Yuhang Li, Le Yang, Yunchao Luo, Yiqian Wu, Zhongqiu Li. 2018: Sequential vigilance is unpredictable in reproductive Black-necked Cranes. Avian Research, 9(1): 44. DOI: 10.1186/s40657-018-0137-2
Citation: Yuhang Li, Le Yang, Yunchao Luo, Yiqian Wu, Zhongqiu Li. 2018: Sequential vigilance is unpredictable in reproductive Black-necked Cranes. Avian Research, 9(1): 44. DOI: 10.1186/s40657-018-0137-2

Sequential vigilance is unpredictable in reproductive Black-necked Cranes

Funds: 

the National Natural Science Foundation of China 31360141

the National Natural Science Foundation of China 31772470

the National Natural Science Foundation of China J1103512

the West Light Foundation of Chinese Academy of Sciences 2015

the Project of National Biodiversity Observation Network-Bird 2015-2018

More Information
  • Corresponding author:

    Zhongqiu Li, lizq@nju.edu.cn

  • Yuhang Li and Le Yang contributed equally to this work

  • Received Date: 06 Jun 2018
  • Accepted Date: 05 Dec 2018
  • Available Online: 24 Apr 2022
  • Publish Date: 09 Dec 2018
  • Background 

    Vigilance refers to the behavior of animals scanning their surroundings with a main purpose of antipredation. Whether vigilance can serve the function of anti-predation depends on its unpredictability,meaning instantaneous randomness,sequential randomness,and independence,the three assumptions from Pulliam model (J Theor Biol 38:419,1973). Here we tested two of these three assumptions in reproductive Black-necked Cranes (Grus nigricollis) in Tibetan Plateau: instantaneous randomness and sequential randomness.

    Methods 

    Observations were carried out in July and September of 2014, July and August in 2017 in Selincuo National Nature Reserve,Tibet,with the help of focal sampling method. For instantaneous randomness,we used Kolmogorov–Smirnov test for its negative exponential distribution; for sequential randomness,we used Run test,correlation analysis,and generalized linear model to see if an inter-scan and its previous scan were correlated.

    Results 

    Not similar to some recent studies,we did not find a significant predictable vigilance in this crane. Most inter-scan intervals (86/100,86.0%) passed negative exponential distribution test,meaning vigilance sequences with instantaneous randomness; most inter-scan intervals (91/100,91.0%) passed sequential random test,showing vigilance sequences were random organized.

    Conclusion 

    Our results suggest that keeping a vigilance pattern with unpredictability is beneficial to the survival of the Black-necked Cranes,which are facing with both cruel natural environments and high predation risks.

  • Animals frequently stop feeding and turn to vigilance status, scanning their surroundings. The primary purpose of this behavior is to detect potential predators (Beauchamp 2014, 2015). If the vigilance has a certain pattern or regularity, or called predictability, it will be known and grasped by a potential predator. Based on this information, the observant predator can make attack adjustments to the predictable vigilance. Therefore, the unpredictability of vigilance has become the baseline for animal individuals to survive from predators.

    The Pulliam's vigilance model (Pulliam 1973) was proposed based on three assumptions: instantaneous randomness in scan initiation, sequential randomness in the duration of successive inter-scans, and independent scanning by different group members. Instantaneous randomness and sequential randomness both derive from the assumption that scanning is controlled by a single parameter: the rate of scan initiation (Pulliam 1973; Bednekoff and Lima 1998). Instantaneous randomness means that an individual has the same probability of lifting its head during each instant when its head is down, regardless of how long its head has been down already. An individual scanning in such a manner would produce inter-scan intervals following a negative exponential distribution. Such a distribution has no central tendency or 'hump' but, instead, shows a smoothly decreasing slope as longer intervals become geometrically less likely.

