815 and 4072 during breeding and non-breeding seasons, respectively), belonging to 11 orders, 23 families, and 56 species (Appendix A). The majority of birds were Passeriformes, with 29 species in 10 families, accounting for 51.79% of the total number of birds, followed by Charadriiformes, with 4 families and 7 species, accounting for 12.50% of the total; Accipitriformes, with 5 species in 1 family, accounting for 8.93% of the total; Anseriformes, with 1 family and 4 species, accounting for 7.14% of the total; and Galliformes, Podicipediformes, Columbiformes, and Falconiformes, each having 1 family and 2 species and accounting for 3.57% of the total. The remaining birds were Cuculiformes, Gruiformes, and Bucerotiformes, with each represented by only one family and one species and accounting for 1.79% of the total. Four species of wild birds—Grus nigricollis, Gypaetus barbatus, Aquila nipalensis, and Falco cherrug—were listed as Level I key protected wild birds in China. Five species of wild birds—Ibidorhyncha struthersii, Gyps himalayensis, Milvus migrans, Buteo hemilasius, and Falco tinnunculus—were Level II key protected wild birds in China.
According to the China Biodiversity Red List, eight species were identified as threatened, while the IUCN Red List classified five species as threatened. The analysis of residence types showed 33 species of resident birds, which were the main bird species in the Shiquan River, accounting for 58.93% of the total. There were 16 species of summer migratory birds, accounting for 28.57% of the total; 4 species of traveling birds, accounting for 7.14% of the total; and 3 species of winter migratory birds, accounting for 5.35% of the total. From the perspective of faunal dependency, there were 52 widespread species, accounting for 92.86% of the total number of birds. The Oriental and Palaearctic realms were each represented by two species, accounting for 3.57% of the total.
3.3. Diversity-Analysis Results
3.3.1. Diversity of Species
Across the different habitats, avian species richness exhibited the following pattern: marsh land (44 species) > grass land (38 species) > bare land (31 species) > water bodies (18 species). Across different seasons, the Shannon–Wiener index (H) and Simpson index (D) showed minimal variation between breeding and non-breeding seasons, with an overall trend of marsh land > grass land > bare land > water bodies. The Pielou index (J) exhibited a trend of bare land > marsh land > grass land > water bodies during the breeding season, shifting to marsh land > grass land > bare land > water bodies in the non-breeding season (Figure 3).
3.3.2. Functional Diversity
The FRic results revealed a pattern of bare marsh land > grass land > bare land > water bodies, indicating that the highest ecological space utilization was in marsh habitats. The FDiv results followed a pattern of bare land > water bodies > grass land > marsh land, suggesting stronger niche complementarity and weaker competition in bare ground habitats. Finally, the FDis results demonstrated a pattern of grass land > marsh land > bare land > water bodies, indicating a greater number of species with similar functional traits in grassland habitats (Figure 3).
3.4. Correlation Analysis
Correlation analysis revealed significant positive relationships between FDiv and the Simpson index (R = 0.49, p < 0.05); FRic and the Shannon–Wiener index (R = 0.98, p < 0.001); FDis and the Shannon–Wiener index (R = 0.72, p < 0.001); and FDis and FRic (R = 0.69, p < 0.001). Significant negative correlations were observed between FDis and the Simpson index (R = −0.52, p < 0.05); the Shannon–Wiener and Simpson indices (R = −0.64, p < 0.01); Simpson and FRic (R = −0.68, p < 0.01); FDis and FDiv (R = −0.59, p < 0.01); FDiv and the Shannon–Wiener index (R = −0.84, p < 0.001); and FDiv and FRic (R = −0.64, p < 0.001) (Figure 4).
4. Discussion
4.1. Changes in Bird Community Composition
A total of 56 bird species were recorded in this survey, with Passeriformes being the most abundant group. This finding aligns with results from the Medika Wetland National Nature Reserve, likely due to the relatively high evolutionary status of Passeriformes within the avian community, their greater diversity and abundance, and their adaptability to various complex ecological environments [38]. In terms of zoogeographical composition, the Shiquan River is located in the Qiangtang Plateau subregion of the Qinghai–Tibet region within the Central Asian subkingdom, and its position in the transition zone between the Palearctic and Oriental realms results in widespread bird species dominating the avian community [29]. Among the four habitat types surveyed, marshes supported the most bird species, while water bodies had the fewest. This pattern may be attributed to the presence of dormant herbaceous plants, plant seeds, fungi, and livestock dung in marsh meadows, which provide abundant food resources for birds in marsh habitats. In addition, the small shrubs observed around nine sampling points provide excellent shelter for birds in marsh habitats. Meanwhile, abundant aquatic plants and invertebrates in water body environments serve as crucial food resources for waterbirds [39,40]. However, the water body habitats in the Shiquan River support the fewest bird species, likely due to its geographical location. Additionally, most water body birds are Anseriformes that feed on small vertebrates and invertebrates, with a high proportion of carnivorous species. The partial freezing of water surfaces in winter reduces the habitat available for waterbirds, which may explain why water body habitats have significantly fewer bird species than marsh habitats.
4.2. Relationship Between Different Habitat Diversity Indices
Elucidating the relationship between species diversity and functional diversity is of significant ecological importance for understanding their impacts on ecosystem functioning [41]. The results of this study show that Shannon–Wiener is positively and significantly correlated with FRic as well as FDis. FRic measures the volume of ecological niche space occupied by species within a community, and the greater the functional space occupied, the higher the stability [42,43]. According to the FRic calculation results, the bird community in the swamp habitat of the Shiquan River had the highest stability, which is consistent with the Shannon–Wiener index. However, the FDis results were the highest in grassland, which may be due to the uneven distribution of individual birds with the same functional traits in the survey area. For instance, most Anseriformes birds live mainly in swamps and water body habitats, whereas most Accipitriformes birds prefer to live in open areas such as grass and bare grounds where they can hunt, and Passeridae birds in Passeriformes prefer to live in swampy shrub habitats to hide from predators [40]. Therefore, an increase in species number will affect Shannon–Wiener and FDis results but will not change the uneven distribution of bird communities. The significant negative correlation between FDiv and Shannon–Wiener indicates that the niche overlap of communities with more species is relatively low, and the loss of a single species will cause changes in functional structure. Moreover, it also reflects the poor resilience of the Shiquan River ecosystem after a disturbance. Clearly, functional diversity connects birds and ecosystems, and studying it helps researchers understand how ecosystems operate and how to maintain their functions and stability [44]. Therefore, the species and functional diversity indices should be evaluated together as an important reference for monitoring, impact assessment, and planning to create conservation units.
