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Article

Dominated Taxonomic and Phylogenetic Turnover but Functional Nestedness of Wetland Bird Beta Diversity in North China

by
Fan Yang
1,†,
Zhuoen Liu
2,†,
Guisheng Yang
1 and
Gang Feng
2,*
1
School of Life Sciences, Inner Mongolia University, Hohhot 010070, China
2
Ministry of Education Key Laboratory of Ecology and Resource Use of the Mongolian Plateau, School of Ecology and Environment, Inner Mongolia University, Hohhot 010070, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Land 2022, 11(7), 1090; https://doi.org/10.3390/land11071090
Submission received: 20 June 2022 / Revised: 13 July 2022 / Accepted: 14 July 2022 / Published: 15 July 2022
(This article belongs to the Special Issue Biodiversity Investigation and Conservation in China: Current Status, Challenges, and Perspectives)
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Abstract

:
The decomposition of taxonomic, phylogenetic, and functional beta diversity into their turnover and nestedness components could provide novel insights into biodiversity conservation, e.g., provide implications for the Single Large Or Several Small reserves debate (SLOSS debate). Due to dramatic climate change and massive anthropogenic activities in recent decades in North China, the wetlands and the associated biodiversity in this region have declined significantly. This study applied the taxonomic, phylogenetic, and functional beta diversity decomposition for the first time in wetland bird communities in North China, aiming to propose scientific and comprehensive suggestions for bird diversity conservation in this region. A paired t-test was used to compare the differences between taxonomic, phylogenetic, and functional turnover, and their nestedness components. In addition, a spearman correlation analysis was used to assess the associations between each explanatory variable (differences in mean annual temperature and mean annual precipitation, as well as spatial distances) and each beta diversity index. A total of 546 bird species were found in 38 wetlands in North China, with three critically endangered species, 19 endangered species, 22 vulnerable species, and 61 near threatened species. The number of threatened species (critically endangered, endangered, and vulnerable) found in these lakes was about 30% of all threatened species in China. The results showed that taxonomic and phylogenetic beta diversity among wetland bird communities in North China was mainly dominated by turnover, while functional beta diversity was mainly dominated by nestedness. Importantly, the phylogenetic and functional results showed similar patterns even after controlling for the effects of taxonomic beta diversity. In addition, the taxonomic and phylogenetic turnover was more associated with both climate variables and spatial distances than other components. The contrasting patterns among the taxonomic, phylogenetic, and functional decompositions of wetland bird communities in North China indicate that distinctive conservation strategies should be considered for different biodiversity dimensions. Specifically, the conservation of taxonomic and phylogenetic bird diversity in this region should focus on multiple wetlands, while the conservation of bird functional diversity should focus on a single wetland with high functional diversity.