    Sequential randomness across scans means that scanning process has no 'memory', and the duration of one scan is not influenced by the duration of the previous scan or inter-scan. If a scan depends on its previous scan or inter-scan, the vigilance pattern would become predictable and can be grasped by predators. Sequential randomness or unpredictability can avoid providing observant predators with useful information about when to launch an attack, because there is no predictability in either the initiation of scans or the duration of successive inter-scans (Bednekoff and Lima 1998). In fact, whether the vigilance behavior can be predictable or not has been controversial for a long time. The instantaneous randomness has been found in some studies (Bertram 1980), but still not in others (Lendrem et al. 1986; Beauchamp 2006). The sequential randomness, was similarly supported in some species (Roberts 1994; Suter and Forrest 1994; Li et al. 2017), but not in others (Ferrière et al. 1999; Beauchamp 2006; Pays et al. 2010; Carro et al. 2011).

    In this study, we want to test the instantaneous randomness and sequential randomness in reproductive Black-necked Cranes (Grus nigricollis), a big bird living only on plateau (Li and Li 2005). As for the third assumption, we shall discuss in our further works and will not mention in this article. A recent report on these cranes has found that the sequential vigilance was unpredictable when they are wintering in Linzhi County, Tibet (Li et al. 2017). But it remains a question that whether they keep their vigilance unpredictable when they migrate up to a breeding area with higher altitude? Our focal population resides in an extremely cruel habitat, with an elevation of about 4700 m asl, strong wind, solar radiation, and very limited food resources. Due to its large size, the crane was formerly considered to have few natural enemies, especially for adults (Li and Li 2005). Nevertheless, Feral Dogs (Canis familiaris) have been increasing dramatically in recent decades, and have become a big threat to the cranes (Farrington and Zhang 2013; Kumar and Paliwal 2015). Other predators, including Golden Eagle (Aquila chrysaetos) and Eurasian Lynx (Lynx lynx), are also potential predators in the area. Human disturbance, especially grazing activities, might also affect vigilance of the cranes (Bishop et al. 1998; Bishop and Li 2002; Yang et al. 2016a, b ; Che et al. 2018). Therefore, we predict that the reproductive cranes should scan randomly thus to reduce the possibility of being grasped of their vigilance information and therefore being attacked from predators. Two predictions were made according to the two assumptions: (1) a random pattern of inter-scan intervals, thus making a negative exponential distribution; (2) an unrelated relationship between an inter-scan and its previous scan, thus making a random vigilance sequence.

    Observations were carried out in July and September of 2014, July and August of 2017 in Selincuo National Nature Reserve, Tibet, China (30°59′39.79″N, 89°06′49.98″E). The reserve was established in 1993 for protecting rare Tibetan wildlife, including Black-necked Cranes, Snow Leopards (Panthera uncia), Tibetan Antelopes (Pantholops hodgsonii). The area is about 1640 km2, with an average elevation of more than 4700 m asl. The reserve is dominated by the semi-arid monsoon climate with thin air, strong solar radiation, cold and dry climate. The mean temperature is about 8 ℃ in summer, but the temperature difference is large. Sometimes it can rise up to more than 20 ℃ at noon, and then drops to 0 ℃ at night. Summer can be called wet or rainy season since more than 80% of the total annual precipitation falls in summer. The reserve area is primarily alpine meadows dominated by Sophora moorcroftiana, Ceratostigma minus, Aristida triseta, Orinus thoroldii, Pennisetum centrasiaticum, and Stipa purpurea.

    Black-necked Cranes have a global population of about 6600 individuals (Yang et al. 2016a, b ). Qinghai-Tibet Plateau is their main breeding area, while the wintering areas are mainly in south-central Tibet, the Yunnan-Guizhou Plateau in southwest China, India and Bhutan (Qian et al. 2009; Farrington and Zhang 2013; Khan et al. 2014). Black-necked Cranes migrate from wintering areas to the central part of the Selincuo Nature Reserve in early April, breed and live in the reserve until October. Summer cranes have two social units: family groups and social groups. Family groups consist of two adult cranes and one or two nestlings, while social groups are made up of several juveniles.

