Volume 14 Issue 1
Feb.  2023
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Article Contents
Abstract
Introduction
Materials and methods
Results
Discussion
Acknowledgements
References
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Hem Bahadur Katuwal, Hari Prasad Sharma, Prashant Rokka, Krishna Prasad Bhusal, Bishnu Prasad Bhattarai, Sabina Koirala, Sandeep Chhetri Luitel, Shailendra Yadav, Ganesh Sah, Hem Sagar Baral, Laxman Prasad Poudyal, Lin Wang, Rui-Chang Quan. 2023: The effects of climate and land use change on the potential distribution and nesting habitat of the Lesser Adjutant in Nepal. Avian Research, 14(1): 100105. DOI: 10.1016/j.avrs.2023.100105
Citation: Hem Bahadur Katuwal, Hari Prasad Sharma, Prashant Rokka, Krishna Prasad Bhusal, Bishnu Prasad Bhattarai, Sabina Koirala, Sandeep Chhetri Luitel, Shailendra Yadav, Ganesh Sah, Hem Sagar Baral, Laxman Prasad Poudyal, Lin Wang, Rui-Chang Quan. 2023: The effects of climate and land use change on the potential distribution and nesting habitat of the Lesser Adjutant in Nepal. Avian Research, 14(1): 100105. DOI: 10.1016/j.avrs.2023.100105
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The effects of climate and land use change on the potential distribution and nesting habitat of the Lesser Adjutant in Nepal

  • a.

    Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, 666303, China

  • b.

    Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences, Yezin, Nay Pyi Taw, 05282, Myanmar

  • c.

    Yunnan International Joint Laboratory of Southeast Asia Biodiversity Conservation, Mengla, Yunnan, 666303, China

  • d.

    Nepal Zoological Society, Kathmandu, 44600, Nepal

  • e.

    Central Department of Zoology, Institute of Science and Technology, Tribhuvan University, Kathmandu, 44600, Nepal

  • f.

    Faculty of Forestry, Agriculture and Forestry University, Hetauda, Makwanpur, 44107, Nepal

  • g.

    IUCN SSC Bird Red List Authority, Rue Mauverney, 1196, Gland, Switzerland

  • h.

    Mithila Wildlife Trust, Janakpurdham, Dhanusa, 45600, Nepal

  • i.

    Zoological Society of London-Nepal Office, Kathmandu, 44600, Nepal

  • j.

    Institute of Land, Water and Society, School of Environmental Sciences, Charles Sturt University, Albury-Wodonga, Australia

  • k.

    Shivapuri-Nagarjun National Park, Department of National Parks and Wildlife Conservation, Kathmandu, Nepal

More Information
  • Corresponding author:

    Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, 666303, China. E-mail address: quanrc@xtbg.ac.cn (R.-C. Quan)

  • Received Date: 19 Jan 2023
  • Rev Recd Date: 23 Apr 2023
  • Accepted Date: 26 Apr 2023
  • Available Online: 07 Oct 2023
  • Publish Date: 13 May 2023
    Graphical Abstract
    • Abstract

  • Climate change and land use change pose a threat to the world's biodiversity and have significant impacts on the geographic distribution and composition of many bird species, but little is known about how they affect threatened large-sized waterbird species that rely on agricultural landscapes. To address this gap, we investigated how climate and land use changes influence the distribution and nesting habitats of the globally vulnerable Lesser Adjutant (Leptoptilos javanicus) in Nepal. Between 2012 and 2023, we collected distribution data from 24 districts and nesting site information from 18 districts. In a nation-wide breeding survey conducted in 2020, we documented a total of 581 fledglings from 346 nests in 109 colonies. The ensemble model predicted a current potential distribution of 15% (21,637 ​km2) and a potential nesting habitat of 13% (19,651 ​km2) for the species in Nepal. The highest predicted current suitable distribution and nesting habitat was in Madhesh Province, while none was predicted in Karnali Province. The majority of this predicted distributional and nesting habitat falls on agricultural landscapes (> 70%). Our model showed a likely range expansion of up to 15% (21,573 ​km2) for the distribution and up to 12% (17,482 ​km2) for the nesting habitat under SSP5–8.5 scenarios for the 2070s. The range expansion is expected to occur mainly within the current distribution and breeding range (Tarai and some regions of Siwalk), particularly in Lumbini and Sudurpashchim provinces, and extend to the northern portions (Siwalik and Mid-hill regions) in other provinces. However, the current Protected Areas and Important Bird and Biodiversity Areas are inadequate for providing optimal habitats for the species. Although the model suggests range expansion, the use of such novel habitats is primarily contingent on the availability and protection of large-sized trees (particularly Bombax ceiba, observed in 65% of colonies) in agricultural regions where nesting occurs. Therefore, our research suggests that agricultural landscapes should be prioritized in management plans for the conservation of the Lesser Adjutant in Nepal.

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  • Tits and titmice are small, familiar cavity-nesting songbirds forming the family Paridae which contains 4 genera, 55 to 65 species, depending on different classifications (Harrap and Quinn, 1996; Salzburger et al., 2002; Dickinson, 2003). They are distributed in the entire Holarctic, Oriental and Afrotropical regions with a hot spot of diversity in the Himalayan and Chinese mountain ranges (Päckert et al., 2007). Because of their overall morphological similarity, all but three species have been classified into the genus Parus and the genus is divided into 10 subgenera (Harrap and Quinn, 1996) or 12 species groups (Eck, 1988). The three other genera, Melanochlora, Sylviparus and Pseudopodoces are monotypic. A well-supported, corroborated and presumably accurate phylogeny is essential for an understanding of ecological and behavioral variation within the group. Therefore, in recent years, a plethora of studies using molecular markers, such as allozyme comparisons (Gill et al., 1989), mitochondrial restriction fragment-length polymorphism (RFLP) data (Gill and Slikas, 1992; Gill et al., 1993), DNA-DNA hybridization distances (Sheldon et al., 1992; Slikas et al., 1996) and cytochrome-b sequences (Kvist et al., 1996; Gill et al., 2005; Martens et al., 2006) have been applied to the phylogeny of Paridae. However, the phylogenetic relationship among species tends to become increasingly controversial as different genetic markers emerge. For instance, based on nuclear DNA-DNA hybridization, Parus caeruleus and P. major formed a clade which is the sister group of all other Parids (Sheldon et al., 1992; Slikas et al., 1996), but the phylogeny inferred from cyt b sequences did not support that result (Gill et al., 2005).