1. Introduction

Due to their high productivity and diverse habitat types, wetland ecosystems are of crucial importance in terms of both harboring extremely high biodiversity and providing valuable ecosystem functioning and services for human beings [1,2,3]. Although only covering a very low proportion (less than 1%) of the Earth’s surface, wetland ecosystems are home to about one third of vertebrate species and many species of other groups [2,4,5]. In addition to the high biodiversity, wetland ecosystems could sequester and store high proportions of carbon and play an important role in mitigating the accelerated climate change [6]. Lastly, wetland ecosystems also provide many other valuable ecosystem services for human beings, e.g., human health, cultural, and educational services [3].
However, the unprecedented global changes in the Anthropocene, including climate change, land-use changes, biological invasion, overexploitation, and pollution, have posed great threats and have caused damage to wetland ecosystems’ functioning, services, as well as biodiversity [1,7,8]. For example, wetland ecosystems are disappearing at a rate three times faster than forest ecosystems [2,9]. Compared with terrestrial ecosystems and marine ecosystems, the freshwater Living Planet Index has fallen more steeply from 1970 to 2016, declining by 84% (ranges from 77% to 89%), which is about 4% per year since 1970 [7]. There is also a higher proportion of freshwater-associated threatened vertebrate species, according to the International Union for Conservation of Nature Red List [10,11].
Consistent with these global patterns, China’s lakes are also experiencing dramatic changes in recent decades [12,13,14]. More importantly, most of China’s lakes are mainly distributed in North China, i.e., Heilongjiang province, the Inner Mongolia Autonomous Region, the Xinjiang Autonomous Region, Qinghai province, and the Tibet Autonomous Region [13,15]. In addition, both the number and area of lakes in these regions have decreased significantly in recent decades, mainly driven by massive anthropogenic activities, e.g., irrigation-dominated in the cultivated area and coal mining-dominated in the grassland area [12,14]. These massive changes would have serious adverse effects on the wetlands’ biodiversity as well as wetland ecosystem functioning and services. However, as far as we know, few studies have investigated the biodiversity distribution patterns in these lakes in North China, especially from the perspective of phylogenetic and functional beta diversity (including the turnover and nestedness components), which could provide novel insights into their biodiversity conservation and ecosystem restoration [16,17,18].
Compared with taxonomic diversity, which treats different species as ecological equivalents, phylogenetic diversity and functional diversity could reflect the evolutionary and functional differences among species, respectively [19,20]. In addition, beta diversity could also be decomposed into the turnover and nestedness components, which mean species replacement, and species gains or losses between biotic communities, respectively [16,17]. The relative importance of the turnover and nestedness components could inform on strategies for biodiversity conservation [16,17]. For example, dominance of the turnover component suggests that different investigation sites or biotic communities need to be better protected, while dominance of the nestedness component emphasizes the need for strict protection of a single important site or biotic community [17,18].
Therefore, to better conserve the wetland bird diversity in North China, this study assesses the taxonomic, phylogenetic, and functional turnover and nestedness components of bird communities among different wetlands in this region. We aimed (a) to test if the phylogenetic and functional decompositions of beta diversity show consistent patterns with taxonomic decomposition; (b) to understand how the taxonomic, phylogenetic, and functional beta diversity components are affected by climate differences and spatial distances, and (c) to provide comprehensive and scientific suggestions for bird diversity conservation in wetlands in North China.

2. Materials and Methods

2.1. Bird Community Data in Wetlands in North China

Bird community data in wetlands in North China were collected from published scientific papers with full bird species lists. These papers were searched, selected, and downloaded from xueshu.baidu.com, which includes databases from both English and Chinese scientific journals. “Wetland bird diversity”, “river bird diversity”, and “lake bird diversity” were the keywords used in the search for related papers. Only scientific papers with investigations on birds lasting more than one year (or covering at least four seasons) were retained for further beta diversity analyses to ensure sufficient sampling efforts. Finally, the bird community data from 546 species (including 438 breeding species, which is the focus of beta diversity-related analyses) in 38 wetlands were extracted from 34 papers (Figure 1). Among the 38 wetlands, the bird species lists in 35 wetlands were created from investigations of the species. Only three wetlands had bird species lists created from combined efforts, i.e., investigations into species combined with existing information on bird occurrence. The investigation times of these studies ranged from 1990 to 2015. Any threatened statuses for these bird species were checked with a published paper that was based on the standard of International Union for Conservation of Nature (IUCN) and extended by many experienced ornithologists in China [21].

2.2. Functional Traits and Phylogeny

Body size, trophic level, and habitat specificity of the 438 breeding birds found in the 38 wetlands were used for the functional beta diversity analyses. These key functional traits are closely related to birds’ energy requirements, resource utilization, and sensitivity to habitat changes. Gower’s distances (could deal with both continuous traits and categorical traits) of these traits among all species pairs were used to represent the functional dissimilarity between all species pairs. The functional distance matrix was then used in a principal coordinate analysis (PCoA). Additionally, a matrix composed by the first three axes of the PCoA was finally used to calculate the functional beta diversity.
A phylogeny including the 432 breeding birds was built from a global bird phylogeny (six species could not be found in the global phylogeny) [24]. The option of ‘Hackett All Species: a set of 10,000 trees with 9993 OUTs each’ was selected first. Then, 5000 trees from the pseudo-posterior distribution were sampled. Finally, a maximum clade credibility tree using mean node heights was calculated in TreeAnnotator using the BEAST package [25]. The resulting phylogeny was used for the subsequent phylogenetic beta diversity relate analyses.

2.3. Environmental Variables

The contemporary climate variables of each wetland, including mean annual precipitation (MAP) and mean annual temperature (MAT), were collected from WorldClim database (https://www.worldclim.org/) [26]. These two variables are widely recognized as the main factors affecting the biodiversity distribution patterns through their direct and indirect effects [27,28]. The Euclidean distances of the MAT and MAP were then used to represent the environmental filtering. The spatial distances among all wetland pairs were calculated to represent the dispersal limitation.