4.3. Differences in Bird Communities Along Vertical Gradients
Numerous studies have established that avian community structures present significant spatiotemporal variations across vertical gradients [45,46]. For example, in a study of Sejilar Forest Park in Tibet, the results showed that fewer species inhabited the high elevation section above 4000 m, and only 26 species were observed in the 4500 m transect at the highest elevation. The reason for the low numbers in this elevation section may be related to its cold climate, low temperature, and low vegetation coverage, which make it difficult for birds to forage and survive [47]. The results of this study are consistent with the vertical distribution pattern of the monotonically decreasing species richness of birds with increasing elevation [46]. The results of this study are similar, indicating that low-elevation food is abundant but competitive, while high-elevation resources are scarce, and species tend to eat more widely; such selection leads to fewer species that can survive and adapt at high elevation. However, functional diversity analysis reveals significant differentiation in avian community characteristics across Shiquan River habitats: bird communities in bare grounds exhibit stronger niche complementarity and weaker competition; marsh habitats show the highest ecological space utilization, reflecting greater primary productivity; and grass habitats contain more species with similar functional traits. Given the complexity of ecosystems, which inherently involve multiple ecological interactions, the presence of numerous species with similar functional traits in the same habitat inevitably leads to competition and facilitation among species [48]. Therefore, habitat type is an important environmental filtering factor, and within local communities, interbiotic interactions may often be dominant.
4.4. Effects of Human Disturbance on Birds
Habitat degradation and destruction by human activities are the main causes of global biodiversity decline [49]. This includes agricultural expansion, urban construction, livestock overgrazing, and selective logging [50]. The bird diversity in the Shiquan River was greatly affected by human disturbance, and the degree of human disturbance was different. During the breeding season, the main threat to birds comes from disturbances by tourists along the national highway G317 in China. This section runs parallel to the middle section of the Shiquan River and has become an important habitat for rare and endangered birds, such as black-necked cranes. However, a large number of tourists stopping at the roadside to take photos, using drones to take close-range photos, making loud noises, and even feeding food have seriously affected the normal breeding behavior of birds. In addition, some off-road enthusiasts drive their vehicle directly into the river, and not only destroy the river bed ecology, but also the huge engine sound and vehicle movement startle birds. These disturbances cause some sensitive individuals to panic and flee, forcing them to abandon their nests or disrupt foraging rhythms. During the non-breeding season, the main threat to birds comes from grazing, but it is beneficial, as many birds feed on the droppings of livestock. This may be because high elevation birds have difficulty accessing food resources [51], and the presence of undigested herbaceous plants, seeds, and fungi in feces provides a food source for the birds.
5. Conclusions
Our study is the first systematic description based on the functional diversity of high-elevation wetland birds, with an outstanding geographic scope. In general, the level of species diversity in the Shiquan River is low, with relatively weak resistance to the disturbance of the ecosystem. Given the conservation priority of plateau wetlands for global biodiversity, the avian diversity of plateau wetlands is exceptional and irreplaceable, regardless of the species richness of the region, especially when these species have experienced unusual ecological and evolutionary processes on Earth’s unique tectonic units. Therefore, the effects of human disturbances on the functional diversity of high-elevation wetlands should be strengthened in the future. For birds eating livestock feces, intestinal microbiota analysis can be conducted to analyze the deeper causes.
Conceptualization, Y.W. and X.L.; Methodology, X.L.; Validation, Y.G., C.H. and J.W.; Formal analysis, Y.W.; Investigation, Y.W., Y.G. and J.W.; Resources, X.L.; data curation, Y.W.; writing—original draft preparation, Y.W.; writing—review and editing, Y.G.; supervision, X.L.; funding acquisition, X.L. All authors have read and agreed to the published version of the manuscript.
Not applicable.
All data are reported in the manuscript. Functional trait data for birds were obtained from the Dataset of Life History and Ecological Characteristics of Chinese Birds (
The Ali District Forestry and Grassland Bureau is gratuitous for field assistance. We thank the reviewers for their valuable time and constructive comments.
The authors declare no conflicts of interest.
Footnotes
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.
Figure 1 A schematic diagram of the study area location and survey sample points.
Figure 2 The cumulative curve of bird richness with the number of investigated species.
Figure 3 Diversity indices of birds in different habitats during the breeding and non-breeding seasons. (a) Shannon–Wiener; (b) Pielou; (c) Simpson; (d) functional richness (FRic); (e) functional dispersion (FDis); (f) functional divergence (FDiv).
Figure 4 Pearson correlation coefficients for species and functional diversity indices in different habitats. The color scale on the right indicates the correlation degree of each indicator, where red indicates a positive correlation, blue indicates a negative correlation, and the larger the circle and the darker the color, the stronger the correlation. *** p < 0.001 < ** p < 0.01 < * p < 0.05.