    Aegithalos, at one time, was classified as a genus in the family Paridae (Gadow, 1883; Hellmayr, 1903; Mayr and Amandon, 1951). However, Snow (1967) considered Aegithalos and a few related genera as a separate family, the Aegithalidae. Phylogenetic analyses based on DNA-DNA hybridization (Sibley and Ahlquist, 1990; Sheldon and Gill, 1996), protein allozyme comparisons (Ohta et al., 2000) and nuclear gene sequences (Barker et al., 2002; Spicer and Dunipace, 2004) suggested that Aegithalos was indeed not Parids and the closest sister group to Parids was the penduline tits, species of Remizidae. However, genera closely related to Aegithalos are still under dispute, as well as the phylogenetic relationships within Aegithalos (Päckert et al., 2010).

    In this study, we sampled part of representative taxa of tits, long-tailed tits and penduline tits in an attempt to resolve the relationships among these three groups and also to infer the phylogenetic relationships within tits and long-tailed tits based on two mitochondrial gene sequences, COΙ and cyt b.

    Taxon selection and choice of outgroups

    Altogether, twenty-nine individuals of ten species from Paridae, nine individuals of four species from Aegithalos and two Chinese penduline tits were included in this study. Six species had more than one subspecies included in the analysis (Table 1). According to Sibley and Monroe (1990), Sheldon and Gill (1996), Barker et al. (2002), Spicer and Dunipace (2004), an individual of Pica pica, Uragus sibiricus, Garrulax lunulatus and G. ocellatus were selected as outgroups.

    Extraction, amplification and sequencing

    Genomic DNA was extracted from blood, feathers or tissue specimens using the QIAamp™ DNA Mini Kit as per manufacturer's instructions. Nucleotide sequence data were obtained from the two mitochondrial, cytochrome c oxidase Ⅰ (COI) and cytochrome b (cyt b) genes. PCR amplification and sequencing of cytochrome c oxidase Ⅰ followed the method suggested by Sorenson et al. (1999), while Gill et al. (2005) described protocols for cytochrome b.

    For the sequencing reactions, the same primers were used. Both strands of each PCR product were sequenced. For each gene and sample, multiple sequence fragments were obtained by sequencing with different primers. Complete sequences were assembled using Seqman Ⅱ (DNASTAR®). Sequences were compared visually to the original chromatograms to avoid reading errors. Assembled sequences were aligned by eye. All sequences were deposited in GenBank.

    Phylogenetic analysis

    Based on a priori assumption and partition homogeneity test (p = 0.44), the two mitochondrial genes were analyzed as one data set with a total nucleotide length of 2149 base pairs (bp). The data were analyzed using maximum likelihood (ML, Felsenstein, 1981) and Bayesian inference methods (BI, Rannala and Yang, 1996; Yang and Rannala, 1997; Larget and Simon, 1999). Statistics for nucleotide variation and genetic distance were computed with MEGA 4 (Tamura et al., 2007). A Jukes-Cantor estimate of the number of nucleotide substitutions per site was computed for the cyt b gene (Jukes and Cantor, 1969). Following the suggestion of Nei and Kumar (2000), if the Jukes-Cantor distance is less than 0.05, the p-distance would be used. Otherwise, a more complicated distance model would be employed.

    Following alignment, we partitioned the data by genes in order to allow different rates for the various partitions for ML and BI analyses. Nucleotide substitution models were selected separately by genes and then used for different data partitions in reconstruction. However, the TVM + I + G model (−lnL = 15397.6758, K = 9, AIC = 30813.3156) was identified as the best fit for these two genes, using both the likelihood-ratio test (LRT) and Akaike Information Criterion (AIC) implemented in MODELTEST 3.7 (Posada and Crandall, 1998). The parameter values for the model include a symmetric rate matrix specifying relative probabilities for all possible nucleotide changes (Rmatrix = 0.6396 [A-C], 8.0280 [A-G], 1.1611 [A-T], 0.0498 [C-G], 8.0280 [C-T], 1.0000 [G-T]), the proportion of invariant sites (pinvar = 0.6183) and the shape parameter for the gamma distribution of rate variation (shape = 1.2128). The base frequencies were set as follows: A = 0.3263, C = 0.4100, G = 0.1009, T = 0.1628.

    ML reconstruction (1000 replicates) was performed in TREEFINDER (Jobb, 2007) and BI performed in MRBAYES 3.1.2 (Ronquist and Huelsenbeck, 2003). In the BI analysis, we ran two analyses of two million generations and trees sampled every 100 generations. One cold and three heated Markov chains were used in our analysis. The trees saved during the "burn-in" phase (the first 200000 generations in our analysis) were discarded. The remaining trees from two runs were used to create a 50% majority rule consensus tree.

    Sequence characteristics

    We obtained a total of 88 sequences, with their GenBank accession numbers listed in Table 1. No stop codons were identified in a contiguous 1201 bp stretch of the COI gene and 948 bp of cyt b. The overlapping sequences from different PCR products and a single peak in the electropherograms suggest that these sequences do not come from "numts" (nuclear sequences of mitochondrial origin). The average base composition of sequence was skewed, which is similar to that found in previous avian studies (Barhoum and Burns, 2002; Webb and Moore, 2005). The characteristics of these sequences are summarized in Table 2.