2.4. Statistics

Taxonomic, functional, and phylogenetic beta diversity as well as their turnover and nestedness components were calculated based on pairwise-site dissimilarity methods, using the Sorensen index [29]. To control the effects of taxonomic beta diversity on functional and phylogenetic beta diversity, the standardized effect sizes (SESs) of functional and phylogenetic beta diversity were also calculated using the following formula:
SESbeta = (betaobs − mean(betarnd))/sd(betarnd)
where betaobs is the observed functional/phylogenetic beta diversity (includes their turnover and nestedness components) and betarnd is the functional/phylogenetic beta diversity (includes their turnover and nestedness components) of null modeled bird communities (randomly shuffles species labels in the bird community data while maintaining species richness and species numbers shared among bird communities for 999 times).
A paired t-test was used to compare the differences between taxonomic turnover and taxonomic nestedness, between functional turnover and functional nestedness, and between phylogenetic turnover and phylogenetic nestedness. A Spearman correlation analysis was used to assess the associations between each explanatory variable (distances between the mean annual temperature and the mean annual precipitation, as well as spatial distances) and each beta diversity index (taxonomic nestedness and turnover, functional nestedness and turnover, and phylogenetic nestedness and turnover). Because most of these six dependent variables (observed beta diversity indices) were skewed, all of them were transformed using a square root function to make them normally distributed.
In addition, the differences between standardized functional turnover and standardized functional nestedness, and between standardized phylogenetic turnover and standardized phylogenetic nestedness were also compared using the paired t-test. These four dependent variables were not transformed because they were normally distributed.

3. Results

3.1. Threatened Status of These Bird Species

A total of 546 bird species (including both breeding and nonbreeding bird species) were found in the 38 lakes in North China, which was about 40% of all bird species in China (compared with the information from Zheng 2011) [30]. Notably, there were three critically endangered species, 19 endangered species, 22 vulnerable species, and 61 near threatened species. The number of threatened species (critically endangered, endangered, and vulnerable) found in these lakes was about 30% of all threatened species in China.

3.2. Comparisons of Taxonomic, Functional, and Phylogenetic Turnover against Their Nestedness Component

The mean pairwise taxonomic beta diversity was 0.68, while the mean taxonomic turnover component was 0.52 and the mean taxonomic nestedness component was 0.15. The mean pairwise functional beta diversity was 0.24, while the mean functional turnover component was 0.04 and the mean functional nestedness component was 0.19. The mean pairwise phylogenetic beta diversity was 0.47, while the mean phylogenetic turnover component was 0.30 and the mean phylogenetic nestedness component was 0.17.
The paired t-test showed that taxonomic turnover was significantly higher than taxonomic nestedness (t = 34.23, p < 0.01, mean differences = 0.35) and that phylogenetic turnover was also significantly higher than phylogenetic nestedness (t = 15.22, p < 0.01, mean differences = 0.15) but that functional turnover was significantly lower than functional nestedness (t = −21.42, p < 0.01, mean differences = 0.21, Figure 2). The standardized functional and phylogenetic beta diversity showed similar patterns (Figure 3). Specifically, the standardized phylogenetic turnover was also significantly higher than the standardized phylogenetic nestedness (t = 7.82, p < 0.01, mean differences = 0.70), but standardized functional turnover was significantly lower than standardized functional nestedness (t = −3.38, p < 0.01, mean differences = 0.30, Figure 3).

3.3. Associations between Different Beta Diversity Component and Explanatory Variables

The Spearman correlation analysis indicated that taxonomic and phylogenetic turnover was significantly and positively correlated with the three explanatory variables, while functional turnover was poorly associated with the explanatory variables (Table 1). In addition, taxonomic nestedness was significantly but negatively correlated with the explanatory variables, although the associations were not high (Table 1).

4. Discussion

Being the first study on the decomposition of the turnover and nestedness components of wetland bird beta diversity in North China, the results showed that the taxonomic and phylogenetic beta diversity of bird communities among 38 wetlands was dominated by turnover while functional beta diversity was dominated by nestedness. Notably, the phylogenetic and functional patterns did not change even after controlling for the effects of taxonomic beta diversity. In addition, the taxonomic and phylogenetic turnover was highly associated with both climate differences and spatial distances.

