Spatial and Temporal Variations in Waterfowl Assemblage Structures in Mongolian Lakes and the Changes Linked to the Gradient of Lake Surface Areas

Abstract

Lakes and wetlands provide top-priority hotspots that play a key role in maintaining and protecting threatened and migratory waterfowl. Identifying seasonal and spatial variations in aquatic bird communities and their responses to environmental factors is vital conservation efforts. However, there is a lack of information on waterfowl in Mongolian lakes and their associated wetlands. The purpose of this study was to investigate the spatial–seasonal changes in waterfowl assemblage structures in Mongolian lakes, as well as to determine how they respond to various environmental factors (lake surface area, elevation, and geographical distribution). Statistical analyses were performed using seasonal data (May, July, and September) for 28 waterfowl collected from 54 lakes across the country between 2016 and 2018. Seasonal heterogeneity in species richness and abundance was observed in lakes in each geographical region (Eastern, Central, and Western Mongolia). The composition of waterfowl in the lake was also relatively similar between May and September compared to July. This was due to the overlapping migration seasons in spring and autumn. Regionally, the number of waterfowl was much higher in the Eastern Mongolian lakes, followed by Central Mongolian lakes and then Western Mongolian lakes. This is likely due to differences in habitat availability and water levels between the regions. Eastern Mongolian lakes tend to have more wetlands and shallow water habitats, while Central and Western Mongolian lakes tend to have deeper open-water habitats. These differences in habitat types could contribute to the observed differences in waterfowl abundance among the regions. Additionally, some small lakes and the group of small lakes supported a greater abundance and diversity of waterfowl compared to some medium-sized and large lakes, suggesting that they are important for conservation. Indices of diversity (H’) and species dominance (D’) showed positive and negative correlations with lake surface area, respectively. Perhaps the increased surface area of the lake decreases the habitat overlap for designated waterfowl due to habitat heterogeneity. Accordingly, the indices (H’ and E_H) increased as the waterfowl species composition became relatively equivalent in large lakes. Overall, spatial variations among the lakes were primarily attributable to the individual features of the lakes (shallowness, small lake groupings, and surface area), and seasonal variation in the lakes depended majorly on the compositional changes of the waterfowl due to migration.

1. Introduction

Lakes and their associated wetlands play a vital role in preserving aquatic ecosystems and supporting ecological diversity [1]. A wide variety of waterbird species utilize the habitats at different times during their annual life cycles for nesting, breeding, food, shelter, migration stops, and wintering [2,3]. The presence and availability of wetlands and lakes throughout the flyways is especially important in supporting the migration success of long-distance migrants such as waterfowl, waders, and shorebirds [1,4]. Intense human disturbances (such as land-use modification, water pollution, and heavy grazing) and climate change, however, majorly affect their availabilities (natural presence, surface size, and heterogeneity), leading to the high risk of waterbird decline worldwide [2,4,5]. It is accordingly imperative to attend to and protect these habitats as they are vital to the conservation of migratory waterbirds and other biodiversity.

There are a variety of environmental descriptors that influence the structure of waterbird assemblages locally, regionally, and seasonally. Local characteristics of lakes such as depth, surface area, sedimentation ratio, and trophic status are key factors in identifying the composition, abundance, and richness of aquatic birds [2,5,6,7]. Shallow and highly productive lakes with a high sedimentation ratio support a high abundance of waterbirds. However, species richness increases with the size of lakes and their associated wetlands due to habitat heterogeneity in large systems. The spatial and seasonal dynamics of waterbird assemblages can also be found in systems due to differences in migration patterns, such as period and corridor [2,8,9]. Accordingly, local environmental factors affecting spatial–seasonal differences in aquatic bird communities are the basis for ecological studies associated with conservation targets [10].

Mongolia is one of the top-priority countries for the research and conservation of migratory birds due to its location at the junction of three major migratory flyways: East Asia–Australia, Central Asia, and Eastern Africa–West Asia [11,12]. A number of pristine natural habitats are also found in Mongolia such as the Altai-Sayan and Daguur ecoregions, which are among the world’s most biologically outstanding regions and include sites noted for their conservation value, Ramsar sites, and important bird areas (IBAs) [11,12,13,14,15]. Moreover, the IBAs with wetlands are considered important breeding and stopover sites for migratory land and water birds [1,12,16,17]. Unfortunately, many lakes and wetlands across Mongolia have been rapidly shrinking and drying up in recent decades due to the continual decrease in river inputs and rapid water evaporation as a consequence of climate change (increasing temperature and decreasing precipitation) [12,18,19,20]. The acceleration of human activities is, moreover, a major cause for the loss of lake sizes in Mongolia and their deterioration, which is due to overgrazing, intense mining, and expanding agricultural practices [18,19,20]. Attending to their conservation is therefore valuable for supporting the ecological requirements of aquatic birds, including nesting, breeding, food, shelter, and migration stopovers, and has international significance. Despite the fact that several monitoring programs have been actively implemented in a few lakes and rivers and their associated wetlands in Mongolia, there is still a lack of information on waterfowl that is connected with spatial–seasonal variations and the impacts of the local characteristics of lakes and wetlands [12,15,18,19,21,22,23,24,25,26].