    Table  1.  List of taxonomic samples and sequences used in the study
    Family Genus Species and subspecies Museum No. Collection locality GenBank Accession Nos.
    cyt b COΙ
    Paridae Parus Parus major commixtus IOZ1254 Guangxi HM185345 HM185334
    Parus major subtibetanus IOZ5236 Yunnan HM185346 HM185333
    Parus major subtibetanus IOZ3918 Sichuan HM185347 HM185332
    Parus major artatus IOZ5661 Jilin HM185348 HM185331
    Parus monticolus yunnanensis IOZ3633 Sichuan HM185349 HM185330
    Parus monticolus yunnanensis IOZ2465 Shaanxi HM185350 HM185329
    Parus spilonotus rex IOZ3026 Fujian HM185351 HM185328
    Parus cyanus IOZ 781 Xinjiang HM185352 HM185327
    Parus venustulus IOZ2806 Hubei HM185353 HM185326
    Parus venustulus IOZ1945 Shaanxi HM185354 HM185325
    Parus ater aemodius IOZ1094 Gansu HM185355 HM185324
    Parus ater IOZ2331 Zvolen HM185356 HM185323
    Parus ater ater IOZ9029 Heilongjiang HM185357 HM185322
    Parus palustris hypermelas IOZ1239 Gansu HM185358 HM185321
    Parus palustris hypermelas IOZ7991 Hubei HM185359 HM185320
    Parus palustris brevirostris IOZ5675 Jilin HM185360 HM185319
    Parus palustris hellmayri IOZ8680 Shanxi HM185361 HM185318
    Parus palustris hellmayri IOZ2458 Shaanxi HM185362 HM185343
    Parus montanus baicalensis IOZ5944 Heilongjiang HM185363 HM185317
    Parus montanus baicalensis IOZ5945 Heilongjiang HM185364 HM185316
    Parus montanus IOZ2237 Zvolen HM185365 HM185315
    Parus montanus affinis IOZ2178 Shaanxi HM185366 HM185342
    Parus dichrous dichrous IOZ2489 Shaanxi HM185367 HM185314
    Parus dichrous dichrous IOZ6117 Shaanxi HM185368 HM185313
    Parus cristatus IOZ2333 Zvolen HM185369 HM185312
    Sylviparus Sylviparus modestus modestus KIZglgs1240 Yunnan HM185370 HM185311
    Sylviparus modestus modestus KIZglgs1241 Yunnan HM185371 HM185310
    Pseudopodoces Pseudopodoces humilis IOZ4783 Qinghai HM185372 HM185309
    Pseudopodoces humilis IOZ4785 Qinghai HM185373 HM185308
    Remizidae Remiz Remiz consobrinus IOZ10640 Liaoning HM185374 HM185298
    Remiz consobrinus IOZ10652 Liaoning HM185375 HM185297
    Aegithalidae Aegithalos Aegithalos caudatus caudatus IOZ5677 Jilin HM185376 HM185307
    Aegithalos caudatus glaucogularis IOZ2769 Hubei HM185377 HM185306
    Aegithalos caudatus glaucogularis IOZ3322 Shaanxi HM185378 HM185305
    Aegithalos concinuus concinnus IOZ1152 Gansu HM185379 HM185304
    Aegithalos concinuus concinnus IOZ1499 Hunan HM185380 HM185303
    Aegithalos concinuus concinnus IOZ3661 Sichuan HM185381 HM185302
    Aegithalos concinuus talifuensis IOZ5344 Yunnan HM185382 HM185301
    Aegithalos bonvaloti IOZ3766 Sichuan HM185383 HM185300
    Aegithalos fuliginosus IOZ2476 Shaanxi HM185384 HM185337
    Timaliidae Garrulax Garrulax lunulatus IOZ2594 Shaanxi HM185385 HM185341
    Garrulax ocellatus IOZ5083 Yunnan HM185386 HM185340
    Fringillidae Uragus Uragus sibiricus IOZ5870 Heilongjiang HM185387 HM185344
    Corvidae Pica Pica pica IOZ3931 Xinjiang HM185388 HM185339
    Note: IOZ, Institute of Zoology, Chinese Academy of Sciences; KIZ, Kunming Institute of Zoology, Chinese Academy of Sciences.
     | Show Table
    DownLoad: CSV
    Table  2.  Molecular characterization of the sequences
    Genes No. of sequences Total sites Variable sites (%) Avg R (si/sv) Nucleotide frequencies
    A (%) T (%) G (%) C (%)
    COΙ 40 1201 370 1.7 25.8 23.8 17.3 33.1
    cyt b 40 948 326 1.5 26.6 23.8 13.2 36.3
     | Show Table
    DownLoad: CSV

    Pairwise genetic distances

    Because the mean Jukes-Cantor distance was 0.112 ± 0.006 SE (> 0.05) for the cyt b sequence data set, the Tamura-Nei model was chosen to compute the genetic distance (Tamura and Nei, 1993). Sequence divergences within species range from 0% (Parus dichrous) to 2.8% (Aegithalos concinnus), with an average divergence of 1.15%. The mean cyt b sequence distance of Aegithalos was 0.081 ± 0.007 SE, with the lowest 0.002 between A. bonvaloti and A. fuliginosus and the highest 0.118 between A. concinnus and A. caudatus. The mean distance of genus Parus was 0.077 ± 0.005 SE, with the lowest 0.053 between P. major and P. monticolus. Between taxa in Parus and the other two species in the Paridae, average pairwise divergences are as follows: 0.115 ± 0.009 SE to Sylviparus modestus and 0.097 ± 0.007 SE to Pseudopodoces humilis. The distances were 0.16 ± 0.01 SE between Aegithalos and Paridae, 0.18 ± 0.013 SE between Aegithalos and Remizidae, and 0.126 ± 0.01 SE between Paridae and Remizidae.

    Phylogenetic relationships

    The consensus tree from the Bayesian analysis is identical to the ML tree, except for a few weakly supported nodes. A few nodes that are resolved in the ML tree are polytomies in the Bayesian consensus tree (Fig. 1). In all optimal trees, no species which includes several subspecies were found to be paraphyletic in our study. Paridae, Remizidae, Aegithalos and Garrulax species formed a monophyletic group with high support (bootstrap support = 70%, Bayesian posterior probability = 97%) and branched off to two monophyletic clades. The clade, representing individuals from species of Paridae and Remidae, was highly supported (bootstrap = 98%, BPP = 100%). Remiz consobrinus positions as a sister species to the Paridae, including Sylviparus, Pseudopodoces and the species in Parus. Aegithalos is monophyletic, grouped with two Garrulax species and, with weak support, formed the other clade.

    Figure  1.  Trees obtained from the analysis of the combined COΙ and cyt b data: (a) Bayesian and (b) maximum likelihood. The optimal model as estimated by Modeltest following the AIC and LRT was estimated to be TVM + I + G. Support values are indicated to the left of the nodes.
    DownLoad: Full-Size Img PowerPoint

    Within Aegithalos, four species are monophyletic and grouped in all optimal trees (Bayesian posterior probability = 100%, bootstrap = 100%). Within the clade, Aegithalos bonvaloti is sister to A. fuliginosus and that pair is sister to A. caudatus. Aegithalos concinnus is sister to these three species. Phylogenetic relationships have strong support (Bayesian posterior probability = 100%, bootstrap > 95%) and are identical in the two phylogenetic trees.

