Influences of submerged plant collapse on diet composition, breadth, and overlap among four crane species at Poyang Lake, China.

BACKGROUND: Interannual variation in resource abundance has become more unpredictable, and food shortages have increasingly occurred in the recent decades. However, compared to seasonal fluctuations in resource abundance, the influences of interannual variation in resource abundance on the dietary niches of consumers remain poorly understood. Poyang Lake, China, is a very important wintering ground for the globally endangered Siberian Crane (Leucogeranus leucogeranus), White-naped Crane (Grus vipio), and Hooded Crane (G. monacha), as well as the non-endangered Eurasian Crane (G. grus). Tubers of Vallisneria spp., the dominant submerged macrophytes at Poyang Lake, is an important food for cranes. Nevertheless, submerged macrophytes have experienced serious degradation recently. In this study, we used metabarcoding technology to explore the consequences of Vallisneria tuber collapse on the diet compositions, breadths, and overlaps of the four crane species based on fecal samples collected in winter 2017 (a year with tuber collapse) and winter 2018 (a year with high tuber abundance). RESULTS: Compared to previous studies, our study elucidates crane diets in an unprecedented level of detail. Vallisneria tubers was confirmed as an important food source of cranes. Surprisingly, the grassland plant Polygonum criopolitanum was also found to be an important food source in the feces of cranes. Agricultural fields were important foraging sites for Siberian Cranes, White-naped Cranes, and Hooded Cranes, providing foods that allowed them to survive in winters with natural food shortages. However, the three crane species preferred natural wetlands to agricultural fields when the abundance of natural foods was high. The abundance of Vallisneria tubers, and probably P. criopolitanum, greatly influenced the dietary compositions, breadths and overlap of cranes. During periods of preferred resource shortage, White-naped Cranes and Hooded Cranes widened their dietary niches, while Siberian Cranes maintained a stable niche width. The dietary niche overlap among crane species increased substantially under conditions of plentiful preferred food resources. CONCLUSIONS: Our study emphasizes the superior quality of natural wetlands compared to agricultural fields as foraging habitats for cranes. To provide safer and better foraging areas for cranes, it is urgent to restore the submerged plants at Poyang Lake. While high dietary niche overlap is often interpreted as intense interspecific competition, our study highlights the importance of taking food abundance into account.

Response of Siberian Cranes (Grus leucogeranus) to Hydrological Changes and the Availability of Foraging Habitat at Various Water Levels in Poyang Lake.

To assess the Siberian crane (Grus leucogeranus)'s response to changing water levels and habitat quality at Poyang Lake, we analyzed the lake's hydrological trends over the past two decades with the Mann-Kendall and Sen slope methods. Additionally, we explored the link between the crane population size and hydrological conditions at the lake from 2011 to 2019. Meanwhile, five environmental factors, including habitat type, distance from shallow lakes, human footprint index, elevation and normalized vegetation index were selected, and the distribution patterns of suitable habitats for the Siberian crane under 10 water level gradients with intervals of about 1 m (5.3-14.2 m) were simulated by using an improved habitat suitability index model that determines the weights of evaluating factors based on the MaxEnt model. The results showed that the overall trend of the inundated area in Poyang Lake was shrinking in the last 20 years, with a significant increase in the area of exposed floodland during the early wintering period (Z = -2.26). The prolonged drought resulting from this will force vegetation succession, thereby diminishing the food resources for cranes in their natural habitat. The mean inundated area in June demonstrated a significant negative correlation with the population of Siberian cranes in natural habitats (r = -0.75, p = 0.02). Shortage of the Siberian crane-preferred Vallisneria tuber due to June flooding was the primary driver of the crane's altered foraging strategy and habitat shift. In years with relatively normal June inundation, indicating abundant Vallisneria resources, the relationship between the inundated area during the dry season and the crane population fit well, with a quadratic curve (R2 = 0.92, p = 0.02). The dry season's inundated area primarily affected the crane population and distribution pattern by influencing the availability of food resources, and both excessive and insufficient inundation areas were unfavorable for crane survival. The modeling results for habitat suitability indicated that as the water level decreased, the trend of the area of good habitat for the Siberian crane showed an inverted bell shape, peaking at a water level of 8.8 m, with optimal conditions occurring between 8 and 10 m. The combined effects of climate and human activities have made the shortage of food resources in Poyang Lake the new normal. The degradation of natural habitats has led to a decline in the quality of Siberian crane habitats, and artificial habitats can only be used as refuges to a certain extent. Thus, formulating strategies to restore natural habitats and enhance the management of artificial habitats is crucial for the conservation efforts of Siberian cranes.

Double jeopardy: global change and interspecies competition threaten Siberian cranes.

Anthropogenic global change is precipitating a worldwide biodiversity crisis, with myriad species teetering on the brink of extinction. The Arctic, a fragile ecosystem already on the frontline of global change, bears witness to rapid ecological transformations catalyzed by escalating temperatures. In this context, we explore the ramifications of global change and interspecies competition on two arctic crane species: the critically endangered Siberian crane (Leucogeranus leucogeranus) and the non-threatened sandhill crane (Grus canadensis). How might global climate and landcover changes affect the range dynamics of Siberian cranes and sandhill cranes in the Arctic, potentially leading to increased competition and posing a greater threat to the critically endangered Siberian cranes? To answer these questions, we integrated ensemble species distribution models (SDMs) to predict breeding distributions, considering both abiotic and biotic factors. Our results reveal a profound divergence in how global change impacts these crane species. Siberian cranes are poised to lose a significant portion of their habitats, while sandhill cranes are projected to experience substantial range expansion. Furthermore, we identify a growing overlap in breeding areas, intensifying interspecies competition, which may imperil the Siberian crane. Notably, we found the Anzhu Islands may become a Siberian crane refuge under global change, but competition with Sandhill Cranes underscores the need for enhanced conservation management. Our study underscores the urgency of considering species responses to global changes and interspecies dynamics in risk assessments and conservation management. As anthropogenic pressures continue to mount, such considerations are crucial for the preservation of endangered species in the face of impending global challenges.