Appendix A
Bird list of Xizang Shiquan River National Wetland Park.
| IDX | Latin Name | Fauna | Distribution | Resident | Protection | IUCN | Red | Habitat Type | |||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Grass | Marshes | Bare | Water | ||||||||
| O1 | GALLIFORMES | ||||||||||
| F1 | Phasianidae | ||||||||||
| 1 | Perdix hodgsoniae | O | We | R | LC | LC | + | + | |||
| 2 | Tetraogallus tibetanus | OP | Pa | R | II | LC | NT | + | + | + | |
| O2 | ANSERIFORMES | ||||||||||
| F2 | Anatidae | ||||||||||
| 3 | Anser indicus | OP | P | W | LC | LC | + | + | + | ||
| 4 | Mergus merganser | OP | Cb | W | LC | LC | + | ||||
| 5 | Tadorna ferruginea | OP | Uf | S | LC | LC | + | + | + | ||
| 6 | Anas platyrhynchos | OP | Cf | W | LC | LC | + | + | + | ||
| O3 | PODICIPEDIFORMES | ||||||||||
| F3 | Podicipedidae | ||||||||||
| 7 | Tachybaptus ruficollis | OP | We | R | LC | LC | + | ||||
| 8 | Podiceps cristatus | OP | Ud | S | LC | LC | + | ||||
| O4 | COLUMBIFORMES | ||||||||||
| F4 | Columbidae | ||||||||||
| 9 | Columba rupestris | OP | O3 | R | LC | LC | + | + | |||
| 10 | Streptopelia orientalis | OP | E | R | LC | LC | + | + | |||
| O5 | CUCULIFORMES | ||||||||||
| F5 | Cuculidae | ||||||||||
| 11 | Cuculus canorus | OP | O1 | S | LC | LC | + | ||||
| O6 | GRUIFORMES | ||||||||||
| F6 | Gruidae | ||||||||||
| 12 | Grus nigricollis | OP | Pc | S | I | NT | VU | + | + | + | |
| O7 | CHARADRIIFORMES | ||||||||||
| F7 | Ibidorhynchidae | ||||||||||
| 13 | Ibidorhyncha struthersii | OP | Pf | R | II | LC | NT | + | |||
| F8 | Charadriidae | ||||||||||
| 14 | Vanellus cinereus | OP | D | P | LC | LC | + | + | + | ||
| F9 | Scolopacidae | ||||||||||
| 15 | Tringa ochropus | OP | Uc | P | LC | LC | + | + | |||
| 16 | Tringa totanus | OP | Uf | P | LC | LC | + | + | + | ||
| F10 | Laridae | ||||||||||
| 17 | Larus brunnicephalus | OP | Pa | S | LC | LC | + | + | |||
| 18 | Larus ichthyaetus | OP | D | P | LC | LC | + | + | |||
| 19 | Sterna hirundo | OP | Cc | S | LC | LC | + | + | |||
| O8 | ACCIPITRIFORMES | ||||||||||
| F11 | Accipitridae | ||||||||||
| 20 | Gypaetus barbatus | OP | O | R | I | EN | NT | + | + | ||
| 21 | Gyps himalayensis | OP | O3 | R | II | NT | NT | + | + | + | |
| 22 | Aquila nipalensis | OP | Da | S | I | EN | VU | + | + | ||
| 23 | Milvus migrans | OP | Uh | R | II | LC | LC | + | + | ||
| 24 | Buteo hemilasius | OP | Df | S | II | LC | VU | + | + | ||
| O9 | BUCEROTIFORMES | ||||||||||
| F12 | Upupldae | ||||||||||
| 25 | Upupa epops | OP | O | S | LC | LC | + | + | + | ||
| O10 | FALCONIFORMES | ||||||||||
| F13 | Falconidae | ||||||||||
| 26 | Falco tinnunculus | OP | O1 | R | II | LC | LC | + | + | + | |
| 27 | Falco cherrug | OP | Ca | S | I | EN | EN | + | + | + | |
| O11 | PASSERIFORMES | ||||||||||
| F14 | Corvidae | ||||||||||
| 28 | Pica pica | OP | Ch | R | LC | LC | + | + | + | ||
| 29 | Pyrrhocorax pyrrhocorax | OP | O3 | R | LC | LC | + | + | + | ||
| 30 | Pyrrhocorax graculus | OP | O | R | LC | LC | + | + | + | ||
| 31 | Corvus corax | OP | Ch | R | LC | LC | + | + | + | ||
| F15 | Paridae | ||||||||||
| 32 | Pseudopodoces humilis | OP | Pa | R | LC | LC | + | + | |||
| F16 | Alaudidae | ||||||||||
| 33 | Eremophila alpestris | OP | C | S | LC | LC | + | + | |||
| F17 | Hirundinidae | ||||||||||
| 34 | Hirundo rustica | OP | Ch | S | LC | LC | + | + | + | ||
| 35 | Ptyonoprogne rupestris | OP | O3 | R | LC | LC | + | + | |||
| F18 | Turdidae | ||||||||||
| 36 | Turdus mandarinus | OP | O3 | R | LC | LC | + | + | + | ||
| F19 | Muscicapidae | ||||||||||
| 37 | Copsychus saularis | O | Wd | R | LC | LC | + | ||||
| 38 | Phoenicurus ochruros | OP | O | S | LC | LC | + | ||||
| 39 | Phoenicuru erythrogastrus | OP | P | S | LC | + | |||||
| 40 | Saxicola maurus | OP | O1 | R | LC | LC | + | + | + | ||
| 41 | Oenanthe deserti | P | Da | R | LC | LC | + | + | + | ||
| F20 | Prunellidae | ||||||||||
| 42 | Prunella collaris | OP | Ud | R | LC | LC | + | + | + | ||
| 43 | Prunella rubeculoides | OP | Pd | R | + | + | + | ||||
| 44 | Prunella fulvescens | OP | Pw | R | LC | LC | + | + | + | ||
| F21 | Passeridae | ||||||||||
| 45 | Passer montanus | OP | Uh | R | LC | LC | + | + | + | ||
| 46 | Montifringilla adamsi | OP | Py | R | LC | LC | + | + | + | ||
| 47 | Onychostruthus taczanowskii | OP | Py | R | LC | LC | + | + | + | ||
| 48 | Pyrgilauda ruficollis | OP | Py | R | LC | LC | + | + | |||
| 49 | Pyrgilauda blanfordi | OP | Py | R | LC | LC | + | + | + | ||
| F22 | Motacillidae | ||||||||||
| 50 | Motacilla citreola | OP | U | R | LC | LC | + | + | + | + | |
| 51 | Motacilla alba | OP | U | R | LC | LC | + | + | + | + | |
| F23 | Fringillidae | ||||||||||
| 52 | Carpodacus erythrinus | OP | U | S | LC | LC | + | ||||
| 53 | Carpodacus rubicilla | P | Pw | S | LC | LC | + | ||||
| 54 | Leucosticte nemoricola | OP | Pw | R | LC | LC | + | + | |||
| 55 | Leucosticte brandti | OP | Pw | R | LC | LC | + | ||||
| 56 | Linaria flavirostris | OP | U | R | LC | LC | + | + | |||
Note: Fauna: Refer to Zoogeography of China [
Appendix B
Dataset of bird life history and ecological characteristics in Shiquan River National Wetland Park Xizang.