    Within the family Paridae, Sylviparus modestus positions as a sister species to the remaining species of Paridae from the two trees. These remaining species form two high-support monophyletic clades in the BI tree (BPP = 99%), but the bootstrap value is rather low (bootstrap = 44%) in the ML tree. One clade includes Parus cyanus, P. monticolus, P. major, P. spilonotus and Ps. humilis. The relationships among these five species are congruent in the two trees except for the position of Ps. humilis. In the two trees, Parus cyanus is a sister species to the remaining species, although the nodal support value is low. Parus major and P. monticolus pair as sister taxa with high support. In the BI tree, P. spilonotus and Ps. humilis pair as sister taxa but in the ML tree, Pseudopodoces humilis is a sister species to P. spilonotus, P. major and P. monticolus. However, the nodal supports are low. Another clade includes P. ater, P. venustulus, P. palustris, P. montanus and two Eurasian crested tits, P. dichous and P. cristatus. Parus palustris and P. montanus, P. ater and P. venustulus, P. dichous and P. cristatus pair as sister taxa with high support. Relationships among these three pairs are unclear because of polytomies in the BI tree and low nodal support value in the ML tree.

    Phylogenetic relationships among Paridae, Remizidae and Aegithalos

    Our data support the classification for the family Paridae proposed by Sibley and Ahlquist (1990). Based on DNA-DNA hybridization, they combined family Remizidae with Paridae, hence the family Paridae includes two subfamilies, Remizinae and Parinae. Sheldon and Gill (1996) studied the phylogeny of song birds using DNA-DNA hybridization and concluded that the sister group of Paridae is the Remizidae. Based on combined myoglobin intron Ⅱ and cytochrome b sequences, Alström et al. (2006) revealed the close relationships between P. major and R. pendulnus. In our study, the Chinese penduline tit (Remizidae) positioned as sister group to the Parids (Paridae) with high support. This may indicate very close relationships between Paridae and Remizidae. Although, in the present study, only one species of Remizidae was tested, the high nodal support (> 95%) signifies that the designated branch is most possibly unaffected by sampling among variation existing in the data (Slikas et al., 1996).

    Long-tailed tits, species of Aegithalos, because of their morphological similarity with tits, were earlier believed to be Parids by several authors (Gadow, 1883; Hellmayr, 1903; Mayr and Amandon, 1951). However, Stresemann (1923) described several characteristics of Aegithalos that differ from those of the Parids, such as the presence of a complete juvenile-molt, nest structure and naked hatching. Since then, Aegithalos and two other monotypic or small genera are usually placed in the family Aegithalidae (e.g., Paynter, 1967; Morony et al., 1975; Sibley and Ahlquist, 1990; Sibley and Monroe, 1990). Sturmbauer et al. (1998) suggested a close relationship between Leptopoecile and Aegithalos based on the mitochondrial 16S sequence. Alström et al. (2006) confirmed the close relationship between Aegithalos and Leptopoecile based on the combined myoglobin intron Ⅱ and cytochrome b sequences. Using protein allozyme comparison, Ohta et al. (2000) found the genetic distance between Aegithalos and Parus appears to be at a familial level. In our study, two distinct clades and Aegithalos grouped with two outgroup Garrulax species, in spite of weak nodal support, show distant relationships between Aegithalos and Paridae. In addition, the genetic divergence of cyt b between Aegithalos and Paridae is larger than that between Remizidae and Paridae. Hence, the morphological similarity between tits and long-tailed tits may have resulted from evolutionary convergence.

    Phylogenetic relationships within Paridae

    Based on plumage pattern, Hellmayr (1903) had recognized eleven subgenera for the genus Parus. However, the delimitation of these subgenera is in dispute. For instance, Wolters (1982) classified the species of Pardaliparus into Pariparus and this classification was supported by molecular analyses (Slikas et al., 1996; Gill et al., 2005). In our study, Parus ater and P. venustulus also formed a closely related group, but the divergence of cyt b is ~7% (uncorrected p-distance). According to Hellmayr's classification, our samples belong to seven subgenera: Cyanistes (P. cyanus), Baeolophus (P. dichous, P. cristatus), Poecile (P. montanus, P. palustrs), Periparus (P. ater), Pardaliparus (P. venustulus), Machlolophus (P. spilonotus) and Parus (P. major, P. monticolus). Similar to previous studies, our data did not reveal phylogenetic relationships among these subgenera. Therefore, the Parus phylogeny needs to be studied further. We intend to add more species and subspecies and new markers, including nuclear loci to classify this challenge in the future.

    Although our results came to quite similar conclusions as previous studies, different phylogenetic relationships among species were detected as well. The question of greatest interest is: what is the phylogentically most closely related species to Ps. humilis in Parids? This aberrant and enigmatic Tibetan species, earlier thought to be a corvid, turned out to be a Parid (James et al., 2003). Past phylogenetic analyses based on cyt b gene sequences positioned Ps. humilis as sister species to P. major (James et al., 2003; Gill et al., 2005). However, in optimal trees based on the cyt b and COΙ gene sequences in our study, Ps. humilis is sister to P. spilonotus, although the nodal support is weak. This result may indicate that more data of the species and different markers are needed to determine the phylogenetic status of Parids.

    Gill et al. (2005) recommended upgrading six subgenra of Parus into genera for facilitating future evolutionary analyses among Parids. The retained genus Parus only included P. major, P. monticolus, P. xanthogenys, P. spilonotus, P. holsti and the African tits (P. leucomelas, P. niger, P. carpi, P. albiventris, P. leuconotus, P. rufiventris, P. funereus, P. fringillinus, P. fasciiventer, P. thruppi, P. griseiventris, P. cinerascens and P. afer). However, in our present study, we also believe that the genus Machlolophus should be recognized in consideration of the phylogenetic relationships between P. spilonotus and Ps. humilis and distinct plumage pattern between P. major and P. spilonotus (Ohta et al., 2000). Furthermore, in our data, the divergence of the cyt b gene between P. major–P. monticolus group and P. spilonotus (8.4%, uncorrected p-distance) is no less than the divergence among recommended genera (ranging from 7.3% between Pariparus and Baeolophus to 9.7% between Poecile and Machlolophus, uncorrected p-distance).

