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Article

Nesting Habitat Selection and Suitable Breeding Habitat of Blue-Crowned Laughingthrush: Implication on Its Habitat Conservation

by
Xinjie Huang
,
Shan Tian
,
Zhengxiao Liu
and
Jiliang Xu
*
School of Ecology and Nature Conservation, Beijing Forestry University, Beijing 100083, China
*
Author to whom correspondence should be addressed.
Forests 2023, 14(6), 1139; https://doi.org/10.3390/f14061139
Submission received: 11 April 2023 / Revised: 29 May 2023 / Accepted: 30 May 2023 / Published: 31 May 2023
(This article belongs to the Special Issue Population Dynamics, Behaviour Preference and Habitat Conservation of Forest Birds)
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Abstract

:
Understanding the impact of human disturbance on the breeding habitat selection of endangered species is critical to improving their conservation. Blue-crowned Laughingthrush Pterorhinus courtoisi (Ménégaux, 1923) syn. Garrulax courtoisi (Passeriformes: Leiotrichidae) is an endangered species in China. To explore the nesting habitat selection of the Blue-crowned Laughingthrush and its response to human disturbance during the breeding period, we conducted a field survey at its nesting sites in Wuyuan County and Dexing City, Jiangxi Province, from March to July 2021 and in June 2022. At the home range scale (200 m) the results of a principal component analysis (PCA) showed that this species had a clear preference for infrastructure construction, grassland, farmland and bare land. At the microhabitat scale (12.26 m), we compared the ecological parameters of a nest plot and control plot using a Kruskal–Wallis H test and found that there were significant differences in the vegetation coverage, crown breadth, shrub coverage, herb maximum height, herb average height and herb species number of the nesting area between the two groups. Ensemble species distribution models showed that the suitable habitat of the Blue-crowned Laughingthrush covered an area of 108.67 km2. Distance to waterways, deciduous broadleaved forests and roads were the main factors impacting the habitat distribution of the Blue-crowned Laughingthrush. Our study suggests that (1) it is highly important to improve the protection of breeding sites and suitable living areas close to the settlements and preserve a certain nesting habitat selection space for the Blue-crowned Laughingthrush during the breeding period; and (2) it is necessary to continue to monitor the potential suitable breeding habitat. This study provides a scientific basis for the protection of the Blue-crowned Laughingthrush by local forestry bureaus and conservation departments in the future.