Complete mitochondrial genome of a Siberian Crane (Grus leucogeranus).

The complete mitochondrial genome (mtDNA) of hemocyte from Siberian Crane (Grus leucogeranus) was sequenced using high-throughput genetic sequencing, and mitochondrial genome was assembled using MITObim tools according complete mitochondrial genome of Grus leucogeranus (NCBI Reference Sequence: NC_020574.1). The assembled mitogenome, consisting of 16,747 bp, has unique 14 protein-coding genes (PCGs), 22 transfer RNAs, and two ribosomal RNAs genes. The complete mitogenome provides essential and important DNA molecular data for further phylogenetic and evolutionary analysis for Siberian Crane phylogeny.

The Far East taiga forest: unrecognized inhospitable terrain for migrating Arctic-nesting waterbirds?

The degree of inhospitable terrain encountered by migrating birds can dramatically affect migration strategies and their evolution as well as influence the way we develop our contemporary flyway conservation responses to protect them. We used telemetry data from 44 tagged individuals of four large-bodied, Arctic breeding waterbird species (two geese, a swan and one crane species) to show for the first time that these birds fly non-stop over the Far East taiga forest, despite their differing ecologies and migration routes. This implies a lack of suitable taiga refuelling habitats for these long-distance migrants. These results underline the extreme importance of northeast China spring staging habitats and of Arctic areas prior to departure in autumn to enable birds to clear this inhospitable biome, confirming the need for adequate site safeguard to protect these populations throughout their annual cycle.

Population sizes and group characteristics of Siberian Crane (Leuco-geranus leucogeranus) and Hooded Crane (Grus monacha) in Poyang Lake Wetland.

Both the Siberian Crane (Leucogeranus leucogeranus) and Hooded Crane (Grus monacha) have limited population sizes and are considered endangered by domestic Chinese and international agencies. To document the current size of their respective populations and characterize their groups, between October 2012 and April 2013 we undertook fieldwork at four nature reserve areas within the Poyang Lake wetlands. We divided Poyanghu National Nature Reserve (PYH) into the Wucheng (PWC) and Hengfeng areas (PHF), because each are each located in different counties. Our fieldwork showed that the Siberian Crane occurred mainly in PYH (364 in the PHF, 158 in the PWC) and the Nanjishan Wetland National Nature Reserve (NJS, with 200 individuals). The Hooded Crane was mainly distributed in PYH (302 in the PHF and 154 in the PWC). Family groups accounted for more than 50% of the total number of groups among both species, with Hooded Cranes forming more family groups than Siberian Cranes. Typically, these groups were formed of two adults with one offspring (Siberian Crane), and two adults with two offspring (Hooded Crane), with the mean family group size of the Siberian Crane and Hooded Crane being respectively 2.65 ± 0.53 (n=43) and 3.09 ± 0.86 (n=47) individuals per group. The mean collective group size of the Siberian Crane and Hooded Crane included 28.09 ± 24.94 (n=23) and 28.94 ± 27.97 (n=16) individuals per group, respectively, with the proportion of juveniles among Hooded Cranes being more than double that seen among the Siberian Cranes.

[Foraging habitat selection of Siberian Crane (Grus leucogeranus) during autumn migration period in the Momoge Nature Reserve].

In autumn of 2008 and 2009, we studied the foraging habitat selection of Siberian Crane (Grus leucogeranus) in the Momoge Nature Reserve of Jilin province. Using the resource selection index, resource selection functions, and the chi-squared test, we found that the Siberian Crane exhibited selectivity in their preferred foraging environments in relation to the distance to human disturbances, vegetation density, coverage and height, foraging vegetation density and water level. Interestingly, this selectivity in regards to large scale disturbances was lower than other factors. The characteristics of favorite foraging habits of Siberian Cranes include a variety of factors: a distance >5 000 m from a national highway, >1 500 m from a non-gravel road, >1 000 m from the nearest road, >1 000 m from a residential area, >1 000 m from farmland; plant density between 20 and 50 grass/m(2); plant coverage lower than 10%; plant height lower than 20 cm; Scirpus planiclmis density between 1 and 50 grass/m(2); Scirpus triqueter density between 1 and 10 grass/m(2); and the water level between 40 and 60 cm. The resource selection functions of Siberian Crane foraging habitat in autumn can be described thusly: Logistic (P) = 0.663 + 0.565×distance to national highway + 0.042×distance to non-gravel road + 0.519×distance to the nearest road + 0.353×distance to residential area + 0.169×distance to farmland - 0.455×vegetation density - 0.618×vegetation coverage - 0.548×vegetation height - 0.158×Scirpus planiclmis density - 0.404×Scirpus triqueter density + 0.920×water level,T (x) =e(Logistic(p)) / [1 + e(Logistic(p))], with an overall prediction accuracy of 82.9%.