    Intra- and interspecies relationships and history of Aegithalos taxa

    On the one hand, intraspecific divergence is significant. The Black-throated Tit (Aegithalos concinnus) includes six highly distinct subspecies. These subspecies are remarkably different in their plumage pattern. Divergence differences of the cyt b gene among these subspecies are also significant. In our data, the pairwise p-distance between specimens from Bengal (India, ssp. iredalei, sequence obtained from GenBank) and Gaoligong (Yunnan, ssp. talifuensis) was 4.5%. p-distance between specimens from Gaoligong and Pingjiang (Hunan, ssp. concinnus) was 6.1%. p-distance between specimens from Bengal and Pingjiang was 5.1%. Eck and Martens (2006) sequenced three specimens, including subspecies ssp. iredalei, ssp. talifuensis and ssp. manipurensis, and they found the pairwise p-distance was 5.1% between ssp. iredalei and ssp. talifuensis, 5.3% between ssp. talifuensis and ssp. manipurensis and 6% between ssp. iredalei and ssp. manipurensis. These four subspecies are reddish-crowned. The other two subspecies A. c. pulchellus and A. c. annamensis are grey-headed. They are obviously different in presence of reddish breast band, the latter of which is absent. Hence, it seems possible that A. concinnus represents an unresolved species swarm (Eck and Martens, 2006).

    As for the Long-tailed Tit (Aegithalos caudatus), based on comparative morphology, up to 19 subspecies are currently recognized, divided by Harrap and Quinn (1996) into four groups. Zink et al. (2005) studied the mitochondrial phylogeography, including five subspecies or representatives of A. caudatus group and A. alpinus group of the long-tailed tit. Within their samples, no correspondence between five subspecies and mitochondrial subdivision has been discovered. However, two geographically unsorted lineages were displayed and differentiation seems to exist between the two main groups. In this study, the cyt b divergence of two specimens belonging to the subspecies A. c. caudatus and A. c. glaucogularis, is 1.3%. Thus, phylogeographic structures would be developed if additional subspecies were taken into consideration.

    On the other hand, interspecies molecular divergence is small. The morphologically distinct sister species A. fuliginosus and A. bonvaloti are separated by unexpectedly small cyt b divergences (0.2%, uncorrected p-distance) and associated very short branch lengths in the cyt b tree. The pairwise cyt b divergence between the species is comparable to that within populations of the same species in other passerine birds. This could indicate recent separation and divergence from their common ancestor. However, surprisingly, the more slowly evolving nuclear locus β-fibrinogen intron 7 shows relatively greater divergence (2.5%, uncorrected p-distance) than the faster-evolving cyt b (unpublished data). This might be the result of amplification of nuclear pseudogenes instead of mitochondrial DNA (Zhang and Hewitt, 1996; Sorensen and Quinn, 1998). However, our sequences show no evidence of being of nuclear origin. Introgression of mitochondrial DNA seems to be a more likely explanation. A. fuliginosus and A. bonvaloti are not known to hybridize, but their current distributions partly overlap. Hybridization or past hybridization leading to introgression is nevertheless a possibility. Weckstein et al. (2001) argued that introgressive hybridization is the cause of discordant patterns of mitochondrial and allozyme data in the North American sparrows Zonotrichia leucophrys and Z. Atricapilla.

    Furthermore, species limits within the A. niveogularis are not, as yet, reliably defined. Harrap and Quinn (1996) proposed the species to be split in two species while Dickinson (2003) proposed a three way split. Therefore, currently, five (Martens and Eck, 1995) or six (Harrap and Quinn, 1996) or seven (Dickinson, 2003) species have been recognized within the genus Aegithalos. Our study includes only a few species and subspecies from Aegithalos because of insufficient or unavailable samples. Recently, Päckert et al. (2010) studied the phylogeny of long-tailed tits and allies based on mitochondrial and nuclear markers and resolved the status of some species on the basis of phylogenetic relationships. However, by considering the long evolutionary time of species and differences within species, both morphological and molecular characters, a study which includes more species and subspecies is necessary to define the phylogeny of Aegithalos.

    We suggest that the southwestern mountain ranges of China might be the center of origin of Aegithalos species and that the taxa of this genus colonized new habitats from west to east across China. Supporting this hypothesis are the patterns of taxonomic diversity and endemism. For example, members of all long-tailed tits are found in the areas of southwestern China except A. niveogularis. The oldest linage in the genus in our study is the A. concinnus talifuensis which is distributed in Yunnan Province of China. The historical biogeography can be deduced by the relationships among species and the areas of species distribution (Gill et al., 2005). For instance, the closely related phylogenetic relationships between Aegithalos fuliginosus and A. bonvaloti is accompanied by a partly overlapped distribution. Aegithalos caudatus caudatus is older than A. c. glaucogularis in our phylogenetic analysis and is thus distributed farther from the original areas than A. c. glaucogularis. Given a rough calibration of 2% divergence per million years, we hypothesize that the separation of A. concinnus may occur ~5.5 Mya, on the basis of the estimate of 11% sequence divergence between A. concinnus and other three species. Then, about 4.5 Mya ago, A. caudatus was divided and colonized the palearctic region. More recently, separation between Aegithalos fuliginosus and A. bonvaloti is hypothesized to have taken place in the late Pleistocene, i.e., ~100000 years ago. However, that break may be earlier than late Pleistocene, for the possible introgression between two species may obscure the real separation time.

    Congruent genetic differentiation among co-distributed species

    Comparative phylogeography helped elucidate the relative effect of shared historical earth events on current patterns of biodiversity by comparing historical patterns of gene flow and divergence among species that overlap in time and space (Hickerson et al., 2010). In other words, co-distribution species may have similar population genetic differentiation or congruent phylogeographical patterns as a result of sharing common environmental and geological changes. In our study, the Great Tit (Parus major) and the Black-throated Tit (A. concinnus) overlap in southern and southwestern China, the Coat Tit (P. ater), the Willow Tit (P. montanus), the Marsh Tit (P. palustris) and the Long-tailed Tit are distributed in the northeast, center and west of China. Although our sample size was small, we found congruent genetic differentiation among these sympatric distribution taxa. The great tit and the black-throated tit have similar phylogeographical patterns. They differentiated into two clades, one including the samples of Yunnan Province and the other one belonging to the other sample locations in China. Similarly, the coat tit, the marsh tit, the willow tit and the long-tailed tit also divided into two branches, one covering the areas of northeastern China and Europe and the other including the species distribution in central and western China. These phylogeographical patterns or population structures of sympatric species may indicate that the historical earth events they experienced, including climatic and geological, had almost the same effect on these closely related taxa.