1. Introduction

Habitats provide birds with sufficient food resources, suitable breeding sites and protection from natural enemies and adverse weather conditions, thus ensuring their survival and reproduction [1,2]. Nesting habitat selection is influenced by multiple factors such as temperature [3], food abundance [4], interspecific competition [5], vegetation coverage [6] and human disturbance [7,8,9]. Increasing human activities are the main factors affecting the nesting habitat selection of birds [10]. Previous studies have shown that changes in land-use patterns due to historical causes can further affect nesting habitat selection [11,12]. A recent study has also demonstrated that increases in human activities and frequent disturbance over the years have had a negative impact on bird habitat utilization [13]. For example, a study has shown that historical factors that arise from human activities, i.e., changes in land-use types, can powerfully shape the suitable habitat distribution of Reeves’ pheasant, Syrmaticus reevesii (J. E. Gray, 1829) (Galliformes: Phasianidae) [14]. The breeding period is an exceptionally important link in bird life history, and reproductive success is strongly influenced by habitat quality [2]. In addition, vegetation of the nesting habitat can provide a shelter for birds; therefore, understanding the habitat requirements of birds will contribute to management and conservation actions [15,16]. However, as human activities expand and intensify in recent years, an increasing degree of disturbance poses a significant threat to bird nesting habitats [17,18].
Nesting habitat selection is usually affected by habitat quality and can be used to model species distributions with conservation concerns. Nowadays, thanks to a wide application of species distribution models (SDMs), the researchers have simulated the change in habitat distribution and achieved remarkable results [19,20]. However, the experts have pointed out that because of the uncertainty of various models, the results of habitat prediction or assessment using a single model may be unreliable [21,22]. Meanwhile, ensemble species distribution models (ESDMs) have become an increasingly popular tool for predicting the occupancy of rare species [23,24]. ESDMs usually forecast and evaluate multiple single models (e.g., MaxEnt, Random Forest, boosting Regression Trees, etc.) through integrated methods such as mathematical mean or median, weighted averages and scaling predictions based on model evaluation statistics, and then output an averaged distribution result. This method greatly reduces the generalization error of a single model method [25,26,27]. Many researchers have compared the performance between ESDMs and a single model and found that ESDMs have a better prediction ability than a single model [24,28]. Using the prediction of suitable habitat distribution for Red Back Shrike (Lanius collurio) through multi-model fitting as an example, its advantages and reliability are demonstrated by comparing and evaluating the accuracy of six modeling techniques [29]. The results predicted by modeling can also reflect a trend in nesting habitat selection.
The Blue-crowned Laughingthrush, Pterorhinus courtoisi (Ménégaux, 1923) syn. Garrulax courtoisi, hereafter BCLT, belongs to order Passeriformes, family Leiotrichidae. It is an extremely endangered bird endemic to China [30,31], and has been listed as Critically Endangered (CR) on the IUCN Red List (Red List ver 3.1) since 2018 (https://www.iucnredlist.org/species/22732350/131890764, accessed on 28 March 2023). This species is a forest specialist species that generally occurs in broadleaved forest habitats with older trees [32,33]. Previous studies have shown that human activities such as construction of highways, new houses and buildings can cause it to abandon its nesting sites [30]. Currently, it is still unclear whether historical human activities affect its nesting habitat selection. However, few studies have evaluated the habitat selection of BCLT in the breeding period by aggregating previous research data on this species and using habitat prediction models.
The population size of BCLT has been maintained at a markedly low level by various types of human disturbance, including infrastructure construction, nesting trees cutting, tourism and so on over the past 20 years, and has not increased significantly since the establishment of natural reserves [30,32,33]. Therefore, we conducted our field survey on BCLT during the breeding period and aimed to: (1) identify habitat and microhabitat features suitable for nesting BCLT; (2) analyze the potential suitable breeding habitat distribution of BCLT. This study may provide a theoretical basis for the conservation and management of BCLT.

2. Method

2.1. Study Area

We investigated BCLT in a hilly region south of the Yangtze River in Wuyuan County (117°21′–118°12′ E, 29°01′–29°34′ N) and Dexing City (28°38′–29°17′ N, 117°22′–118°06′ E) in northeast Jiangxi Province. The two counties have a subtropical humid monsoon climate with warm temperatures, abundant rainfall, short frost periods and distinct seasons (http://www.jxwy.gov.cn, http://www.dxs.gov.cn, accessed on 10 April 2021). Wuyuan County and Dexing City are bounded by a section of the Le’an River, along which there are several main habitats for the Blue-crowned Laughingthrush with a relatively fixed breeding period (Figure 1). The dominant vegetation in the study area is subtropical evergreen broadleaved forest [33]. Chinese sweet gum, Liquidambar formosana (Hance, 1866) (Saxifragales: Altingiaceae), Chinese wingnut, Pterocarya stenoptera (C. de Candolle, 1862) (Fagales: Juglandaceae), Chinese hackberry, Celtis sinensis, (Pers., 1805) (Rosales: Cannabaceae) and Camphor tree, (Cinnamomum camphora ((L.) J. Presl, 1825) (Laurales: Lauraceae), etc., are common tree species in this region. The population size of BCLT in these areas ranged from 300 to 334 based on continuous monitoring statistics, and the nest number of BCLT was found in the range of 20 to 50 each year from 2012 to 2016 [30,34].