Based on biological data from 54 Mongolian lakes and their associated wetlands, the present study has investigated spatial–seasonal variations in the assemblages of migratory waterfowl along the different migration flyways. The influence of the size of lakes and the grouping of small lakes was also addressed as descriptors for the changes in the waterfowl community structures [4,27]. This is because of the lack of attention given by the government to small lakes and wetlands in Mongolia compared to the larger lakes. Moreover, several factors affecting waterfowl communities around the country were investigated, including the gradients of geographical locations and longitudes.

2. Materials and Methods

2.1. Background of Study Lakes

The lakes studied are distributed all over Mongolia, which is located in the transition zone between the boreal forests of Siberia and the deserts of Central Asia (Figure 1). The southern fringes of the Siberian Great Taiga (boreal forest) extend into northern Mongolia, whereas the vast Mongolian and Manchurian steppes spread into the country from the east [12,13]. The landscapes of southern Mongolia are dominated by the Gobi Desert, while the high Altai Mountains dominate the west and northwest. From north to south, the landscape changes from forested mountains through grassy steppe to barren, arid desert plains [12]. Meanwhile, the topography from the west to the east changes from a high mountainous terrain to boundless plains. Each region has its own specific floral and faunal characteristics. When combined, these characteristics comprise the unique biological richness of the country [12].

There are three main watersheds: the Arctic Ocean Basin, the Pacific Ocean Basin, and the Central Asian Internal Drainage Basin [28]. The majority of lakes in this study address the third river watershed and include the western and south–central Mongolian lakes such as Uvs, Buun Tsagaan, and Khar Lake. Eastern Mongolian lakes (Khukh, Buir, and Tashgai Tavan Lakes, etc.) are in the Pacific Ocean Basin. Central–northern Mongolian lakes (Khuvsgul, Terkhiin Tsagaan, Ugii Lake, etc.) include the Arctic Ocean Basin [13]. Most lakes in the eastern region are fed by rainwater; however, some lakes are also fed by rivers and streams (e.g., Khukh and Buir Lake, etc.) [12,15]. The small- and medium-sized lakes in the Gobi-desert depend on rainfall levels. Most lakes in the western and north–central regions are fed by rivers and streams [12,23]. The surface area of the study lakes varied in the range of 1.17 km² and 3350 km² (<10 km²—twenty-six lakes, 10–20 km²—four lakes, 20–50 km²—four lakes, 50–100 km²—8 lakes, 100–500 km²—seven lakes, 500–1000 km²—two lakes, and 1000 km² <—three lakes) (

Table 1. Summary data of waterfowl community metrics in the lakes, showing lake surface area and depth.