    We are grateful to Tao Li for laboratory assistance and anonymous reviewers who provided helpful comments to the improvement of the manuscript. This work was financially supported by the National Natural Science Foundation of China (Grant No. 30870270) and the National Science Funds for Distinguished Young Scientists (No. 30925008) to Fumin Lei.

    • References (87)
  • Adhikari, P., Kim, B.J., Hong, S.H., Lee, D.H., 2022. Climate change induced habitat expansion of nutria (Myocastor coypus) in South Korea. Sci. Rep. 12, 3300.
    Allouche, O., Tsoar, A., Kadmon, R., 2006. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43, 1223–1232.
    Araújo, M.B., New, M., 2007. Ensemble forecasting of species distributions. Trends Ecol. Evol. 22, 42–47.
    Awan, M.N., Saqib, Z., Buner, F., Lee, D.C., Pervez, A., 2021. Using ensemble modeling to predict breeding habitat of the red-listed Western Tragopan (Tragopan melanocephalus) in the Western Himalayas of Pakistan. Glob. Ecol. Conserv. 31, e01864.
    Baral, B., Bhandari, S., Koirala, S., Bhandari, P., Magar, G., Basnet, D.R., et al., 2020. First distributional record of the lesser adjutant Leptoptilos javanicus Horsfield, 1821 (Ciconiiformes: Ciconiidae) from Sindhuli district, Nepal. J. Threat. Taxa 12, 17028–17031.
    Baral, H.S., Inskipp, C., 2005. Important bird areas in Nepal: key sites for conservation. In: Bird Conservation Nepal and BirdLife International (Kathmandu and Cambridge).
    Baral, S., Kunwar, A., Adhikari, D., Kandel, K., Mandal, D.N., Thapa, A., et al., 2023. The potential distribution of the yellow monitor, Varanus flavescens (Hardwick & Gray) under multiple climate, land cover and dispersal scenarios in Nepal. Wildl. Res. .
    Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W., Courchamp, F., 2012. Impacts of climate change on the future of biodiversity. Ecol. Lett. 15, 365–377.
    Bhattarai, B.P., Adhikari, J.N., Rijal, M., 2021. Nesting habitat selection and challenges of conservation of the vulnerable Lesser Adjutant Leptoptilos javanicus (Horsfield, 1821) in the Chitwan National Park, Nepal. Ornis Hung. 29, 33–46.
    BirdLife International, 2021. Species factsheet: Leptoptilos javanicus. . (Accessed 3 August 2021).
    Boria, R.A., Olson, L.E., Goodman, S.M., Anderson, R.P., 2014. Spatial filtering to reduce sampling bias can improve the performance of ecological niche models. Ecol. Model. 275, 73–77.
    Bradley, A.P., 1997. The use of the area under the ROC curve in the evaluation of machine learning algorithms. Pattern Recogn. 30, 1145–1159.
    Brambilla, M., Rubolini, D., Appukuttan, O., Calvi, G., Karger, D.N., Kmecl, P., et al., 2022. Identifying climate refugia for high-elevation alpine birds under current climate warming predictions. Global Change Biol. 28, 4276–4291.
    Chapagain, D., Dhaubanjar, S., Bharati, L., 2021. Unpacking future climate extremes and their sectoral implications in western Nepal. Clim. Change 168, 8.
    Chhetri, B., Badola, H.K., Barat, S., 2021. Modelling climate change impacts on distribution of Himalayan pheasants. Ecol. Indicat. 123, 107368.
    Chhogyel, N., Kumar, L., 2018. Climate change and potential impacts on agriculture in Bhutan: a discussion of pertinent issues. Agric. Food Secur. 7, 79.
    Coad, L., Watson, J.E.M., Geldmann, J., Burgess, N.D., Leverington, F., Hockings, M., et al., 2019. Widespread shortfalls in protected area resourcing undermine efforts to conserve biodiversity. Front. Ecol. Environ. 17, 259–264.
    Coetzee, B.W.T., Gaston, K.J., Chown, S.L., 2014. Local scale comparisons of biodiversity as a test for global protected area ecological performance: a meta-analysis. PLoS One 9, e105824.
    Condro, A.A., Syartinilia Higuchi, H., Mulyani, Y.A., Raffiudin, R., Rusniarsyah, L., Setiawan, Y., et al., 2022. Climate change leads to range contraction for Japanese population of the Oriental Honey-Buzzards: implications for future conservation strategies. Glob. Ecol. Conserv. 34, e02044.
    D'Amour, C.B., Reitsma, F., Baiocchi, G., Barthel, S., Güneralp, B., Erb, K.H., et al., 2017. Future urban land expansion and implications for global croplands. Proc. Nat. Acad. Sci. USA 114, 8939–8944.
    DNPWC, BCN, 2022. Birds of Nepal: an Official Checklist. Department of National Parks and Wildlife Conservation and Bird Conservation Nepal, Kathmandu, Nepal.
    Elith, J., Leathwick, J.R., 2009. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 40, 677–697.
    Elliott, A., Garcia, E.F.J., Boesman, P.F.D., 2020. Lesser adjutant (Leptoptilos javanicus), version 1.0. In: del Hoyo, J., Elliott, A., Saragata, J., Christie, D.A., de Juana, E. (Eds.), Birds of the World. Cornell Lab of Ornithology, Ithaca, NY.
    Fick, S.E., Hijmans, R.J., 2017. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315.
    Fois, M., Cuena-Lombraña, A., Fenu, G., Cogoni, D., Bacchetta, G., 2016. The reliability of conservation status assessments at regional level: past, present and future perspectives on Gentiana lutea L. ssp. lutea in Sardinia. J. Nat. Conserv. 33, 1–9.
    Fonseca, C.R., Venticinque, E.M., 2018. Biodiversity conservation gaps in Brazil: a role for systematic conservation planning. Perspect. Ecol. Conserv. 16, 61–67.
    Fusco, J., Walker, E., Papaïx, J., Debolini, M., Bondeau, A., Barnagaud, J.Y., 2021. Land use changes threaten bird taxonomic and functional diversity across the Mediterranean Basin: a spatial analysis to prioritize monitoring for conservation. Front. Ecol. Evol. 9, 612356.
    Garcia, R.A., Cabeza, M., Rahbek, C., Araújo, M.B., 2014. Multiple dimensions of climate change and their implications for biodiversity. Science 344, 1247579.