2.2. Data Collection

2.2.1. Occurrence of BCLT

In order to compare the historical distribution and current situation for the BCLT, we carried out a field survey on the nests of this species with the help of the patrols from Wuyuan Bird National Nature Reserve Management and the local forestry department. These patrols monitored the BCLT for many years, and they were familiar with the distribution and nest sites of the BCLT during those years. According to the field monitoring, they found the BCLT did not use some sites as nest sites, whereas the BCLT occurred in some new sites and bred. Cooperating with these patrols, we carried out a full-coverage survey in Wuyuan County and Dexing City during the breeding season (March to June) for BCLT in 2021 and 2022, respectively, on the sites where the BCLT had been distributed over the past 20 years. The survey was conducted every 3 days and was repeated 12 times in total. A total of 20 points were surveyed, including all sites that have been found before and sites that were newly discovered. For places that have existed before but were not found now, they were determined via a song playback method. Those that have not been found in multiple investigations are identified as “unoccupied breeding sites”, and sites where BCLTs were actually found as “recorded breeding sites”. For areas that have never been discovered before but have environmental characteristics similar to the nesting habitat of BCLTs during the breeding season, the song playback method was also used to find possible new nesting sites. The recording of songs of BCLT (a 54-s playback) was played consecutively at each survey site, with an interval of 2 min. In order not to affect the normal life of birds or alarm them, the observation point was set at a certain distance from the nesting trees with good concealability to record the location of breeding small groups when BCLT flied over.
At each survey site, longitude and latitude were recorded with an accuracy within 10 m via GPS (GPSMAP 60CSX, Garmin Inc. Kansas City, MO, USA).

2.2.2. Nesting Habitat Characteristic

The nesting habitat characteristics were analyzed at two scales: the home range scale (i.e., meso-scale) and micro-scale. At the meso-scale, in order to compare the bird preference for land-use types, circular research areas were established with a radius of 200 m in recorded breeding sites and unoccupied breeding sites according to the home range area of the BCLT [35]. The central point of the nesting tree group served as the plot center at the sample plots of the nesting sites, while the control plot coordinates of nests that have been recorded previously served as the plot center at those of the unoccupied sites. The surveyed area at each point was about 0.1 km2, with the total surveyed area being about 2 km2. The shortest distance between two adjacent breeding sites was 0.59 km, and the longest 12.44 km. There was no overlap between all breeding sites studied. Based on the Classification of Current Land Use Status issued by The State Council in 2017 and the standard classification referred to GB/T21010-2017, we divided land-use types of breeding sites into the following 7 categories: bare land, farmland, forest land, forest–grass mixed area, grassland, infrastructure construction and water area. Additionally, we used the track-recording and manual mapping capabilities of tagged outdoor helpers (field trip data recording software) to mark the boundaries of various land-use types. We imported the classified data in a kml format recorded outdoors into ArcGIS software and converted them into vector surface elements. The projection coordinate system used in this study was WGS_1984_UTM_zone_49N. After that, we converted vector data into raster data. Then, all the breeding areas were classified according to the presence and absence of the BCLT. Finally, the land-use type map of the recorded and unoccupied breeding sites was obtained via a statistical analysis of the raster data with ArcMap 10.2.
At the micro habitat scale, the standard nest plot was circular and 0.05 ha in extent (12.26 m radius) [36], in which nesting trees served as the plot center. In total, 11 ecological variables were recorded (Table 1). In order to select the control plot, 30-m resolution land cover maps of Wuyuan County and Dexing City were divided into 1 km × 1 km grids in advance, and the control grids were randomly selected from these grids. Subsequently, the control plots were selected in these control grids when they had not been occupied by the BCLT in recent years, were far from the nesting areas and their habitat conditions were similar to the nesting areas. A total of 36 nest plots and 30 control plots were investigated.

2.2.3. Environmental Variables Used by SDMs

Environmental factors, including topography, land cover and human disturbance can affect the presence of BCLT [32,33,37]. This study modeled the occurrence and suitable habitat of the BCLT using the above three groups of factors. We first obtained topographic data (aspect, altitude, and slope) from a digital elevation model (DEM). Then, we downloaded land-use/land cover data from Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC). There were ten land cover types in land cover maps, including Grassland, Shrubland, Cultivated land, Forest, Water bodies, Wetland, Impervious surface, Tundra, Bare land, Permanent snow and ice. The resolution of the land cover data was resampled to 30 m in consistency with the topographic data. Human disturbance was represented by the distance to roads (including highways, provincial highways, expressways, railways, etc.). To minimize the multicollinearity between model variables, the Band Collection Statistics tool in the Spatial Analyst extension of ArcMap was employed to calculate the correlations among variables [38]. Subsequently, in total ten variables were selected to model the occurrence and suitable habitat of the BCLT (Table 2).