Code	Lake Name	Province	Average Depth (m)	Surface Area (km2)	Elevation (m)	Richness	F.O	Total Abundance	H’	EH	D’
WL1	Tolbo lake	Bayan-Ulgii	6.8	84	2083	22	17	7006	2.32	0.60	0.12
WL2	Khoton-Khurgana Lake	Bayan-Ulgii	27	50	2072	8	12	836	1.73	0.47	0.26
WL3	Dayan Lake	Bayan-Ulgii	2.3	67	2232	5	14	2325	2.17	0.62	0.14
WL4	Uvs Lake	Uvs	11.9	3350	743	16	18	2787	2.06	0.44	0.22
WL5	Uvsiin Khar Us Lake	Uvs	5.2	85.2	1792	10	15	2005	2.37	0.71	0.11
WL6	Uureg Lake	Uvs	26.9	238	1425	12	16	1341	2.21	0.57	0.14
WL7	Uvsiin Baga-Bayan Lakes	Uvs	8	30.6	931	11	21	2493	2.02	0.36	0.22
WL8	Airag lake	Uvs	5.7	143	1030	15	16	987	1.98	0.45	0.19
WL9	Achit lake	Uvs	2	296.8	1435	8	18	1756	2.31	0.56	0.13
WL10	Khar Us lake	Khovd	2	1852	1157	8	16	3691	1.90	0.42	0.20
WL11	Khar Lake	Khovd	4.2	578	1132	14	17	1591	1.90	0.39	0.20
WL12	Taigam Lake	Govi-Altai	0.9	4.1	1730	14	18	4915	2.37	0.59	0.12
WL13	Ereen Lake	Govi-Altai	2.1	4.31	1451	5	14	3733	1.94	0.50	0.19
WL14	Ulaagchiin Khar Lake	Zavkhan	19.6	84.5	1647	4	14	2893	1.73	0.40	0.22
WL15	Telmen Lake	Zavkhan	13.8	213.37	1544	11	9	328	1.82	0.69	0.20
WL16	Santmargatsiin Bayan Lake	Zavkhan	21.7	64.2	1662	8	9	1109	0.65	0.21	0.74
WL17	Oigon Lake	Zavkhan	3.4	75.57	1574	5	14	623	2.04	0.55	0.19
CL18	Olon Lakes	Bulgan	1.5	5.6	980	14	18	4907	1.86	0.36	0.27
CL19	Terkhiin Tsagaan Lake	Arkhangai	6	63.31	2060	24	15	5980	1.73	0.38	0.24
CL20	Selengiin Tsagaan Lake	Selenge	1.3	5.8	680	8	11	1135	1.05	0.26	0.58
CL21	Targan Lake	Khuvsgul	6	19.9	1536	12	7	561	1.09	0.43	0.48
CL22	Khuvsguliin Sangiin Dalai	Khuvsgul	12.1	165	1889	21	17	7434	1.85	0.37	0.20
CL23	Khuvsgul Lake	Khuvsgul	137.9	2760	1645	13	17	715	2.62	0.81	0.09
CL24	Erkhel Lake	Khuvsgul	0.9	13.2	1544	4	15	1860	1.87	0.43	0.22
CL25	Dood Tsagaan Lake	Khuvsgul	8	43.1	1538	10	8	963	1.42	0.52	0.29
CL26	Deed Tsagaan Lake	Khuvsgul	5	2.7	1550	8	9	241	1.64	0.57	0.24
CL27	Ugii Lake	Arkhangai	6.6	25.7	941	10	14	1485	1.98	0.51	0.17
CL28	Sharga Lake	Bulgan	3.7	12.4	1335	5	13	1090	1.80	0.47	0.20
CL29	Ulziitiin Sangiin Dalai	Uvurkhangai	1.5	2.4	1705	8	18	5712	1.03	0.16	0.61
CL30	Khargal Lake	Bulgan	5	13.5	1071	6	2	82	0.26	0.65	0.86
CL31	Dashinchilengiin Bayan Lake	Bulgan	-	2.9	936	8	14	444	1.88	0.47	0.20
CL32	Airkhan Lake	Bulgan	1.3	5	1030	6	15	2359	1.60	0.33	0.35
CL33	Taatsiin Tsagaan Lake	Uvurkhangai	1	9.9	1234	5	10	669	1.89	0.66	0.19
CL34	Orog Lake	Bayankhongor	3	121.37	1334	11	18	2462	2.29	0.55	0.13
CL35	Buun Tsagaan Lake	Bayankhongor	9.3	252	1433	24	18	8705	1.74	0.32	0.29
EL36	Gun Tsengeleg Lake	Dornod	-	0.8	832	13	10	2524	1.54	0.47	0.35
EL37	Gurmen Lake	Khentii	0.8	5.6	918	6	14	381	2.15	0.62	0.16
EL38	Ganga Lake	Sukhbaatar	0.5	2.2	1294	4	10	2244	1.26	0.35	0.36
EL39	Turgen Tsagaan Lake	Dornod	0.9	3.7	812	8	11	1553	2.07	0.72	0.14
EL40	Tashgain Lake	Dornod	-	1.1	718	9	17	5116	1.96	0.42	0.21
EL41	Shuut Lake	Dornod	-	1.1	715	8	12	1421	2.04	0.64	0.18
EL42	Shaazan Lake	Dornod	-	1.17	800	5	13	551	2.19	0.69	0.15
EL43	Khukh Lake	Dornod	3.2	51.6	560	13	16	22,219	2.06	0.49	0.17
EL44	Khaichiin Tsagaan Lake	Dornod	1.6	7.6	663	7	11	1484	1.98	0.66	0.17
EL45	Ikh Daila Lake	Dornod	-	2.2	601	9	7	459	1.65	0.74	0.22
EL46	Baga Dalai Lake	Dornod	-	2.8	715	6	6	609	1.49	0.74	0.27
EL47	Galuut Lake, Baga	Dornod	-	1	839	9	3	444	0.04	0.35	0.99
EL48	Galuut Lake	Dornod	1.3	6.5	583	7	11	2943	1.61	0.45	0.32
EL49	Erveekhii Lake	Dornod	-	0.6	839	8	13	621	2.08	0.61	0.16
EL50	Duruu Lake	Dornod	1.5	6.5	632	7	7	664	1.62	0.72	0.22
EL51	Chukh Lake	Dornod	2.5	2.64	582	6	9	2517	1.09	0.33	0.51
EL52	Busiin Lake	Dornod	1	2.9	628	6	3	1870	0.64	0.63	0.66
EL53	Buir lake	Dornod	6.5	615	581	15	15	4342	1.79	0.40	0.27
EL54	Khurkheree Lake	Khentii	-	1.6	1020	6	6	456	1.17	0.54	0.40

Notes: F.O—frequency of observation, H’—Shannon diversity index, D’—dominance index, E_H—Shannon evenness index, WL—Western Lake, CL—Central Lake, EL—Eastern Lake.