    Every day we drove from a little town Maiba, where we stayed, heading to one of three directions: Xiongmei, Bange, or Shenza, to find the cranes from 9:00 to 18:00. In the process, we recorded every Black-necked Crane that we encountered with focal observation method. After locating the Black-necked Cranes with binoculars (Nikula 8 × 42), a video camera (Nikon D7100) was used for recording. Each group or individual was recorded for about 20 min. We used tripods throughout the recording process to stabilize the cameras. We stopped recording if any visual disturbances occurred, such as passing human vehicles or large grazing herds. During the reproductive season, the cranes are loyal to their territories (Li and Li 2005). So we recorded the GPS information of each family or individual, thus to avoid resampling same individual on a same day (they all have their own certain territory during reproductive season, especially for those families that carry nestlings and were about to have nestlings, so it is basically impossible that one same family was sampled on more than one occasion). Weather, day time, group type and group size were also recorded at the same time. Observations were only made on sunny or cloudy days thus to avoid potential effect of bad weathers.

    A focal observation includes a sequence of scans and inter-scans. We totally collected 208 focal samples with a total time of about 2400 min. Samples less than 10 min, or with less than 20 feeding/vigilance transitions, or with visible disturbances were deleted, and thus 100 samples from 55 groups were left. We reviewed all these samples and timed scans and inter-scans to the nearest 1 s.

    For instantaneous randomness, we used Kolmogorov-Smirnov test to examine the distribution of inter-scans of each vigilance sequence. We considered the inter-scan intervals were randomly organized if they passed the negative exponential distribution test, and then we calculated its parameter λ, which was the only determinant of the distribution.

    Since most sequences of our samples included less than 30 transitions, we tested sequential randomness of inter-scan intervals with nonparametric one-sample runs test (Beauchamp 2006). Median value was set as the cut point. This test was used to assess whether long (> median value) or short (< median value) inter-scans occurred together in the sequence more often than expected by chance. Rejection of random test provides evidence for a nonrandom pattern of vigilance sequence. We also used a generalized linear model to assess whether every inter-scan interval was dependent on the previous scan duration (Pays et al. 2010). The previous scan duration was set as an independent variable. Family or group ID was set as a random factor. For each independent sample, we also used Pearson correlation when data were normally distributed or Spearman rank correlation when data were not normally distributed to evaluate whether the inter-scan intervals and the previous scan durations were closely related (Li et al. 2017).

    All statistical analyses were carried out with SPSS (version 20.0). The level of statistical significance was set at p = 0.05, and data were reported as mean ± SE.

    We totally included 100 vigilance sequences in our database; the average duration of inter-scan intervals was 20.3 ± 0.4 s, ranging from 1 to 331 s, whereas the average scan duration was 6.6 ± 0.3 s, ranging from 1 to 215 s. For the instantaneous randomness, 86 sequences passed Kolmogorov-Smirnov test for the negative exponential distribution, meaning that 86.0% sequences interrupted feeding and scanned their surroundings randomly. The parameters of each negative exponential function were shown in Table 1, and the grouped inter-scan intervals were shown as Fig. 1.