2.3. Data Processing

2.3.1. Data Analysis

Principal Component Analysis (PCA) was used to determine the nesting habitat selection preference in two groups (recorded breeding sites and unoccupied breeding sites), and only the first and second principal components were retained [39,40]. The values of the ecological factors data were normalized using the arctangent function, and data among all survey groups were averaged before analysis. One-way analysis of variance (one-way ANOVA) or a Kruskal–Wallis H test was used to compare the difference between the nest plot and control plot. If the data passed the homogeneity of variance test, one-way ANOVA was used; otherwise, a Kruskal–Wallis H test was used to test the difference significance of the environmental variables.

2.3.2. Suitable Habitat Distribution Prediction

We used the ‘sdm’ package to model species distribution in R 4.0.3 [41], which is an ensemble modeling approach based on multi-model predictions for occurrence and suitable habitats, and is able to reduce the uncertainty of single-model predictions and enhance the effectiveness of conservation efforts [42]. We chose five modeling algorithms which are reported to display high performance when assessing species distribution [43,44], which included a bioclimatic envelope algorithm [Bioclim], generalized linear models [GLMs], generalized additive models [GAMs], random forest [RF] and maximum entropy [MaxEnt]. Bioclim only considers ‘presence’ data, while the other four methods use both presence data and absence data. As it is difficult to obtain confirmed absences, especially in mobile and hidden species, pseudo-absences often come from background data [43,45].
Eighty percent of the occurrence points were used to train the model and the other points were used to test their performance. The area under the curve (AUC) of the receiver operating characteristic (ROC) plot was applied to evaluate the prediction accuracy of the models [45,46]. If AUC values are smaller than 0.7, the models have poor performance [47]. We excluded the ‘Bioclim’ model and ‘GAMs’ model from the final ensemble predictions and averaged the predictions of remaining models [48,49]. We create weights for each model predictions by subtracting 0.5 (random expectation) from the AUC score of each model and squaring the results, thereby providing further weights for models with higher AUC values. The average weighted prediction of different models was considered as the ensemble prediction. We then transform the ensemble predictions into binary suitable (present) and unsuitable (absent) graphs based on the “average logical threshold of maximum training sensitivity plus specificity” [50].

3. Results

A total of 18 breeding sites were compiled and summarized according to the previous studies on the BCLT from between 2000 to 2018. Among them, 8 were regarded as recorded breeding sites, while another 10 were regarded as unoccupied breeding sites. In 2022, two new breeding sites were observed in the central part of Dexing City and Wuyuan County along the Le’an River at the border of Dexing City.

3.1. Habitat Preference at Different Scales

At the meso-scale, the PCA showed that PC1 explained 30.9% and PC2 explained 26.7% of the variance in habitat use at unoccupied breeding sites and recorded breeding sites; the main representative variables of the unoccupied sites were water area, forest–grass mixed area and infrastructure construction, and the main representative variables of the recorded sites were infrastructure construction, grassland, bare land and farmland. Our results showed marked differences in the habitat preference of the BCLT between unoccupied and recorded breeding sites (Figure 2).
At the micro-scale, vegetation coverage, crown breadth, shrub coverage, herb maximum height, herb average height and herb species number (6 of 11 variables) were found to differ significantly (p < 0.05) between the nest plot and the control plot. The tree coverage, herb maximum height and herb average height of the nest plot were significantly higher than those of the control plot, while the vegetation coverage, shrub coverage and herb species number of the recorded breeding sites were significantly lower than those of the control plot (Table 3).

3.2. Suitable Breeding Habitat Distribution

The ensemble model with three predictive algorithms had good discriminatory power. The AUC values were 0.91, 0.85 and 0.88 in RF, GLMs and Maxent, respectively. The suitable habitat covered an area of 108.67 km2 in the study area. The threshold was 0.117. The centralized distribution area was mainly located in the central and southern parts of Wuyuan County and in the western parts of Dexing City. The forest bird nature reserve in Wuyuan County did not completely cover the suitable habitat of the BCLT, and there was an obvious protection gap (Figure 3). In addition, we verified the results of habitat prediction in 2022 and found two new breeding sites in the predicted area which were distributed in the central part of Dexing City and Wuyuan County along the Le’an River at the border of Dexing City.
Based on the contribution rates of various environmental variables to the suitable habitat, we could intuitively judge the preference of the BCLT for nesting habitat selection. The relative contribution rates of all environmental variables to the modeling process of the ESDMs showed that (Figure 4) distance to waterways (41.50%) had the highest contribution to the distribution modeling of the BCLT. Distance to deciduous broadleaf forest and distance to roads also had contributions to the model construction, and their contribution rates were 17.80% and 10.20%, respectively, followed by aspect (5.00%), altitude (4.00%), distance to mixed forest (2.80%), distance to evergreen needleleaf forest (2.80%), distance to evergreen broadleaf forest (2.70%), land cover (1.70%) and slope (0.80%).