). The average depth of the study lakes ranged from 0.9–137.9 m (<5 m—twenty-four lakes, 5–10 m—twelve lakes, 10–20 m—four lakes, 20–30 m—three lakes, and 100 m <—one lake) (Table 1) [28,29,30].

2.2. Procedure of Field Observation

From 2016 to 2018, field surveys were conducted at all Mongolian important bird areas in May, July, and September. Observation data on twenty-eight waterfowl in fifty-four lakes were extracted from our collected data for this study. Observation sites were randomly selected along the shoreline within each lake and their associated wetlands, with high points being preferred. The waterfowl species were registered and counted from 525 sites using the point counting method and research tools (the visible eye encounter, field binoculars (Nikon Monarch HG, 10 × 42), and a spotting scope (CarlZeiss, 20—60 × 80)) [31]. The number of observation sites varied from five to twenty-four, depending on the size of the lakes and some difficult natural situations. The observations lasted approximately 10 min to diminish the probability of bird recount [31], and the distance between observers along the shores of the lakes varied from approximately 50 to 200 m.

2.3. Analytic Approach

Shannon–Weiner’s diversity (H’), evenness (E_H), and Simpson’s dominance (D’) were applied to quantify the diversity of the waterfowl species because these indices provide more information about community composition than species richness [32,33,34]. These calculations were performed using PAST (version 4.3.0) [35]. Moreover, the following formula was utilized to compute the species’ probability of observation: P_{(species 1,2…)} = (n_l * n_os)/(N_l * N_os), where P is the species probability to observe, n_l is the number of observed lakes, n_os is the number of observed sites, and N_l and N_os are the total numbers of study lakes and counting point sites, respectively. The relative abundance (RA) of a bird species was determined using the following expression: (number of individuals for species n/N total number of individuals) × 100%.

To illustrate seasonal variations in waterfowl community attributes (i.e., species richness and abundance), we performed an analysis of variance (ANOVA) and a Tukey’s post -hoc test using the function “aov” in R software (version 4.2.2) [36]. A non-metric multidimensional scaling (NMDS) [37] was performed to examine spatial variations in the waterfowl due to region and flyway differences across the country with the help of the function “metamds” in the R package vegan 2.6-2 [38]. Data on waterfowl abundance with total species were Hellinger-transformed using the R package vegan function “decostand” [39], which reduces the weights of abundant species but keeps the Bray–Curtis index between lakes [39]. Additionally, a permutational multivariate analysis of variance (PERMANOVA, using the “Adonis” function in R software [35]) was used to test for regional differences. A principal component analysis (PCA) was used to analyze the relationship between environmental variables and waterfowl community attributes, aided by the “FactoMiner” and “factoextra” packages in R software [40].

3. Results

3.1. Waterfowl Diversity and Abundance in Lakes

During this study, 139,641 individual waterfowl were recorded, belonging to 28 waterfowl species from the families Anatidae and Anseriiformes. The richness varied from 2 to 21 among the lakes, with a range of 0.04–2.62 for species diversity (H’) (Table 1). The highest richness (21 species) was found in the group lake of Baga-Bayan in western Mongolia. On the contrary, in the central region, Khargal Lake showed the lowest richness (2 species). According to the evenness index (E_H), the evenness of waterfowl in the lakes ranged between 0.16 and 0.81. The highest value was identified in Khuvsgul Lake and the smallest value was found in the Ulziitiin Sangiin Dalai lake in central Mongolia. Regarding the dominance index (D’), there was a high variation among lakes in the range of 0.09–0.99. The total abundance of the 28 waterfowl varied greatly between lakes. The most abundant lake (22219 individuals) was Khukh Lake in eastern Mongolia, and the lowest abundance was observed in Khargal Lake, which had 82 individuals (Table 1).

According to each species’ abundance, the most numerous species were Tadorna ferruginea (relative abundance: 19.35%, mean ± s.e.: 77.9 ± 10.2), Aythya ferina (10.14%, 80.9 ± 11.2), Anser indicus (8.87%, 129.0 ± 28.3), and Aythya fuligula (8.23%, 69.2 ± 8.6) (

Table 2. The assemblage patterns of 28 waterfowl in lakes throughout the country.