4.1. Diverse Bird Species Found in These Lakes

Due to the high productivity and diverse habitats around wetland, it has been widely proven that wetlands harbor extremely high biodiversity, including many different taxon groups and many threatened species [2,3,31]. Consistent with these studies, we also found that the wetlands in North China harbored high bird diversity, with 546 bird species and 44 threatened bird species only in 38 wetlands, which is 40% and 30% of all bird species and all threatened bird species in China. This finding emphasizes the importance of these wetlands for bird diversity conservation in China.

4.2. Higher Taxonomic and Phylogenetic Turnover but Lower Functional Turnover

The higher taxonomic and phylogenetic turnover than their nestedness components indicated that changes in the wetland bird community composition in North China were mainly driven by species and lineage replacement rather than species and lineage loss [18,32]. This finding suggests that conservation of all wetlands is needed to protect the bird taxonomic and phylogenetic diversity in this region [16,18]. In contrast, the lower functional turnover than functional nestedness indicated that changes in the wetland bird functional composition were mainly caused by functional diversity loss, rather than functional replacement [18,33]. Therefore, a different conservation strategy is needed for protecting the wetlands’ bird functional diversity in North China, i.e., to protect the few wetlands with high functional diversity [16,18].
Our results were consistent with those of many previous studies [18,32,33]. For example, dominated taxonomic replacement and functional nestedness were also found for waterbird communities across anthropogenic subsidence wetlands in the North China Plain, suggesting that the taxonomic turnover may be mainly driven by functionally redundant species [33]. In addition, an avian study in riparian Amazonian habitats also found dominated taxonomic and phylogenetic replacements, highlighting the crucial role of transition zones and ecotones for avian taxonomic and phylogenetic diversity conservation [32].

4.3. Better Explained Taxonomic and Phylogenetic Turnover

The distribution patterns of beta diversity are mainly shaped by two mechanisms, i.e., environmental filtering and dispersal limitation [18,34,35]. These two mechanisms are usually represented by climate differences and spatial distances at large scales [18,28]. The results in this study showed that the dominated taxonomic turnover and phylogenetic turnover was highly associated with temperature and precipitation differences as well as spatial distances, indicating that both environmental filtering and dispersal limitation have affected the bird diversity distributions in wetlands in North China. Consistent with this finding, the study in riparian Amazonian habitats also found that taxonomic replacement and phylogenetic replacement of avian communities were significantly correlated with the climate gradient [32]. In contrast to the high associations between explanatory variables and taxonomic, phylogenetic turnover, the low correlations between functional beta diversity and each predictor, as well as the relatively lower functional beta diversity (in terms of both the turnover and nestedness components) may suggest that the strong environmental filtering in North China has left a significant legacy on the functional diversity of wetland bird communities in this region. In addition, the significant and negative (relatively weak) correlations between taxonomic nestedness and each explanatory variable may suggest that larger differences in environmental situations may result in different species pool and, therefore, promote lower nestedness.

5. Conclusions

North China contains most of China’s lakes, which have decreased in terms of both number and area in recent decades due to both rapid climate change and massive anthropogenic activities, e.g., agriculture irrigation and coal mining [12,14]. These changes in lakes would further affect their high biodiversity, indicating the importance of scientific biodiversity conservation in this region. The contrasting patterns of the decompositions of taxonomic, phylogenetic, and functional beta diversity suggest that different conservation strategies should be implemented to protect the multiple dimension of bird diversity in North China. The high associations between climate differences, and taxonomic and phylogenetic turnover also indicate that the adverse effects of future climate change on bird diversity should also be considered for the biodiversity conservation in this region.

Author Contributions

Conceptualization, G.F.; methodology, F.Y. and Z.L.; software, F.Y. and Z.L.; validation, F.Y. and Z.L.; formal analysis, F.Y. and Z.L.; investigation, F.Y. and G.Y.; resources, G.Y.; data curation, F.Y. and Z.L.; writing—original draft preparation, G.F., F.Y. and Z.L.; writing—review and editing, G.F., F.Y. and Z.L.; visualization, F.Y. and Z.L; supervision, G.F. and G.Y.; project administration, G.F. and G.Y.; funding acquisition, G.F. All authors have read and agreed to the published version of the manuscript.