4. Discussion

4.1. Land-Use Selection

The dominant land-use types of the unoccupied breeding sites were water area, forest–grass mixed area and infrastructure construction. Clean water is the basic need of birds, and previous studies have shown that the BCLT bathes along rivers regularly [51], suggesting that water is an important habitat land type for this riparian bird species. Moreover, water sources are also an important factor for habitat prediction. However, the relatively low demand may be caused by changes in water quality. Studies have shown that a large amount of urban wastewater and farmland wastewater from the upper reaches will enter the downstream section of the Le’an River, which is polluted by sewage, agricultural fertilization and animal feces, and water quality monitoring has indicated that the great influence of human activities on water quality may pose a threat to the BCLT [52,53,54]. The forest–grass mixed area provides not only basic living conditions, but also natural enemies such as squirrels, snakes and corvids for the BCLT [30,33,36,55]. Previous studies and our research have shown that these species are the predator or nest predator of the BCLT [56]. During the field survey, we also found that the eggs and chicks of the BCLT in this habitat type were subjected to the stress from nest predators such as squirrels, snakes and corvids.
In particular, our results showed significant selectivity for infrastructure construction in both groups. Among the land-use types at the recorded breeding sites, infrastructure construction was the most advanced type. The previous studies declared that the bird richness increases with increasing density of human construction [57]. Studies have shown that proximity to human settlements can help increase reproductive rates by helping species reduce the impact of predators and providing extra food. Hooded Vultures, Necrosyrtes monachus (Temminck, 1823) (Accipitriformes: Accipitridae), for instance, achieve a higher reproductive success near human habitations thanks to the protection from traditional customs [58], and human disturbance can help reduce the number of predators such as snakes [59], thus reducing the stress from nest feeding. In addition, as a companion species, the BCLT shows a certain degree of compatibility with human activity in the selection of nesting areas during the breeding period [17]. Meanwhile, some studies have shown that roads may pose a threat to large mammals or amphibian reptiles to some extent, but the impact on species, especially on small mammals or birds, is not always negative and sometimes can be neutral or positive [60]. Some studies have shown that roadsides are used as a network ecological corridor by various insects [61,62] which are also the main prey of the BCLT, so the roadside may provide more open feeding space for it. All these indicate that human activities or protection can provide the BCLT with a certain degree of survival welfare. However, our attention also needs to be wary of the negative effect of human disturbance. Some studies have shown that even in protected areas, artificial disturbance brought by increased frequency of photography would increase the height of ground at nesting sites [32]. Due to the lack of protection and habitat management of the species in the early stage and the increase in tourists photographing birds, the location of its nesting habitat during the breeding period has continuously changed, with significant differences in land use. Therefore, it will be of great benefit to the protection work to avoid excessive interference by adjusting the protection measures constantly. In addition, the BCLT also exhibited strong selectivity for ancient forests, which is probably because infrastructure construction has a closer spatial relationship with the ancient tree populations and fengshui forests that the BCLT prefers [34,36,63]. Although the parks and green spaces for residents’ activities have increased in recent years, due to the protection from local customs and policies, the ancient forest inside the village is not cut down on a large scale and the suitable habitat of the BCLT is retained to a certain extent [51,64,65]. Forest land area is sufficient, and this habitat type is not obviously destroyed or reformed. At the same time, our results showed that there was a strong demand for grassland, farmland and bare land, as the food resources are more sufficient in grassland and farmland [66,67,68]. Considering that birds select habitats depending on equally important requirements for subsistence resources and habitat characteristics [69], we should avoid overexploiting resources in areas of their special preference and implement rational protection policies, so as to provide them with more options for nesting habitat selection during the breeding period.