Scientific Name	English Name	Lake Observed (54)	O.F (525)	Probability to Observe (%)	Total Abundance	Average Abundance	Std. Error	Max	Min	R.A
Anas acuta	Northern Pintail	38	105	14.07	3793	36.1	7.1	485	1	2.72
Anas crecca	Common Teal	31	58	6.34	1685	29.1	4.7	158	2	1.21
Anas platyrhynchos	Mallard	40	156	22.01	4445	28.5	3.6	424	1	3.18
Anas zonorhyncha	Eastern Spot-billed Duck	2	2	0.01	3	1.5	0.5	2	1	0.00
Anser anser	Graylag Goose	22	126	9.78	5440	43.2	6.2	574	1	3.90
Anser cygnoid	Swan Goose	35	96	11.85	12,386	129.0	28.3	1425	1	8.87
Anser fabalis	Bean-Goose	6	11	0.23	2185	198.6	117.9	1300	2	1.56
Anser indicus	Bar-headed Goose	31	134	14.65	11,391	85.0	33.5	4300	1	8.16
Aythya ferina	Common Pochard	46	175	28.40	14,154	80.9	11.2	1112	1	10.14
Aythya fuligula	Tufted Duck	45	166	26.35	11,486	69.2	8.6	803	1	8.23
Aythya marila	Greater Scaup	4	6	0.08	47	7.8	1.2	12	3	0.03
Aythya nyroca	Ferruginous Duck	13	18	0.83	256	14.2	3.9	62	2	0.18
Bucephala clangula	Common Goldeneye	41	146	21.11	10,378	71.1	9.8	745	1	7.43
Cygnus columbianus	Tundra Swan	3	6	0.06	15	2.5	0.8	6	1	0.01
Cygnus cygnus	Whooper Swan	48	272	46.05	5248	19.3	3.2	544	1	3.76
Cygnus olor	Mute Swan	7	10	0.25	34	3.4	1.2	14	1	0.02
Mareca falcata	Falcated Duck	5	6	0.11	72	12.0	3.1	24	3	0.05
Mareca penelope	Eurasian Wigeon	38	101	13.54	4407	43.6	7.5	414	1	3.16
Mareca strepera	Gadwall	41	165	23.86	9856	59.7	11.3	1160	1	7.06
Melanitta fusca	Velvet Scoter	22	50	3.88	1460	29.2	14.6	730	1	1.05
Mergus merganser	Goosander	12	32	1.35	1596	49.9	37.4	1200	1	1.14
Mergus serrator	Red-breasted Merganser	4	12	0.17	54	4.5	0.9	11	1	0.04
Netta rufina	Red-crested Pochard	14	46	2.27	2260	49.1	14.3	550	1	1.62
Oxyura leucocephala	White-headed Duck	3	5	0.05	33	6.6	0.9	9	4	0.02
Spatula clypeata	Northern Shoveler	33	82	9.54	2102	25.6	4.4	244	1	1.51
Spatula querquedula	Garganey	19	28	1.88	339	12.1	2.1	48	1	0.24
Tadorna ferruginea	Ruddy Shelduck	51	347	62.42	27,014	77.9	10.2	1917	1	19.35
Tadorna tadorna	Common Shelduck	37	125	16.31	7502	60.0	12.8	1285	1	5.37

Notes: RA—relative abundance; O.F—observation frequency.

). The first two species were observed in the majority of the lakes in our study, which included 51 and 46 lakes, respectively. On the other hand, Anser indicus was mostly found in lakes in western and central Mongolia (31/54), and Anser cygnoid was commonly observed in the lakes of eastern and central Mongolia (35/54). Moreover, the least numerous species were Oxyure leucocephala (0.02%, 6.6 ± 0.9), Cygnus columbianus (0.1%, 2.5 ± 0.8), and Anas zonorhyncha (0.001%, 1.5 ± 0.5). Additionally, Tadorna ferruginea (62.42%), Cygnus cygnus (46.05%), Aythya ferina (28.40%), and Aythya fuligula (26.35%) were evaluated as having a higher possibility of observation than other species throughout Mongolia (Table 2).

Among the observed months, a statistical difference in species diversity and evenness (H’ and E_H) was found during the study years (ANOVA, df = 122.2, F = 14.34 and 14.86, p < 0.001, respectively). The indexes and species richness were higher in the May surveys than in the July and September surveys (Figure 2A,

Table 3. The seasonal patterns in waterfowl assemblage structures are described by the regions and overall.