| IDX | Latin Name | Weight/g | Body Length/mm | Culmem/mm | Wing Length/mm | Tail Length/mm | Metatarsal | Feeding | Nest | Nest | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Male | Female | Male | Female | Male | Female | Male | Female | Male | Female | Male | Female | |||||
| 1 | Tetraogallus tibetanus | 1500~1755 | 1170~1600 | 490~570 | 510~638 | 29.7~32 | 28.7 | 265~283 | 250~270 | 163~174 | 160~176 | 60.3~61.9 | 58.7~59.2 | 1 | 1 | 1 |
| 2 | Perdix hodgsoniae | 270~550 | 270~430 | 230~300 | 255~320 | 16~19 | 15~19 | 133~160 | 134~152 | 84~100 | 68~100 | 38~42 | 37~41 | 1 | 2 | 1 |
| 3 | Anser indicus | 2300~3000 | 1600~2700 | 700~850 | 625~735 | 42~52 | 35~46 | 440~480 | 398~440 | 114~160 | 116~150 | 64~80 | 60~73 | 1 | 2 | 1 |
| 4 | Tadorna ferruginea | 1000~1656 | 969~1689 | 516~670 | 510~680 | 42~50 | 36~46 | 350~390 | 312~380 | 115~165 | 115~165 | 54~63 | 50~58 | 1 | 1 | 1 |
| 5 | Anas platyrhynchos | 1000~1300 | 910~1015 | 540~615 | 470~550 | 53~61 | 49~59 | 270~285 | 250~286 | 72~112 | 69~125 | 40~55 | 39~50 | 1 | 2 | 1 |
| 6 | Mergus merganser | 936~1925 | 650~1686 | 630~680 | 540~660 | 48~59 | 43~53 | 270~294 | 250~272 | 108~139 | 100~125 | 47~53 | 43~51 | 2, 3 | 1 | 4 |
| 7 | Tachybaptus ruficollis | 160~275 | 150~225 | 220~318 | 221~274 | 20~23 | 18~22 | 95~140 | 72~138 | 28~44 | 28~40 | 32~50 | 29~44 | 2, 3 | 2 | 2 |
| 8 | Podiceps cristatus | 650~1000 | 425~950 | 520~580 | 450~546 | 50~53 | 38~50 | 180~197 | 165~190 | 40~48 | 36~46 | 61~64 | 51~67 | 2, 3 | 2 | 2 |
| 9 | Columba rupestris | 180~305 | 201~290 | 290~350 | 232~333 | 14~18 | 15~18 | 211~230 | 210~230 | 110~146 | 108~141 | 25~28 | 25~28 | 4 | 2 | 5 |
| 10 | Streptopelia orientalis | 175~323 | 192~280 | 300~359 | 260~340 | 16~20 | 16~19 | 187~205 | 180~203 | 124~145 | 114~148 | 20~29 | 20~26 | 1 | 2 | 4 |
| 11 | Cuculus canorus | 100~153 | 91~135 | 302~345 | 260~334 | 18~23 | 19~23 | 203~240 | 187~223 | 150~190 | 147~189 | 20~24 | 19~26 | 2 | 3 | 0 |
| 12 | Grus nigricollis | 3850~6100 | 5000~6250 | 1140~1190 | 1160~1200 | 114~128 | 115~127 | 585~593 | 540~680 | 225~231 | 218~240 | 231~253 | 238~233 | 1 | 2 | 1 |
| 13 | Ibidorhyncha struthersii | 253~292 | 293~337 | 370~412 | 381~442 | 71~78 | 80~84 | 225~241 | 230~242 | 113~131 | 113~126 | 45~56 | 47~57 | 2, 3 | 2 | 1 |
| 14 | Charadrius mongolus | 55~67 | 51~67 | 180~198 | 180~196 | 17~19 | 17~19 | 124~139 | 126~131 | 47~60 | 45~51 | 31~36 | 30~34 | 2, 3 | 2 | 1 |
| 15 | Tringa totanus | 97~157 | 105~145 | 260~283 | 250~287 | 38~45 | 41~46 | 147~160 | 150~161 | 59~67 | 58~68 | 45~51 | 45~50 | 2 | 2 | 1 |
| 16 | Tringa ochropus | 60~104 | 60~107 | 200~255 | 217~264 | 32~37 | 31~38 | 131~147 | 133~151 | 50~63 | 54~67 | 30~38 | 30~42 | 2 | 2 | 1 |
| 17 | Chroicocephalus brunnicephalus | 550~714 | 450~700 | 419~466 | 421~462 | 37~41 | 35~37 | 344~379 | 323~341 | 133~143 | 121~138 | 50~55 | 49~50 | 2, 3 | 2 | 1 |
| 18 | Ichthyaetus ichthyaetus | 2000 | 2000 | 630~715 | 630~715 | 50~71 | 50~71 | 470~520 | 460~497 | 170~200 | 170~200 | 68~80 | 68~80 | 2, 3 | 2 | 1 |
| 19 | Sterna hirundo | 100~122 | 92~110 | 327~375 | 310~354 | 33~36 | 28~35 | 258~271 | 260~271 | 111~164 | 118~160 | 18~19 | 18~20 | 2, 3 | 2 | 1 |
| 20 | Gypaetus barbatus | 3500~5600 | 3500~5600 | 1000~1400 | 1000~1400 | 51~54 | 51~54 | 780~860 | 780~860 | 540~630 | 540~630 | 91~100 | 91~100 | 5 | 2 | 5 |
| 21 | Gyps himalayensis | 8000~12,000 | 8000~12,000 | 1200~1499 | 1200~1499 | 71~81 | 71~81 | 755~805 | 755~805 | 365~402 | 365~402 | 110~126 | 110~126 | 5 | 2 | 5 |