    Table  1.  Goodness-of-fit of inter-scan intervals of reproductive Black-necked Cranes for negative exponential distribution test
    ID n λ p ID n λ p
    1A 28 - 0.118 0.204 28A 22 - 0.189 0.280
    2A 31 - 0.024 29A 39 - 0.323 0.274
    3A 54 - 0.001 30A 54 - 0.302 0.104
    3B 30 - 0.100 0.508 31A 20 - 0.034
    4A 36 - 0.147 0.367 31B 28 - 0.190 0.358
    5A 26 - 0.109 0.980 31C 31 - 0.359 0.455
    6A 19 - 0.086 0.993 31D 41 - 0.238 0.580
    7A 19 - 0.049 0.163 31E 30 - 0.112 0.751
    7B 24 - 0.154 0.853 31F 51 - 0.005
    7C 19 - 0.079 0.616 32A 20 - 0.578 0.065
    7D 28 - 0.239 0.921 32B 30 - 0.719 0.334
    7E 29 - 0.216 0.341 33A 25 - 1.153 0.076
    7F 22 - 0.275 0.758 34A 26 - 1.044 0.862
    7G 25 - 0.440 0.583 35A 22 - 0.233 0.100
    7H 19 - 0.336 0.870 35B 20 - 0.298 0.985
    8A 38 - 0.303 0.214 36A 22 - 0.815 0.967
    8B 51 - 0.214 0.140 36B 27 - 1.472 0.059
    9A 27 - 0.089 0.232 37A 22 - 0.879 0.502
    9B 34 - 0.250 0.745 38A 38 - 1.354 0.098
    10A 26 - 0.083 0.125 38B 41 - 1.155 0.284
    11A 41 - 0.164 0.054 39A 43 - 0.248 0.217
    12A 49 - 0.033 39B 25 - 1.568 0.144
    12B 32 - 0.188 0.324 40A 27 - 0.455 0.428
    13A 31 - 0.415 0.270 41A 87 - 0.186 0.257
    14A 52 - 0.002 41B 84 - 0.024
    15A 52 - 0.521 0.125 42A 40 - 0.443 0.524
    16A 43 - 0.356 0.386 42B 58 - 0.303 0.227
    16B 95 - 0.004 43A 32 - 0.276 0.180
    17A 80 - 0.001 44A 54 - 0.238 0.653
    17B 108 - 0.387 0.091 44B 48 - 0.181 0.333
    18A 23 - 0.538 0.762 45A 23 - 0.266 0.736
    19A 30 - 0.216 0.517 45B 36 - 0.390 0.573
    19B 28 - 0.216 0.617 46A 33 - 0.502 0.157
    19C 43 - 0.003 46B 42 - 1.241 0.106
    19D 28 - 0.185 0.478 47A 26 - 0.959 0.797
    19E 33 - 0.328 0.889 48A 22 - 0.233 0.100
    19F 27 - 0.111 0.329 48B 20 - 0.484 0.949
    20A 20 - 0.191 0.474 49A 23 - 0.830 0.728
    21A 23 - 0.381 0.398 49B 27 - 1.472 0.059
    21B 50 - 0.046 49C 26 - 0.693 0.370
    22A 72 - 0.016 50A 22 - 0.879 0.502
    22B 48 - 0.198 0.436 51A 38 - 0.044
    23A 60 - 0.243 0.470 51B 41 - 1.155 0.284
    23B 47 - 0.181 0.838 52A 42 - 0.242 0.157
    24A 39 - 0.138 0.311 52B 24 - 1.546 0.174
    24B 55 - 0.148 0.834 53A 29 - 0.195 0.298
    25A 40 - 0.837 0.098 54A 20 - 0.146 0.454
    25B 33 - 0.021 54B 26 - 0.101 0.140
    26A 26 - 1.522 0.055 55A 26 - 0.080 0.347
    27A 28 - 0.992 0.154 55B 21 - 0.366 0.519
    Significant cases were in italics. While numbers represent the group number and the letters represent the individuals from the same group
     | Show Table
    DownLoad: CSV
    Figure  1.  Frequency of inter-scan intervals obtained from 100 individual behavioral sequences of reproductive Black-necked Cranes in Selincuo National Nature Reserve, Tibet

    For the sequential randomness, runs tests revealed that most sequences of inter-scan intervals (91/100, 91.0%) could be considered as non-significant correlation or random organized, and only 9 sequences were in nonrandom order (Table 2). The correlation analysis between the previous scan and the current inter-scan also showed an unpredictable correlation in most cases (92/100, 92.0%). Only 8 sequences showed a negative or positive correlation (Table 2). From the generalized linear model, there was no significant correlation between the previous scan and the current inter-scan (F1, 3489 = 3.212, p = 0.0732), although the group ID had a significant effect on inter-scan intervals (F99, 3489 = 4.939, p < 0.001).