	Eastern (19 Lake)			Central (18 Lakes)			Western (17 Lakes)			Total (54 Lakes)
	May	July	September	May	July	September	May	July	September	May	July	September
F.O	40	59	53	71	68	58	59	50	67	152	197	176
Richness	21	13	17	24	27	21	24	21	22	28	27	27
H’	2.44 a	1.59 b	2.33 a	2.57 a	2.12 b	2.20 b	2.49 a	2.46 a	2.63 b	2.65 a	2.39 b	2.56 a
EH	0.54 a	0.37 b	0.60 a	0.54 a	0.31 b	0.37 b	0.50 a	0.55 a	0.63 b	0.50 a	0.40 b	0.48 a
Abundance	10,038 a	18,820 a	23,560 a	6523 a	23,374 b	16,915 b	8774 a	16,205 b	15,432 b	25,335 a	58,399 b	55,907 b
Mean	250.9	318.9	444.5	91.8	343.7	291.6	148.7	324.1	230.2	149.2	329.9	314.4
Std.Error	59.8	83.3	87.9	17.6	86.4	69.2	21.7	50.6	26.9	17.9	44.9	36.4
Max	1972	4038	2581	867	4388	3234	722	1527	1068	1972	4388	3234
Min	8	2	5	2	1	1	2	4	12	2	1	1

Notes: Abundance and diversity metrics with different letters (a, b) in the same row indicate significant differences (p < 0.05); F.O—frequency of observing; H’—waterfowl diversity index (using Shannon index); and E_H—waterfowl evenness index.

). Waterfowl abundance and the species diversity of regional levels showed similar seasonal patterns (Table 3), with a lower abundance of birds in May, followed by a tendency to peak in July and September. The seasonal variation in waterfowl abundance was significantly different in the eastern region (May–July–September; one-way ANOVA, df = 98.78, F = 1.6, p = 0.1), central Region (ANOVA, df = 89.9, F = 7.6, p < 0.01) and the western region (ANOVA, df = 101.2, F = 6.3, p < 0.01) (Table 3).

A Tukey test (all pairwise multiple comparisons) determined that there were differences in species diversity and the evenness of waterfowl surveys from May to September, whereas the diversity and evenness of surveys from July were statistically different from others and clearly lower than that of other months (Figure 2A and Table 3). By contrast, the abundance of twenty-eight waterfowl was higher in July than in other months (ANOVA, df = 302.8, F = 13.07, p < 0.001) (Figure 2B). Additionally, Tukey tests evaluated that the abundance recorded by the surveys in July and September was no different, although both of them differed statistically from the May survey with respect to the abundance of waterfowl.

3.2. Spatial–Seasonal Variations of Waterfowl Diversity and Abundance and with Species Similarity among Lakes

The lakes of eastern Mongolia observed a higher abundance of waterfowl than western and central Mongolian lakes, but not significantly (Table 1 and Figure 2C). In contrast, the species richness of the western and central Mongolian lakes was slightly higher than that of the eastern Mongolian lakes (Table 1 and Table 3). The ANOVA determined that the species richness in the three regions differed statistically (ANOVA, df = 33.6, F = 7.73, p < 0.05).

The NMDS analysis specified 28 species of waterfowl that were affected by regional variables (Figure 3). Tadorna tadorna and Anser cygnoid were highly abundant in the eastern lakes with low altitudes and small sizes. In contrast, Anser fabalis, Anser indicus, Anas acuta, Aythya marila, and Mergus merganser were found in western and central lakes with high altitudes and large lakes. Furthermore, an NMDS (stress = 0.22) analysis of waterfowl abundance based on Bray–Curtis revealed a distinct similar grouping in all three regions. There was no dramatic separation of waterfowl species according to the regional level (PERMANOVA: R² = 0.15, F_2,53 = 1.45, p = 0.1).

3.3. Species Diversity Metric-Lake Size Relationship Pattern

In order to confirm the diversity relationship results, we show the PCA of the diversity metric for the three regions together with the lake surface area, altitude, and longitude (Figure 4). As a general trend, the lakes of the same region are grouped together independently with respect to the environmental factor. For example, the dispersion of the lakes in central and western Mongolia are on the right side and the eastern lakes are on the left side. The dominance index (D’) was negatively correlated with the lake surface area (R = 0.33, p < 0.05) and positively explained the variations in the indices of waterfowl diversity (H’) (R = 0.29, p < 0.05). By contrast, the richness of waterfowl was significantly and positively correlated with the elevation (R = 0.38, p < 0.05). The longitude did not show a significant correlation with the diversity metric and total abundance (p > 0.05) (Figure 4).