4.2. Microhabitat Selection

The BCLT usually builds nests on the top of trees with dense branches in the middle of the canopy, and its nests are well shielded by the thick branches and leaves around them, as the well-growing vegetation in habitats can provide birds with concealed breeding sites and a foraging environment, thus minimizing the risk of predation [70]. A similar selection strategy was also observed in our field study on the preference of the BCLT for the arbor forest type. Higher soil acidity in coniferous and broadleaved forests may result in lower invertebrate diversity and abundance than in deciduous forests [71], and this may limit the food selection range of the BCLT to some extent. At the same time, the greater number of predators present in evergreen forests due to the rich biological resources in the canopy increases the need to avoid predators [72]. This partly explained the why our results showed that deciduous broad-leaved forests had a more significant impact on the nesting habitat selection of the BCLT than evergreen broad-leaved forests and evergreen coniferous forests. Even though the natural conservation zones designated for the protection of fengshui forests (the main nesting habitat of the BCLT) was dominated by evergreen broad-leaved forests and mixed coniferous forests, with only a small amount of deciduous broad-leaved forests [33,37,56]. The shrub coverage of the experimental group was significantly lower than that of the control group. This may be due to the relatively sparse vegetation spatial structure in the living space under the forest canopy, which can provide the BCLT with better vision and flight convenience so that they may maintain a faster speed when shuttling between tree crowns and herb layers and improve foraging efficiency and escape velocity [34]. Moreover, the herb species number of the nest plot was lower than that of the control plot, which may be related to the fact that the BCLT prefers to build nests near the infrastructure facilities (mainly houses) in the above results. During the survey, we found that farmers would plant sparsely arranged crops in scattered small patches of space, with the manicured areas having fewer weeds. Therefore, the corresponding environmental characteristics of these selections were low herbage diversity and single species characteristics. Additionally, the average height and maximum height of herbs of the nest plot were significantly higher than those of the control plot, which may be due to the shelter range of grass. The high-grass area with good growth of natural vegetation can provide an ideal shelter for birds when foraging under the forest canopy, thus helping them to better avoid the risk of predation.

4.3. Suitable Habitat Distribution and Conservation Strategies

For practical purposes, the distribution model in our analysis was based solely on a few environmental parameters [14,73]. Actually, the geographical distribution of species can be uneven, and the regional environment and resources within it are usually not uniform [74]. However, for habitat specialists or those with narrow distributions, such as the BCLT, species distribution models usually perform well [75,76]. The use of the ensemble model factoring weighting accuracy makes the results more comprehensive and representative, so that the habitat suitability of species can be closely approximated, thus providing more reliable research conclusions for the assessment of endangered wild species [2,77]. The ESDMs were used in our study, and most of the available models had an AUC value close to one, which indicates that our ensemble model has made a highly precise prediction [47,78]. Moreover, we found two new breeding sites in the predicted area in 2022, which further confirms that our prediction accuracy is remarkably high.
Most of the central and southern parts of Wuyuan County are urban construction areas, and although there are elements of habitat for the BCLT, there is a certain degree of difference with its preferred environment and vegetation structure characteristics, so it is unknown whether it is possible to develop into its new target site [79]. Conservation and management departments can examine this large area and make reasonable plans for the construction of a suitable environment when making policies. In the western part of Dexing City, there are many mountains and dense forests, but the connection degree between villages containing open woodland is not enough, so it is difficult to form breeding sites with the same scale as the breeding sites along the Lean River [80,81]. Our assessment confirmed that their fidelity to the past breeding site is very high. The BCLT breeding period will not directly select the forest area far away from the rivers and human activities, but always took the original breeding area as the main breeding period habitat. For instance, the BCLT population size in Huaqiao breeding sites is relatively small, with only 3–6 individuals being recorded in our two-year survey, but the groups still settle at this breeding site each year. In view of this, even if the projected potential suitable habitat area is much larger than the current breeding habitat area, we believe that when discussing conservation strategies, it is more advantageous to protect the current breeding site and avoid excessive reconstruction.
As we all know, China is building the world’s largest national park system (http://www.gov.cn/zhengce/2022-12/30/content_5734162.htm, accessed on 1 March 2023). Many efforts have been made for the species conservation and harmonious coexistence between humans and nature [82,83,84], as well as the protection of extremely small populations, including the BCLT [30,33,36]. However, there were still a large number of gaps in the suitable habitat area of the BCLT in the national nature reserve. Given the increasing impact of human activities and climate change, species management and protection will become increasingly important for the maintenance of biodiversity and healthy ecosystems, upon which human well-being depends [78,85]. We believe that our analysis can be applied for identifying conservation needs and increasing the effectiveness of protection for the species concerned.