Funding

G.F. was supported by the National Key R&D Program of China (2019YFA0607103) and the National Natural Science Foundation of China (41861004).

Conflicts of Interest

The authors declare no conflict of interest.

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Land 11 01090 g001 550
Figure 1. Distribution patterns of the 38 wetlands with relatively sufficient sampled bird community data (yellow points) in North China. The different colors in the background mean different vegetation types, which is based on the information from Vegetation of China [22]. The red line is the border between North and South China, which was revised based on the information from [23].
Figure 1. Distribution patterns of the 38 wetlands with relatively sufficient sampled bird community data (yellow points) in North China. The different colors in the background mean different vegetation types, which is based on the information from Vegetation of China [22]. The red line is the border between North and South China, which was revised based on the information from [23].
Land 11 01090 g001
Land 11 01090 g002 550
Figure 2. Results of the paired t-test of taxonomic nestedness against taxonomic turnover, functional nestedness against functional turnover, and phylogenetic nestedness against phylogenetic turnover. Taxonomic and phylogenetic turnover was significantly higher than their nestedness components. In contrast, functional turnover was significantly lower than functional nestedness. The circles in the figure were some extreme values.
Figure 2. Results of the paired t-test of taxonomic nestedness against taxonomic turnover, functional nestedness against functional turnover, and phylogenetic nestedness against phylogenetic turnover. Taxonomic and phylogenetic turnover was significantly higher than their nestedness components. In contrast, functional turnover was significantly lower than functional nestedness. The circles in the figure were some extreme values.
Land 11 01090 g002
Land 11 01090 g003 550
Figure 3. Results of the paired t-test of standardized functional and standardized phylogenetic turnover against their nestedness components. Nestedness of standardized functional beta diversity was significantly higher than its turnover component. In contrast, nestedness of standardized phylogenetic beta diversity was significantly lower than its turnover component. The circles in the figure were some extreme values.
Figure 3. Results of the paired t-test of standardized functional and standardized phylogenetic turnover against their nestedness components. Nestedness of standardized functional beta diversity was significantly higher than its turnover component. In contrast, nestedness of standardized phylogenetic beta diversity was significantly lower than its turnover component. The circles in the figure were some extreme values.
Land 11 01090 g003
Table
Table 1. Spearman correlations between explanatory variables and taxonomic, functional, phylogenetic turnover and nestedness. MAT is differences in mean annual temperature; MAP is differences in mean annual precipitation; and dispersal is spatial distance. * p < 0.05; ** p < 0.01.
Table 1. Spearman correlations between explanatory variables and taxonomic, functional, phylogenetic turnover and nestedness. MAT is differences in mean annual temperature; MAP is differences in mean annual precipitation; and dispersal is spatial distance. * p < 0.05; ** p < 0.01.
TaxonomicFunctionalPhylogenetic
TurnoverNestednessTurnoverNestednessTurnoverNestedness
MAT0.44 **−0.08 *−0.040.070.38 **0.01
MAP0.52 **−0.12 **0.050.10 *0.45 **0.03
Dispersal0.42 **−0.12 **0.0100.33 **−0.03
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MDPI and ACS Style

Yang, F.; Liu, Z.; Yang, G.; Feng, G. Dominated Taxonomic and Phylogenetic Turnover but Functional Nestedness of Wetland Bird Beta Diversity in North China. Land 2022, 11, 1090. https://doi.org/10.3390/land11071090

AMA Style

Yang F, Liu Z, Yang G, Feng G. Dominated Taxonomic and Phylogenetic Turnover but Functional Nestedness of Wetland Bird Beta Diversity in North China. Land. 2022; 11(7):1090. https://doi.org/10.3390/land11071090

Chicago/Turabian Style

Yang, Fan, Zhuoen Liu, Guisheng Yang, and Gang Feng. 2022. "Dominated Taxonomic and Phylogenetic Turnover but Functional Nestedness of Wetland Bird Beta Diversity in North China" Land 11, no. 7: 1090. https://doi.org/10.3390/land11071090

APA Style

Yang, F., Liu, Z., Yang, G., & Feng, G. (2022). Dominated Taxonomic and Phylogenetic Turnover but Functional Nestedness of Wetland Bird Beta Diversity in North China. Land, 11(7), 1090. https://doi.org/10.3390/land11071090

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