4. Discussion and Conclusions

Spatial–seasonal variations and local environmental factors of the individual waterbodies are responsible for structuring aquatic bird assemblages [1,2,6,41]. Based on data collected from 54 Mongolian lakes between 2016 and 2018, this study identified several changes in the waterfowl community that were related to spatial–seasonal features and lake size (their associated wetlands). A high probability existed of observing Aythya fuligula, Aythya ferina, Cygnus Cygnus, and T. ferruginea throughout the lakes. Also, Tadorna ferruginea, Aythya ferina, Anser indicus, and Anser cygnoid were recorded more abundantly than other species during the study period. The first two species (T. ferruginea and A. ferina) were observed commonly throughout the country; however, the composition of waterfowl communities changed spatially with major contributions from A. indicus and A. cygnoid. A. indicus was abundantly observed in the lakes of western and central Mongolia and is mainly attributed to breeds in central Asia, from Kazakhstan and Kyrgyzstan in the extreme east, across southern Russia to western Mongolia and the Qinghai–Tibetan Plateau, south to Ladakh in India, and migrating along the Central Asian flyway [42,43]. By contrast, A. cygnoid were copiously observed in the lakes of eastern Mongolia and some central Mongolian lakes. Studies in the past have indicated a high prevalence of A. cygnoid in eastern Mongolia. In northeastern Mongolia, for instance, the small lakes of Mongol Daguur and Buir Lake support the largest population of A. cygnoid by serving as stopover sites and breeding habitats. Ganga Lake does the same in southeastern Mongolia [15,26,44,45,46]. The global population trend reports announced A. ferina, A. cygnoid, and A. indicus are in a downward trend, the trends of T. ferruginea and C. cygnus are unknown, and the other two species are experiencing an upward trend [22,47,48,49,50]. Accordingly, considering only the common and abundant species, the lakes and their associated wetlands in Mongolia can show a high importance value in waterfowl conservation, particularly for the species whose populations are globally and regionally decreased [15,22,25].

A large number of birds generally arrive in Mongolia by the East Asia—Australia flyway to breed and forage [12,15]. Similarly, according to our study, there appeared to be a higher abundance of waterfowl in Eastern Mongolia than in the western and central Mongolian lakes. This is likely due to differences in habitat availability and water levels between the regions. The PCA showed two main clusters of lake similarity, which comprised the most central Mongolian lakes and all western Mongolian lakes (right side), and some central Mongolian lakes and all Eastern Mongolian lakes (left side). Eastern Mongolian lakes tend to have more wetland and shallow water habitats, while central and western Mongolian lakes tend to have deeper open-water habitats [28]. For this study, these differences in habitat types could contribute more to the observed differences in waterfowl abundance among the regions than different flyways. Non-metric multidimensional scaling (NMDS) was used to demonstrate the geographic dissimilarity of waterfowl species. We did not find any differences in waterfowl community patterns between different lake sizes of lakes and regions in different latitudes. These findings show no significant difference between the species of waterfowl birds distributed in Mongolia; differences were observed only within seasonal and same regions.

The seasonal analysis of waterfowl data showed that the species diversity and evenness indices were higher in May and September than in July. There was no difference in species diversity and the evenness of waterfowl in the surveys from May–September, while the diversity and evenness in July were statistically different from others. A significant difference was, however, not found in the species richness among the study months (27 species in July and September and 28 species in May) for the chosen twenty-eight waterfowl. Another way to put it is that the composition of the selected species was more similar in May and September than in July. This can be explained in part by the seasonal movement of waterfowl during migratory periods. Several studies have found that the temporal variation in species diversity and the evenness of water birds is mainly driven by migration and movement in the northern hemisphere during spring and fall [2,9,51].

A number of studies have indicated that habitat heterogeneity with the increasing size of lakes and their associated wetlands is an influencing factor in the deviation of aquatic bird diversity [2,3,6,7,15,41,51,52,53]. Our study shows that the richness and abundance of waterfowl were not clearly related to the surface area of the lake. Regarding abundance, some small lakes supported a greater number of waterfowl than large ones during the migration terms. This might be attributable to the weak relationship between the lake size and the average abundance, which some papers reported [2,54]. The waterfowl diversity index was positively related to the surface area of the lake, whereas the species dominance index showed a negatively correlation. It might be due to the fact that the increased surface area of the lake decreases the habitat overlap for the designated waterfowl due to habitat heterogeneity [2,6,55]. In other words, there is more chance to select suitable habitats for the waterfowl seeking to breed, rest, and refuel. Accordingly, the composition of the waterfowl species might become relatively equivalent in large lakes, and these indices may increase. The richness in our study was restricted to a certain species of waterfowl; thus, it may not appropriately elucidate the relationship with the size of a lake.