| 22 | Aquila nipalensis | 2015~2650 | 2150~2900 | 707~758 | 705~818 | 38~39.5 | 38~42 | 510~553 | 592~620 | 265~280 | 295~340 | 87~97 | 97~102 | 2, 3, 5 | 2 | 5 |
| 23 | Milvus migrans | 1015~1150 | 900~1160 | 540~660 | 585~690 | 25~40 | 27~38 | 438~550 | 440~530 | 270~362 | 285~358 | 52~75 | 50~72 | 2, 3 | 2 | 4 |
| 24 | Buteo hemilasius | 1320~1800 | 1950~2100 | 582~622 | 569~676 | 24~30 | 28~30 | 446~477 | 470~520 | 262~272 | 262~285 | 76~92 | 80~94 | 3 | 2 | 4 |
| 25 | Upupa epops | 53~81 | 55~90 | 266~312 | 245~300 | 47~59 | 43~56 | 140~158 | 136~157 | 95~124 | 90~110 | 18~27 | 20~25 | 2 | 1 | 4 |
| 26 | Falco tinnunculus | 173~240 | 180~335 | 316~340 | 305~360 | 14~15 | 14~15 | 238~252 | 234~269 | 161~183 | 152~184 | 37~42 | 33~43 | 2, 3 | 2 | 4 |
| 27 | Falco cherrug | 680~890 | 970~1200 | 425~580 | 520~591 | 20~22 | 24.2~26.5 | 348~380 | 378~412 | 232~240 | 245~258 | 55~55.5 | 59.5~60.5 | 3 | 2 | 4 |
| 28 | Pica pica | 190~266 | 180~250 | 365~485 | 380~460 | 31~38 | 28~37 | 190~230 | 178~210 | 210~275 | 200~262 | 48~58 | 42~54 | 1 | 2 | 4 |
| 29 | Pyrrhocorax pyrrhocorax | 210~485 | 216~370 | 360~470 | 370~422 | 44~60 | 33~56 | 268~333 | 263~312 | 143~187 | 135~173 | 36~51 | 38~50 | 1 | 2 | 5 |
| 30 | Pyrrhocorax graculus | 202~254 | 165~290 | 335~426 | 321~376 | 29~43 | 27~40 | 265~295 | 230~266 | 150~188 | 157~180 | 40~46 | 38~44 | 1 | 1 | 5 |
| 31 | Corvus corax | 650~1450 | 600~1240 | 630~710 | 607~671 | 64~82 | 68~76 | 450~469 | 431~460 | 265~290 | 246~285 | 58~69 | 57~67 | 1 | 2 | 4 |
| 32 | Pseudopodoces humilis | 25~46 | 25~47 | 132~180 | 133~171 | 18~27 | 19~23 | 78~96 | 76~94 | 53~71 | 51~68 | 23~30 | 25~29 | 2 | 1 | 1 |
| 33 | Eremophila alpestris | 32~43 | 29~47 | 150~193 | 147~182 | 10~15 | 10~14 | 91~121 | 95~120 | 63~92 | 63~92 | 19~26 | 19~26 | 1 | 2 | 1 |
| 34 | Ptyonoprogne rupestris | 18~25 | 20~28 | 127~160 | 130~175 | 6~9 | 7~8 | 120~140 | 126~175 | 57~73 | 57~70 | 10~12 | 10~12 | 2 | 1 | 5 |
| 35 | Hirundo rustica | 14~22 | 14~21 | 134~197 | 132~183 | 6~9 | 6~9 | 101~121 | 106~116 | 68~112 | 66~109 | 8~12 | 9~12 | 2 | 1 | 5 |
| 36 | Turdus mandarinus | 80~110 | NA | 240~250 | NA | NA | NA | NA | NA | NA | NA | NA | NA | 1 | 2 | 4 |
| 37 | Copsychus saularis | 33~47 | 32~50 | 187~227 | 178~214 | 15~21 | 15~20 | 90~105 | 88~99 | 87~110 | 80~96 | 27~34 | 26~32 | 2 | 1 | 4 |
| 38 | Phoenicurus ochruros | 14~24 | 17~24 | 127~165 | 128~152 | 9~12 | 10~12 | 78~89 | 73~88 | 57~70 | 56~78 | 22~25 | 21~25 | 2 | 1 | 3 |
| 39 | Phoenicurus erythrogastrus | 25~31 | 22~28 | 160~190 | 155~180 | 10~13.7 | 11~13 | 101~104 | 100~105 | 74~80 | 71~82 | 23~27 | 22~26 | 2 | 2 | 1 |
| 40 | Oenanthe deserti | 17~28 | 17~25 | 124~175 | 128~161 | 12~16 | 11~16 | 90~102 | 85~96 | 61~75 | 47~68 | 24~27 | 25~27 | 2 | 1 | 1 |
| 41 | Saxicola maurus | 12~22 | 12~24 | 118~146 | 115~140 | 9~12 | 8~12 | 62~74 | 60~74 | 41~58 | 42~58 | 20~24 | 20~23 | 2 | 2 | 1 |
| 42 | Prunella collaris | 31~45 | 30~40 | 160~195 | 154~188 | 10~14 | 10~14 | 90~106 | 95~101 | 59~84 | 63~72 | 20~25 | 19~25 | 1 | 2 | 1 |
| 43 | Prunella rubeculoides | 15~35 | 22~23 | 145~171 | 150~160 | 11~13 | 9~11 | 72~77 | 73~76 | 63~75 | 66~70 | 22~25 | 22~24 | 1 | 2 | 3 |
| 44 | Prunella fulvescens | 18~19 | 14~18 | 148~164 | 126~144 | 10~11 | 10~12 | 73~78 | 72~77 | 66~73 | 61~67 | 19~20 | 19~21 | 1 | 2 | 1 |
| 45 | Passer montanus | 16~24 | 17~23.7 | 115~150 | 116~147 | 9.5~11.8 | 9~12 | 60~78 | 61~70 | 44~66 | 44~66 | 17~20 | 17~20 | 1 | 1 | 5 |