    Table  2.  Run test and correlation test of inter-scan intervals and scan durations in reproductive Black-necked Cranes in Tibet
    ID n Run Correlation ID n Run Correlation
    Z p r p Z p r p
    1A 28 - 0.940 0.347 0.153 0.437 28A 22 - 0.655 0.512 0.251 0.260
    2A 31 - 1.457 0.145 0.239 0.196 29A 39 - 0.289 0.773 0.071 0.669
    3A 54 - 0.550 0.583 - 0.034 0.808 30A 54 - 1.239 0.215 - 0.037 0.792
    3B 30 - 1.301 0.193 - 0.383 0.037 31A 20 0.689 0.491 0.371 0.107
    4A 36 - 2.198 0.028 0.131 0.447 31B 28 0.000 1.000 - 0.047 0.811
    5A 26 - 0.976 0.329 - 0.272 0.179 31C 31 - 1.726 0.084 - 0.063 0.736
    6A 19 - 0.935 0.350 - 0.252 0.298 31D 41 - 0.313 0.755 0.060 0.709
    7A 19 0.486 0.627 0.411 0.080 31E 30 0.186 0.853 - 0.243 0.196
    7B 24 - 0.626 0.531 0.139 0.516 31F 51 - 1.253 0.210 - 0.188 0.186
    7C 19 0.012 0.990 0.324 0.176 32A 20 0.279 0.781 - 0.180 0.447
    7D 28 - 0.553 0.580 - 0.232 0.235 32B 30 - 0.929 0.353 - 0.200 0.289
    7E 29 0.000 1.000 - 0.261 0.171 33A 25 - 2.000 0.046 0.340 0.097
    7F 22 - 1.529 0.126 - 0.548 0.008 34A 26 - 3.403 0.001 0.013 0.948
    7G 25 - 0.810 0.418 - 0.183 0.381 35A 22 - 1.092 0.275 0.102 0.653
    7H 19 0.486 0.627 - 0.211 0.387 35B 20 - 0.689 0.491 0.226 0.337
    8A 38 0.000 1.000 0.140 0.400 36A 22 - 1.503 0.133 - 0.186 0.408
    8B 51 0.860 0.390 0.097 0.498 36B 27 0.793 0.428 - 0.035 0.864
    9A 27 - 0.779 0.436 0.202 0.311 37A 22 1.583 0.113 0.200 0.372
    9B 34 - 0.174 0.862 0.018 0.918 38A 38 - 1.480 0.139 - 0.022 0.895
    10A 26 - 1.001 0.317 - 0.197 0.334 38B 41 1.499 0.134 - 0.151 0.345
    11A 41 1.270 0.204 - 0.331 0.034 39A 43 - 1.850 0.064 - 0.381 0.012
    12A 49 - 0.509 0.611 - 0.075 0.608 39B 25 - 0.340 0.734 - 0.019 0.927
    12B 32 - 0.898 0.369 - 0.361 0.042 40A 27 - 0.779 0.436 0.151 0.452
    13A 31 - 0.726 0.468 0.058 0.755 41A 87 - 1.617 0.106 - 0.124 0.253
    14A 52 - 1.961 0.050 - 0.057 0.688 41B 82 - 0.439 0.660 - 0.169 0.130
    15A 52 0.011 0.991 0.300 0.031 42A 40 - 1.762 0.078 - 0.161 0.320
    16A 43 - 1.232 0.218 - 0.066 0.673 42B 58 - 0.762 0.446 0.091 0.499
    16B 95 - 3.346 0.001 0.110 0.288 43A 32 - 0.539 0.590 - 0.048 0.794
    17A 80 - 1.500 0.134 - 0.037 0.747 44A 54 - 0.815 0.415 0.036 0.795
    17B 108 - 1.094 0.274 - 0.148 0.126 44B 48 - 0.134 0.893 - 0.182 0.215
    18A 23 - 0.846 0.398 - 0.654 0.001 45A 23 0.000 1.000 - 0.296 0.170
    19A 30 0.212 0.832 0.152 0.422 45B 36 - 2.536 0.011 - 0.311 0.069
    19B 28 - 0.193 0.847 - 0.110 0.576 46A 33 0.713 0.476 - 0.076 0.676
    19C 43 - 0.305 0.760 - 0.039 0.805 46B 42 - 1.299 0.194 0.075 0.636
    19D 28 1.383 0.167 - 0.064 0.745 47A 26 - 3.002 0.003 - 0.242 0.233
    19E 33 - 0.225 0.822 0.022 0.904 48A 22 - 1.092 0.275 0.102 0.653
    19F 27 1.580 0.114 - 0.285 0.150 48B 20 - 0.689 0.491 0.035 0.883
    20A 20 - 0.230 0.818 0.060 0.801 49A 23 - 1.653 0.098 - 0.270 0.212
    21A 23 - 0.846 0.398 - 0.094 0.670 49B 27 0.793 0.428 - 0.035 0.864
    21B 50 - 1.429 0.153 - 0.269 0.059 49C 26 - 0.573 0.566 0.206 0.314
    22A 70 - 0.963 0.335 - 0.216 0.072 50A 22 1.583 0.113 0.122 0.589
    22B 48 0.146 0.884 0.039 0.791 51A 38 - 1.480 0.139 - 0.046 0.782
    23A 60 - 2.604 0.009 0.205 0.116 51B 41 1.499 0.134 - 0.151 0.345
    23B 47 0.003 0.997 - 0.109 0.464 52A 42 - 1.718 0.086 - 0.346 0.025
    24A 39 - 0.970 0.332 - 0.044 0.788 52B 24 - 0.175 0.861 - 0.009 0.966
    24B 55 - 2.312 0.021 0.014 0.917 53A 29 0.007 0.995 - 0.345 0.067
    25A 40 - 1.442 0.149 - 0.223 0.167 54A 20 - 0.230 0.818 - 0.147 0.536
    25B 33 - 0.349 0.727 - 0.144 0.423 54B 26 - 0.600 0.548 0.012 0.955
    26A 26 - 0.170 0.865 - 0.047 0.821 55A 26 - 0.976 0.329 0.054 0.793
    27A 28 - 0.871 0.384 0.116 0.558 55B 21 0.011 0.991 - 0.039 0.868
    Significant cases were in italics. While numbers represent the group number and the letters represent the individuals from the same group
     | Show Table
    DownLoad: CSV