5. Conclusions

We investigated the nesting habitat of the BCLT in order to further understand its population status and future conservation direction. At the home range scale, the preferred land use types of the BCLT were infrastructure construction, grassland and farmland, and the nesting site preference may be influenced by changes in land-use types. At the microhabitat scale, the environmental conditions of high vegetation coverage and good growth of trees and herbs were significantly preferred by the BCLT. The predicted results showed that the suitable habitat of the BCLT was mainly distributed in the central and southern part of Wuyuan County and the western and northern part of Dexing City, with an area of 108.67 km2. There were still huge gaps in the protected area. We suggest that (1) the protection of the current nesting habitat should be improved; (2) the BCLT populations within the predicted range should be monitored continuously for a long time; (3) the scope and number of protected areas should be adjusted in a timely fashion; (4) the vegetation types preferred by the BCLT should be protected, and overexploitation in areas with suitable habitat characteristics should be controlled.

Author Contributions

Conceptualization, X.H., S.T. and J.X.; methodology, X.H.; software, Z.L.; validation, X.H.; formal analysis, Z.L.; investigation, X.H.; resources, X.H. and S.T; data curation, S.T.; writing—original draft preparation, X.H.; writing—review and editing, J.X.; visualization, S.T.; supervision, J.X.; project administration, J.X. All authors have read and agreed to the published version of the manuscript.

Funding

This research was supported by the National Key Programme of Research and Development, of the Ministry of Science and Technology (2016YFC0503200) and the National Natural Science Foundation of China (31672319).

Data Availability Statement

Publicly available datasets were analyzed in this study. These data can be found here: Rank of Blue-crowned Laughingthrush in the Red List (https://www.iucnredlist.org/species/22732350/131890764, accessed on 28 March 2023); Information of study area (http://www.jxwy.gov.cn, http://www.dxs.gov.cn, accessed on 10 April 2021); Topographic variables (http://srtm.csi.cgiar.org/, accessed on 29 June 2021) Land cover data (http://data.ess.tsinghua.edu.cn/, accessed on 29 June 2021); Interpretation of the Spatial Layout Plan of National Parks (http://www.gov.cn/zhengce/2022-12/30/content_5734162.htm, accessed on 1 March 2023).

Conflicts of Interest

The authors declare no conflict of interest.