| 46 | Montifringilla adamsi | 20~36 | 20~31 | 147~182 | 140~171 | 11~13.5 | 11~13.5 | 101~115 | 96~115 | 64.5~80.5 | 61~74 | 19~27 | 19~24.5 | 1 | 1 | 5 |
| 47 | Onychostruthus taczanowskii | 20~43 | 20~40 | 140~182 | 130~165 | 11~14.5 | 12~14 | 92~116 | 96~108 | 58~81 | 63~86 | 21~26.5 | 21~24.5 | 1 | 1 | 5 |
| 48 | Pyrgilauda ruficollis | 15~32 | 15~34 | 130~161 | 125~153 | 10~12 | 10~13 | 81~93 | 83~93 | 50~65 | 50~64 | 20~22 | 20~23 | 1 | 1 | 5 |
| 49 | Pyrgilauda blanfordi | 24~28 | 22~29 | 119~137 | 117~138 | 10~11 | 10~11 | 85~95 | 87~97 | 48~59 | 48~60 | 16~20 | 16~19 | 1 | 1 | 1 |
| 50 | Motacilla alba | 15~30 | 17~29 | 156~195 | 157~195 | 11~17 | 11~16 | 85~96 | 81~98 | 83~101 | 82~97 | 20~28 | 22~27 | 2 | 2 | 1 |
| 51 | Motacilla citreola | 17~26 | 14~27 | 150~195 | 145~180 | 12~14 | 12~14 | 77~92 | 74~90 | 76~90 | 68~88 | 21~29 | 21~27 | 2 | 2 | 1 |
| 52 | Leucosticte nemoricola | 16~25 | 19~25 | 142~167 | 145~167 | 9~11 | 10~11.5 | 92~102 | 90.5~101 | 67~77 | 66~76 | 19~23 | 19~21.5 | 1 | 1 | 5 |
| 53 | Leucosticte brandti | 28 | 26~29 | 164~190 | 160~179 | 11.8 | 10~11 | 105~119 | 103~119 | 78 | 74~76 | 21.5 | 20~22 | 1 | 2 | 1 |
| 54 | Carpodacus erythrinus | 18~27 | 18~31 | 133~162 | 126~159 | 10~13 | 10~12 | 71~87 | 71~88 | 51~67 | 51~67 | 17~21 | 17~21 | 1 | 2 | 3 |
| 55 | Carpodacus rubicilla | 30~52 | 37~52 | 173~205 | 167~198 | 12~15 | 12~15 | 103~130 | 108~118 | 79~96 | 75~95 | 20~28 | 21~29 | 1 | 1 | 5 |
| 56 | Linaria flavirostris | 10~18 | 10~15 | 112~162 | 118~144 | 7.5~9.5 | 7.3~11 | 73~80 | 71.7~78 | 57~71 | 60~68.5 | 14~18.5 | 14~18 | 1 | 2 | 3 |
Note: Feeding habits: omnivorous 1, insectivorous 2, carnivorous 3, fruit-eating 4, scavenging 5. Nest type: Hole nest 1, open nest 2, parasitic 3. Nest site: ground 1, water 2, scrub 3, crown 4, rock wall 5.
1. Sanjeev, S.; Pardeep, S. Wetlands Conservation: Current Challenges and Future Strategies; John Wiley & Sons, Ltd.: Hoboken, NJ, USA, 2021.
2. Geng, C.; Yan, L.; Tong, S.Z. Analysis of the causes of wetland landscape patterns and hydrological connectivity changes in Momoge National Nature Reserve based on the Google Earth Engine Platform. Arab. J. Geosci.; 2021; 14, 170.
3. Vento, B.; Rivera, J.; Ontivero, M. Climate influence on future suitability of high-altitude wetlands in two natural protected areas from the Central Andes of Argentina. Perspect. Ecol. Conserv.; 2024; 22, pp. 240-249. [DOI: https://dx.doi.org/10.1016/j.pecon.2024.04.006]
4. Immerzeel, W.W.; Van Beek, L.P.H.; Bierkens, M.F.P. Climate change will affect the Asian water towers. Science; 2010; 328, pp. 1382-1385. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20538947][DOI: https://dx.doi.org/10.1126/science.1183188]
5. Yan, L.Y.; Kong, L.Q.; Wang, L.J.; Hu, J.M.; Ouyang, Z.Y. Grass-livestock balance under the joint influences of climate change, human activities and ecological protection on Tibetan Plateau. Ecol. Indic.; 2024; 162, 112040. [DOI: https://dx.doi.org/10.1016/j.ecolind.2024.112040]
6. Wan, W.; Gadd, G.M.; Yang, Y.; Yuan, W.; Gu, J.; Ye, L.; Liu, W. Environmental adaptation is stronger for abundant rather than rare microorganisms in wetland soils from the Qinghai-Tibet Plateau. Mol. Ecol.; 2021; 30, pp. 2390-2403. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33714213][DOI: https://dx.doi.org/10.1111/mec.15882]
7. Carlos, M.; Ricardo, M.; Vicente, G. Protected area coverage of vulnerable regions to conserve functional diversity of birds. Conserv. Biol. J. Soc. Conserv. Biol.; 2023; 37, e14131.