    Ghimire, P., 2019. A review of studies on climate change in Nepal. Geogr. Base 6, 11–20.
    Ghosh-Harihar, M., An, R., Athreya, R., Borthakur, U., Chanchani, P., Chetry, D., et al., 2019. Protected areas and biodiversity conservation in India. Biol. Conserv. 237, 114–124.
    Gula, J., Sundar, K.S.G., Willows-Munro, S., Downs, C.T., 2023. The state of stork research globally: a systematic review. Biol. Conserv. 280, 109969.
    Gulati, H., Rana, S., 2021. Nest characteristics and breeding success of Sarus Crane, Antigone antigone (Linnaeus, 1758) (Aves: Gruidae) in different habitats at Dhanauri Wetland, Uttar Pradesh, India. Record Zool. Surv. India 121, 205–210.
    Hamal, K., Sharma, S., Baniya, B., Khadka, N., Zhou, X., 2020. Inter-annual variability of winter precipitation over Nepal coupled with ocean-atmospheric patterns during 1987-2015. Front. Earth Sci. 8, 161.
    Hausfather, Z., 2018. Explainer: how 'Shared Socioeconomic Pathways' explore future climate change. .
    Hijmans, R.J., 2022. raster: geographic data analysis and modeling. R package version 3.5-29. .
    Hijmans, R.J., Cameron, S.E., Parra, J.L., Jones, P.G., Jarvis, A., 2005. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25, 1965–1978.
    Hilaluddin Shah, J.N., Shawl, T.A., 2003. Nest site selection and breeding success by Cattle Egret and Little Egret in Amroha, Uttar Pradesh, India. Waterbirds 26, 444–448.
    Inskipp, C., Baral, H.S., Phuyal, S., Bhatt, T., Khatiwada, M., Inskipp, T., et al., 2016. The Status of Nepal's Birds: the National Red List Series. Zoological Society of London, United Kingdom.
    Jetz, W., Wilcove, D.S., Dobson, A.P., 2007. Projected impacts of climate and land-use change on the global diversity of birds. PLoS Biol. 5, 1211–1219.
    Kar, T., Debata, S., Mundkur, T., 2021. Population, breeding phenology, and factors affecting breeding success of River Tern (Sterna aurantia) in Eastern India. Waterbirds 44, 308–316.
    Karki, R., Gurung, A., 2012. An overview of climate change and its impact on agriculture: a review from least developing country, Nepal. Int. J. Ecosyst. 2, 19–24.
    Karki, R., ul Hasson, S., Schickhoff, U., Scholten, T., Böhner, J., 2017. Rising precipitation extremes across Nepal. Climate 5, 4.
    Karki, S., Thapa, T.B., 2013. Population status, nesting habitat selection and conservation threats of lesser adjutant stork (Leptoptilos javanicus) in the eastern lowlands of Nepal. Conserv. Sci. 1, 27–35.
    Kattel, G.R., 2022. Climate warming in the Himalayas threatens biodiversity, ecosystem functioning and ecosystem services in the 21st century: is there a better solution? Biodivers. Conserv. 31, 2017–2044.
    Katuwal, H.B., Rai, J., Tomlinson, K., Rimal, B., Sharma, H.P., Baral, H.S., et al., 2022a. Seasonal variation and crop diversity shape the composition of bird communities in agricultural landscapes in Nepal. Agric. Ecosyst. Environ. 333, 107973.
    Katuwal, H.B., Sundar, K.S.G., Zhang, M., Rimal, B., Baral, H.S., Sharma, H.P., et al., 2022b. Factors affecting the breeding ecology of the globally threatened Lesser Adjutant Leptoptilos javanicus in agricultural landscapes of Nepal. Avian Conserv. Ecol. 17, 15.
    Kearney, S.G., Adams, V.M., Fuller, R.A., Possingham, H.P., Watson, J.E.M., 2020. Estimating the benefit of well-managed protected areas for threatened species conservation. Oryx 54, 276–284.
    Khadka, K.K., Pandey, R., 2014. Changes in the distribution of Lesser Adjutant Storks (Leptoptilos javanicus) in South and Southeast Asia: a plausible evidnce of global climate change and land-use change effect. Int. J. Zool. Res. 10, 9–14.
    Koju, R., Maharjan, B., Gosai, K.R., Kittur, S., Sundar, K.S.G., 2019. Ciconiiformes nesting on trees in cereal-dominated farmlands: importance of scattered trees for heronries in lowland Nepal. Waterbirds 42, 355–365.
    Lamsal, P., Kumar, L., Atreya, K., Pant, K.P., 2017. Vulnerability and impacts of climate change on forest and freshwater wetland ecosystems in Nepal: a review. Ambio 46, 915–930.
    Langham, G.M., Schuetz, J.G., Distler, T., Soykan, C.U., Wilsey, C., 2015. Conservation status of North American birds in the face of future climate change. PLoS One 10, e0135350.
    Li, M., Zhou, H., Bai, J., Zhang, T., Liu, Y., Ran, J., 2022. Distribution of breeding population and predicting future habitat under climate change of Black-Necked Crane (Grus nigricollis Przevalski, 1876) in Shaluli Mountains. Animals 12, 2594.
    Li, X., Chen, G., Liu, X., Liang, X., Wang, S., Chen, Y., et al., 2017. A new global land-use and land-cover change product at a 1-km resolution for 2010 to 2100 based on human-environment interactions. Ann. Assoc. Am. Geogr. 107, 1040–1059.
    Liu, C., Berry, P.M., Dawson, T.P., Pearson, R.G., 2005. Selecting thresholds of occurrence in the prediction of species distributions. Ecography 28, 385–393.
    Liu, C.Y., Gélin, U., He, R.C., Li, H., Quan, R.C., 2021. Flexible breeding performance under unstable climatic conditions in a tropical passerine in Southwest China. Zool. Res. 42, 221–226.
    Lobo, J.M., Jiménez-valverde, A., Real, R., 2008. AUC: a misleading measure of the performance of predictive distribution models. Global Ecol. Biogeogr. 17, 145–151.
    LRMP, 1986. Land Resources Mapping Project. Kenting Earth Sciences, HMGN and Government of Canada, Land Resources Mapping Project, Kathmandu.
    Marmion, M., Parviainen, M., Luoto, M., Heikkinen, R.K., Thuiller, W., 2009. Evaluation of consensus methods in predictive species distribution modelling. Divers. Distrib. 15, 59–69.
    Mishra, V., Kumar, D., Ganguly, A.R., Sanjay, J., Mujumdar, M., Krishnan, R., et al., 2014. Reliability of regional and global climate models to simulate precipitation extremes over India. J. Geophys. Res. Atmos. 119, 9301–9323.