Furthermore, shallow lakes with a large surface area had a tendency to support larger waterfowl assemblages during the migration seasons. The shallowness is also one of the main physical factors influencing the community structure of the water birds (richness and abundance) because the depth prerequisites of various feeding groups overlap [2,6,7,54,56]. Rich food availability also makes the waterfowl more flexible in foraging, and many duck species may have high diet overlap in such a type of “super-abundant” foraging habitat [57]. Generally, waterfowl utilize large amounts of protein during migration, nesting, and molting, and they fulfill this requirement by consuming aquatic invertebrates [58]. As lakes become shallower, they are more likely to be highly diverse in aquatic plants, which support a high number of aquatic invertebrates [54,59,60]. Therefore, the nutritional requirements of waterfowl have been met in shallow lakes and wetlands where diverse aquatic plant growth is abundant [60]. Additionally, the trophic state is a major factor that influences the abundance and richness of species on lakes with shallowness and a high primary productivity [5,6]. On one hand, some small lakes and the groups of small lakes also support the same number and more waterfowl species when compared with some medium-sized and large lakes. For instance, Erveekhii lake and Gun Tsengeleg lake, which was one of the smallest lakes in our study, demonstrated a higher richness than the Khoton, Dayan, Dood Tsagaan, and Telmen lakes, which were medium-sized and large-sized lakes. The four groups of small lakes, which were the Tsengeleg Lakes, Tashgain Tavan Lakes, Teshigiin Olon Lakes, and Uvsiin Baga-Bayan Lakes, had a greater abundance of waterfowl with the same richness compared to larger lakes with an equivalent area. Several studies suggested that a group of small lakes provides nearby alternative feeding sites and a suitably undisturbed breeding habitat for waterfowl and contain high habitat heterogeneity in the wetlands among small lakes [2,7].

Regardless of their size, all lakes and wetlands through certain flyways play a role during waterfowl migration as a stopover site (staging post). These sites are crucial to the success of the birds’ long migratory route, while water birds fly over and lack a direct way around large expanses of land that lack acceptable wetlands and lakes for resting and refueling, such as the Tibetan and Mongolian Plateau [2]. Therefore, the loss of any lakes and wetlands through flyways can have a harmful impact on migratory birds [1,16,61]. The lakes studied are internationally designed as wetlands of great conservation value for threatened species and migratory waterfowl, including the IBAs and the Ramsar sites in Mongolia. These can include, for instance, the lakes of Mongol Daguur, the Valley of Lakes, and Khar–Us Nuur National Park, located along the East Asia–Australia, Central Asian, and Eastern Africa–West Asian flyways [12,13].

Unfortunately, some valuable lakes and wetlands in Mongolia have rapidly shrunk and dried up due to intensive anthropogenic activities around the lakes (e.g., livestock overgrazing, mining, etc.) and climate changes, which have decreased precipitation, increased water evaporation, and increased the air temperature [12,18,19,20,21,22,23]. A rapid drying-out of lakes was reported around Mongolia from 1996 to 2011 in accordance with the study of [62]. Furthermore, Kang and Hong (2016) [18], who analyzed the surface area of 73 lakes in four different regions of Mongolia, identified that the lake area decreased by −9.3% at an annual rate of −53.7 km² yr⁻¹ from 2001 to 2011 for the lakes studied. The study also indicated slight-to-moderate decreases of lake surface area in semi-arid regions (desert steppe) and rapid reductions of lake surface area in arid regions (Gobi Desert). According to their study at Ugii lake, Sumiya et al. (2020) [20] revealed a significant decline in the total precipitation and inflow river discharge and an increase in the total annual evaporation and annual average temperature, as well as an abrupt diminishing of the lake surface area (which reduced by 13.8% over 32 years). However, there is a lack of information on the relationship between the lake surface area reduction and the water birds’ dynamics in Mongolian lakes, in addition to the physical and chemical variations associated with environmental conditions.

In summary, the presence of numerous migratory waterfowl recorded in our study shows that Mongolian lakes are a hotspot habitat for waterfowl birds and are used as breeding and stopover sites. We suggest that land-use changes and anthropogenic threats in Mongolia can have a significant impact on heterogeneity in waterfowl communities among lakes which may be greater than the impact of seasonal movements and migration patterns. Anthropogenic threats, such as overgrazing, mining, and expanding land use, have caused the degradation of wetland habitats, including the loss of vegetation and the degradation of water quality [18,19,21]. This can reduce the availability of food resources and nesting sites for waterfowl, as well as increase their vulnerability to predators and other threats [1,58,63]. There was little indication that changing wetlands and lakes resulted in a waterfowl habitat loss in Mongolia. A further monitoring program and frequent research on lakes and their associated wetlands are crucial for developing fundamental scientific resources for the conservation and management of waterbirds, with a priority on anthropogenically induced impacts on lakes and their surroundings. For instance, the factors should consider the degradation of land, water quality losses, and intense human activities near shorelines.