8. Gregory, D.R.; Strien, V.A. Wild Bird Indicators: Using Composite Population Trends of Birds as Measures of Environmental Health. Ornithol. Sci.; 2010; 9, pp. 3-22. [DOI: https://dx.doi.org/10.2326/osj.9.3]
9. Zhang, X.; Zhong, Z.; Zhang, M.; Zhao, F.; Wu, Y.; Sun, Y.; Luo, J.; Zhang, Y.; Wang, X.; Cai, J.
10. Zhang, J.T.; Xiao, J.; Li, L. Variation of plant functional diversity along a disturbance gradient in mountain meadows of the Donglingshan reserve, Beijing, China. Russ. J. Ecol.; 2015; 46, pp. 157-166. [DOI: https://dx.doi.org/10.1134/S1067413615020058]
11. Griffin, J.N.; Verónica, M.; Johnson, A.F.; Jenkins, S.R.; Foggo, A. Functional diversity predicts overyielding effect of species combination on primary productivity. Oikos; 2009; 118, pp. 37-44. [DOI: https://dx.doi.org/10.1111/j.1600-0706.2008.16960.x]
12. Petchey, O.L.; Gaston, K.J. Functional diversity: Back to basics and looking forward. Ecol. J. Lett.; 2006; 9, pp. 741-775. [DOI: https://dx.doi.org/10.1111/j.1461-0248.2006.00924.x] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16706917]
13. Villéger, S.; Mason, N.W.H.; Mouillot, D. New multidimensional functional diversity indices for a multifaceted framework in functional ecology. Ecology; 2008; 89, pp. 2290-2301. [DOI: https://dx.doi.org/10.1890/07-1206.1]
14. Mason, N.W.H.; Mouillot, D.; Lee, W.G.; Wilson, B. Functional richness, functional evenness and functional divergence: The primary components of functional diversity. Oikos; 2005; 111, pp. 112-118. [DOI: https://dx.doi.org/10.1111/j.0030-1299.2005.13886.x]
15. Petchey, O.L.; Hector, A.; Gaston, K.J. How do different measures of functional diversity perform?. Ecology; 2004; 85, pp. 847-857. [DOI: https://dx.doi.org/10.1890/03-0226]
16. Díaz, S.; Cabido, M. Vive la différence: Plant functional diversity matters to ecosystem processes. Trends Ecol. Evol.; 2001; 16, pp. 646-655. [DOI: https://dx.doi.org/10.1016/S0169-5347(01)02283-2]
17. Mouchet, M.A.; Villéger, S.; Mason, N.W.H.; Mouillot, D. Functional diversity measures: An overview of their redundancy and their ability to discriminate community assembly rules. J. Funct. Ecol.; 2010; 24, pp. 867-876. [DOI: https://dx.doi.org/10.1111/j.1365-2435.2010.01695.x]
18. Cadotte, M.W.; Cascadden, K.; Mirotchnick, N. Beyond species: Functional diversity and the maintenance of ecological processes and services. J. Appl. Ecol.; 2011; 48, pp. 1079-1087. [DOI: https://dx.doi.org/10.1111/j.1365-2664.2011.02048.x]
19. Wang, Y.; Zong, N.; He, N.P.; Zhang, J.J.; Tian, J.; Li, L.T. Soil microbial functional diversity patterns and drivers along an elevation gradient on Qinghai-Tibet, China. Acta Ecol. Sin.; 2018; 38, pp. 2-9.
20. Gao, H.M.; Jiang, F.; Zhang, J.J.; Chi, X.W.; Song, P.F.; Li, B.; Cai, Z.Y.; Zhang, T.Z. Effects of ex situ conservation on diversity and function of the gut microbiota of the Tibetan wild ass (Equus kiang). Integr. Zool.; 2023; 18, pp. 1089-1104. [DOI: https://dx.doi.org/10.1111/1749-4877.12726]
21. Zhang, Y.W.; Guo, Y.P.; Feng, Y.H.; Zhang, Z.H.; Tang, R.; Bai, Y.; Tang, Z.Y. Satellite hyperspectral imagery reveals scale dependence of functional diversity patterns in a Qinghai-Tibetan alpine meadow. Int. J. Appl. Earth Obs. Geoinf.; 2024; 129, 103868. [DOI: https://dx.doi.org/10.1016/j.jag.2024.103868]
22. Min, T.; Hong, L.J.; Feng, T.H.; Kun, Z.Z.; Qian, Q.; Lin, Y.K.; Zhou, C.H.; Ping, M.S.; Jun, X.K.; Yu, C.Z.
23. Wu, F.; Yang, X.J. Application of sample point method in forest bird survey. J. Ecol.; 2008; 27, pp. 2240-2244.
24. John, M.; Karen, P.; Ho, F. Chinese Bird Field Manual; Lu, H.F.; He, F.C.; Xie, Y. Hunan Education Press: Changsha, China, 2000.
25. Zheng, G.M. Classification and Distribution of Birds in China; 4th ed. Beijing Science Press: Beijing, Chian, 2023.
26. China Forestry and Grassland Administration, Ministry of Agriculture and Rural Affairs. National List of Wildlife under Key Protection (revised on 1 February 2021). J. Wildl.; 2021; 42, pp. 605-640.
27. Zhang, Y.Y. China Red List of Biodiversity: Vertebrates Volume 2 Birds; Science Press: Beijing, China, 2021; pp. 2-274.
28. IUCN. Red List of Threatened Species. R. 2024; Available online: https://www.iucnredlist.org (accessed on 20 December 2024).
29. Zhang, R.Z. Zoogeography of China; Science Press: Beijing, China, 2011; pp. 281-315.
30. Hsieh, T.C.; Ma, K.H.; Chao, A. iNEXT: An R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol.; 2016; 7, pp. 1451-1456. [DOI: https://dx.doi.org/10.1111/2041-210X.12613]
31. Ma, K.P.; Liu, Y.M. Methods for measuring the diversity of biological communities I: D Methods for measuring the diversity (ii). Biodiversity; 1994; 2, pp. 231-239.