    Mitra, A., Chatterjee, C., Mandal, F.B., 2011. Synthetic chemical pesticides and their effects on birds. Res. J. Environ. Toxicol. 5, 81–96.
    Moradi, S., Sheykhi Ilanloo, S., Kafash, A., Yousefi, M., 2019. Identifying high-priority conservation areas for avian biodiversity using species distribution modeling. Ecol. Indicat. 97, 159–164.
    Naimi, B., Araújo, M.B., 2016. Sdm: a reproducible and extensible R platform for species distribution modelling. Ecography 39, 368–375.
    Naimi, B., Hamm, N.A.S., Groen, T.A., Skidmore, A.K., Toxopeus, A.G., 2014. Where is positional uncertainty a problem for species distribution modelling? Ecography 37, 191–203.
    Oppel, S., Meirinho, A., Ramírez, I., Gardner, B., O'Connell, A.F., Miller, P.I., et al., 2012. Comparison of five modelling techniques to predict the spatial distribution and abundance of seabirds. Biol. Conserv. 156, 94–104.
    Pang, R.H., Yu, T.L., Busam, M., 2019. Low breeding success of the little egret (Egretta garzetta) near residential areas and in colonies exposed to gales: a comparison of colony in Sichuan, Southwest China, with literature. Anim. Cell. Syst. 23, 235–240.
    Pant, G., Maraseni, T., Apan, A., Allen, B.L., 2021. Predicted declines in suitable habitat for greater one-horned rhinoceros (Rhinoceros unicornis) under future climate and land use change scenarios. Ecol. Evol. 11, 18288–18304.
    R Core Team, 2021. R: a Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna. .
    Ramamohan, H., Rao, K.K., 2017. Breeding Success and Mortality Rates in the Spot-Billed Pelican (Pelecanus philippensis), at Telineelapuram Bird Protected Areas, (An IBA Site; in 229) Srikakulam District, Andra Pradesh, India, vol. 143. Indian For, pp. 1064–1070.
    Riahi, K., van Vuuren, D.P., Kriegler, E., Edmonds, J., O'Neill, B.C., Fujimori, S., et al., 2017. The shared socioeconomic pathways and their energy, land use, and greenhouse gas emissions implications: an overview. Global Environ. Change 42, 153–168.
    Rimal, B., Sloan, S., Keshtkar, H., Sharma, R., Rijal, S., Shrestha, U.B., 2020. Patterns of historical and future urban expansion in Nepal. Rem. Sens. 12, 628.
    Riordan, E.C., Montalvo, A.M., Beyers, J.L., 2018. Using species distribution models with climate change scenarios to aid ecological restoration decisionmaking for southern California shrublands. In: Research Paper—Pacific Southwest Research Station. USDA Forest Service. PSW-RP-270.
    Sagi, O., Rokach, L., 2018. Ensemble learning: a survey. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 8, e1249.
    Santangeli, A., Lehikoinen, A., Bock, A., Peltonen-Sainio, P., Jauhiainen, L., Girardello, M., et al., 2018. Stronger response of farmland birds than farmers to climate change leads to the emergence of an ecological trap. Biol. Conserv. 217, 166–172.
    Sharma, H.P., Rimal, B., Zhang, M., Sharma, S., Poudyal, L.P., Maharjan, S., et al., 2020. Potential distribution of the critically endangered Chinese pangolin (Manis pentadactyla) in different land covers of Nepal: implications for conservation. Sustainability 12, 1282.
    Sharma, S., 2006. Population status and distribution of Lesser Adjutant (Leptoptilos javanicus) in far-western lowland Nepal. Tigerpaper 33, 9–11.
    Sundar, K.S.G., 2011. Agricultural intensification, rainfall patterns, and large waterbird breeding success in the extensively cultivated landscape of Uttar Pradesh, India. Biol. Conserv. 144, 3055–3063.
    Sundar, K.S.G., Koju, R., Maharjan, B., Marcot Bruce, G., Kittur, S., Gosai, K.R., 2019. First assessment of factors affecting the breeding success of two stork species in lowland Nepal using Bayesian network models. Wildfowl 69, 45–69.
    Sundar, K.S.G., Maharjan, B., Koju, R., Kittur, S., Gosai, K.R., 2016. Factors affecting provisioning times of two stork species in lowland Nepal. Waterbirds 39, 365–374.
    Sundar, K.S.G., Yaseen, M., Kathju, K., 2018. The role of artificial habitats and rainfall patterns in the unseasonal nesting of Sarus Cranes (Antigone antigone) in South Asia. Waterbirds 41, 80–86.
    Tatebe, H., Ogura, T., Nitta, T., Komuro, Y., Ogochi, K., Takemura, T., et al., 2019. Description and basic evaluation of simulated mean state, internal variability, and climate sensitivity in MIROC6. Geosci. Model Dev. (GMD) 12, 2727–2765.
    Tehrani, N., Naimi, B., Jaboyedoff, M., 2020. Toward community predictions: multi-scale modelling of mountain breeding birds' habitat suitability, landscape preferences, and environmental drivers. Ecol. Evol. 10, 5544–5557.
    Thuiller, W., Lafourcade, B., Engler, R., Araújo, M.B., 2009. BIOMOD: a platform for ensemble forecasting of species distributions. Ecography 32, 369–373.
    Trautmann, S., 2018. Climate change impacts on bird species. In: Tietze, D.T. (Ed.), Bird Species, How They Arise, Modify and Vanish. Springer Nature, Switzerland, pp. 217–234.
    Wagle, Y., Bhattarai, B.P., Adhikari, J.N., 2022. Factors influencing distribution and habitat utilisation of Leptoptilos javanicus in and around Barandabhar Corridor Forest, Chitwan, Nepal. Nat. Conserv. Res. 7, 19–26.
    Walther, G., Post, E., Convey, P., Menzel, A., Parmesank, C., Beebee, T.J.C., et al., 2002. Ecological response to recent climate cnahge. Nature 416, 389–395.
    Wiens, J.J., 2016. Climate-related local extinctions are already widespread among plant and animal species. PLoS Biol. 14, e2001104.
    Yang, B., Qin, S., Xu, W., Busch, J., Yang, X., Gu, X., et al., 2020. Gap analysis of Giant Panda conservation as an example for planning China's National Park System. Curr. Biol. 30, 1287–1291.
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