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Forests 14 01139 g001 550
Figure 1. The study area and breeding sites documented in 2021 and 2022 for the Blue-crowned Laughingthrush (BCLT). Unoccupied sites: The sites where BCLT was recorded in the past studies but not found during the investigation period from 2021 to 2022; Recorded sites: The sites where BCLTs were actually found in this study.
Figure 1. The study area and breeding sites documented in 2021 and 2022 for the Blue-crowned Laughingthrush (BCLT). Unoccupied sites: The sites where BCLT was recorded in the past studies but not found during the investigation period from 2021 to 2022; Recorded sites: The sites where BCLTs were actually found in this study.
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Figure 2. Results of the principal component analysis of variable contribution within the unoccupied and recorded breeding sites of the Blue-crowned Laughingthrush. ba: bare land; fa: farmland; fo: forest land; mi: forest–grass mixed area; gr: grassland; inf: infrastructure construction; wa: water area.
Figure 2. Results of the principal component analysis of variable contribution within the unoccupied and recorded breeding sites of the Blue-crowned Laughingthrush. ba: bare land; fa: farmland; fo: forest land; mi: forest–grass mixed area; gr: grassland; inf: infrastructure construction; wa: water area.
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Figure 3. The suitable habitat of the Blue-crowned Laughingthrush in Wuyuan and Dexing Counties.
Figure 3. The suitable habitat of the Blue-crowned Laughingthrush in Wuyuan and Dexing Counties.
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Figure 4. The rank of environment variable contribution. DTW: Distance to waterways, DTDB: Distance to deciduous broadleaf forests, DTR: Distance to roads, DTMF: Distance to mixed forests, DTEN: Distance to evergreen needleleaf forests, DTEB: Distance to evergreen broadleaf forests, LC: Land cover.
Figure 4. The rank of environment variable contribution. DTW: Distance to waterways, DTDB: Distance to deciduous broadleaf forests, DTR: Distance to roads, DTMF: Distance to mixed forests, DTEN: Distance to evergreen needleleaf forests, DTEB: Distance to evergreen broadleaf forests, LC: Land cover.
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Table
Table 1. The ecological parameters and measurement methods in the nest plot and control plot.
Table 1. The ecological parameters and measurement methods in the nest plot and control plot.
Ecological ParametersMethod
Vegetation coveragePercentage cover of nest plot and control plot (estimated by the average value of three investigator)
DBHThe tape measure was used
Crown breadthMeasurement with laser rangefinder
Tree heightMeasurement with laser rangefinder (if the trees are too high, visual measurement is used)
Tree coveragePercentage cover of tree (estimated by the average value of three investigator)
Shrub species numberVisual counting method
Shrub heightMeasure with a tape measure or a laser rangefinder
Shrub coveragePercentage cover of shrub (estimated by the average value of three investigator)
Herb average heightAverage the values obtained by the laser rangefinder
Herb maximum heightThe tape measure was used
Herb species numberVisual counting method
Table
Table 2. Selected environmental variables for modeling the suitable habitat for the Blue-crowned Laughingthrush.
Table 2. Selected environmental variables for modeling the suitable habitat for the Blue-crowned Laughingthrush.
CategoryVariablesType
Topography Altitudecontinuous
Slopecontinuous
Aspectcategorical
Land use/Land coverLand cover (LC)categorical
Distance to evergreen broadleaf forests (DTEB)continuous
Distance to evergreen needleleaf forests (DTEN)continuous
Distance to deciduous broadleaf forests (DTDB)continuous
Distance to mixed forests (DTMF)continuous
Distance to waterways (DTW)continuous
Human disturbanceDistance to roads (DTR)continuous
Table
Table 3. The difference in ecological factors between the nest plot and the control plot.
Table 3. The difference in ecological factors between the nest plot and the control plot.
Ecological FactorNest Plot (n = 36)Control Plot (n = 30)H Testp
Vegetation coverage (%)80.000 ± 18.94183.267 ± 10.38954.465<0.001
DBH (cm)45.081 ± 35.00134.900 ± 16.509680.198
Crown breadth (m2)61.513 ± 49.03560.010 ± 45.447680.198
Tree height (m)13.262 ± 5.7609.958 ± 5.007680.131
Tree coverage (%)56.372 ± 19.67852.533 ± 20.67255.9360.006 **
Shrub species number5.308 ± 2.1505.433 ± 3.25315.9390.194
Shrub height (m)2.427 ± 1.3832.522 ± 1.67758.3090.355
Shrub coverage (%)16.897 ± 21.17226.067 ± 23.41448.9510.016 *
Herb maximum height (cm)123.808 ± 55.5602.659 ± 7.02965.9950.018 *
Herb average height (cm)45.058 ± 18.1955.435 ± 13.55358.6810.003 **
Herb species number11.564 ± 5.05832.300 ± 8.11260.314<0.001
* means p < 0.05, ** means p < 0.01.
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Huang, X.; Tian, S.; Liu, Z.; Xu, J. Nesting Habitat Selection and Suitable Breeding Habitat of Blue-Crowned Laughingthrush: Implication on Its Habitat Conservation. Forests 2023, 14, 1139. https://doi.org/10.3390/f14061139

AMA Style

Huang X, Tian S, Liu Z, Xu J. Nesting Habitat Selection and Suitable Breeding Habitat of Blue-Crowned Laughingthrush: Implication on Its Habitat Conservation. Forests. 2023; 14(6):1139. https://doi.org/10.3390/f14061139

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Huang, Xinjie, Shan Tian, Zhengxiao Liu, and Jiliang Xu. 2023. "Nesting Habitat Selection and Suitable Breeding Habitat of Blue-Crowned Laughingthrush: Implication on Its Habitat Conservation" Forests 14, no. 6: 1139. https://doi.org/10.3390/f14061139

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