32. Pielou, E.C. Ecological Diversity; M. John Wiley: New York, NY, USA, 1975.
33. Wang, Y.P.; Song, Y.F.; Zhong, Y.Q.; Chen, C.W.; Zhao, Y.H.; Zeng, J.; Wu, Y.R.; Ding, P. A dataset of life history and ecological characteristics of birds in China. Biodiversity; 2021; 29, pp. 1149-1153.
34. He, X.; Wen, Z.; Zhang, D.; Yang, Q.; Yin, X.; Chen, X.; Ran, J. Low impact of forest conversion on biodiversity: Evidence from small mammals in contrasting forests of Mt. J. Liangshan. Ecosphere; 2021; 14, 10. [DOI: https://dx.doi.org/10.1002/ecs2.4570]
35. Laliberté, E.; Legendre, P. A distance-based framework for measuring functional diversity from multiple traits. J. Ecology; 2010; 91, pp. 299-305. [DOI: https://dx.doi.org/10.1890/08-2244.1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20380219]
36. Kembel, S.W.; Cowan, P.D.; Helmus, M.R.; Cornwell, W.K.; Morlon, H.; Ackerly, D.D. Picante: R tools for integrating phylogenies and ecology. Bioinformatics; 2010; 26, pp. 1463-1464. [DOI: https://dx.doi.org/10.1093/bioinformatics/btq166]
37. Oksanen, J.; Simpson, G.; Blanchet, F.; Kindt, R.; Legendre, P.; Minchin, P.; O’Hara, R.; Solymos, P.; Stevens, M.; Szoecs, E.
38. Gong, H.D. The Relationship Between Bird Community Characteristics and Environmental Factors in Medika Wetland National Nature Reserve, Xizang Province. Master’s Thesis; Xizang University: Xianyang, China, 2021.
39. Rehfisch, M.M. Man-made lagoons and how their attractiveness to waders might be increased by manipulating the biomass of an insect benthos. J. Appl. Ecol.; 1994; 31, pp. 383-401. [DOI: https://dx.doi.org/10.2307/2404552]
40. Horváth, Z.; Ferenczi, M.; Móra, A.; Vad, C.F.; Ambrus, A.; Forró, L.; Szövényi, G. Invertebrate food sources for waterbirds provided by the reconstructed wetland of Nyirkai-Hany, northwestern Hungary. Hydrobiologia; 2012; 697, pp. 59-72. [DOI: https://dx.doi.org/10.1007/s10750-012-1170-5]
41. Stefano, M.; Carmona, C.P.; Thomas, G. Concepts and applications in functional diversity. Funct. Ecol.; 2021; 35, pp. 1869-1885.
42. Cosset, C.C.; Edwards, D.P. The effects of restoring logged tropical forests on avian phylogenetic and functional diversity. Ecol. Appl. A Publ. Ecol. Soc. Am.; 2017; 27, pp. 1932-1945. [DOI: https://dx.doi.org/10.1002/eap.1578] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28543995]
43. Batisteli, A.F.; Tanaka, M.O.; Souza, A.L. Bird functional traits respond to forest structure in riparian areas undergoing active restoration. Diversity; 2018; 10, 90. [DOI: https://dx.doi.org/10.3390/d10030090]
44. Majid, S.; Mansoureh, K.; Zeinab, J. The relationship between the functional diversity, functional redundancy and community stability in mountain rangelands. Community Ecol.; 2022; 24, pp. 1-8.
45. Dehling, D.M.; Fritz, S.A.; Till, T.; Martin, P.; Patrizia, E.; Katrin, B.G.; Schleuning, M. Functional and phylogenetic diversity and assemblage structure of frugivorous birds along an elevational gradient in the tropical Andes. Ecography; 2014; 37, pp. 1047-1055. [DOI: https://dx.doi.org/10.1111/ecog.00623]
46. Pan, X.Y.; Liang, D.; Zeng, W.; Hu, Y.M.; Liang, J.C.; Wang, X.W.; Robinson, S.K.; Luo, X.; Liu, Y. Climate, human disturbance and geometric constraints drive the elevational richness pattern of birds in a biodiversity hotspot in southwest China. Glob. Ecol. Conserv.; 2019; 18, pp. 1-11. [DOI: https://dx.doi.org/10.1016/j.gecco.2019.e00630]
47. Zhao, L.L. Study on Bird Species Diversity in Sejira National Forest Park, Tibet; Tibet College of Agriculture and Animal Husbandry: Nyingchi, China, 2023.
48. García, G.J.; Heino, J.; García, C.F.; Camino, F.A.; Janne, A. Biotic interactions hold the key to understanding metacommunity organisation. Ecography; 2020; 43, pp. 1180-1190. [DOI: https://dx.doi.org/10.1111/ecog.05032]
49. Matuoka, A.M.; Benchimol, M.; Almeida-Rocha, D.M.J.; Morante-Filho, C.J. Effects of anthropogenic disturbances on bird functional diversity: A global meta-analysis. Ecol. Indic.; 2020; 116, 106471. [DOI: https://dx.doi.org/10.1016/j.ecolind.2020.106471]
50. Asefa, A.; Davies, B.A.; McKechnie, E.A.; Kinahan, A.A.; Rensburg, J.B. Effects of anthropogenic disturbance on bird diversity in Ethiopian montane forests. Condor; 2017; 119, pp. 416-430. [DOI: https://dx.doi.org/10.1650/CONDOR-16-81.1]
51. Crampton, L.H.; Longland, W.S.; Murphy, D.D.; Sedinger, J.S. Food abundance determines distribution and density of a frugivorous bird across seasons. Oikos; 2011; 120, pp. 65-76. [DOI: https://dx.doi.org/10.1111/j.1600-0706.2010.18624.x]
© 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.