    The randomness or unpredictability is probably the baseline of whether vigilance can serve its main function of anti-predation. We tested the two main assumptions of the classical group-size-effect model proposed by Pulliam in 1973, namely the instantaneous randomness and the sequential randomness. Our results showed that most of the inter-scan intervals of the Black-necked Cranes can be considered as randomly organized.

    Instantaneous or sequential randomness of vigilance did not receive supports from most recent studies (Beauchamp 2006; Pays et al. 2010; Carro et al. 2011), but it did from some other studies (Bertram 1980; Li et al. 2017), just like what we found in this study of reproductive Black-necked Cranes. Actually, using a random or regulative strategy for a vigilant animal is probably depending on their environmental surroundings, especially the predation risk. If feeding is too risky, especially with stalking predators present, animals will make themselves unpredictable; otherwise detection of predation risk should be achieved better by regular scanning. In former studies that rejected vigilance randomness, there were no natural enemies for Greater Flamingos (Phoenicopterus ruber ruber) (Beauchamp 2006) and Greater Rheas (Rhea Americana) (Carro et al. 2011) in South America. These large birds are sensitive to human disturbance (Galicia and Baldassarre 1997; Baldassarre and Arengo 2000; Yosef 2000); however, human disturbance is not like a stalking predation threat in an open landscape of water or grassland. In this case, regular scanning for human disturbance would be a better option and therefore about half of their vigilance sequences can be predicted.

    Comparably, although Black-necked Crane is also a large bird, its surviving environments are extremely cruel. The cranes mostly form a family group with only two members during the reproductive season, thus leading to a much smaller group than Greater Flamingos or Greater Rheas. They not only need to survive from high altitude, low temperature, thin air and starvation, and take care of their offspring, but also need to face threatens from human or stalking predators such as Eurasian Lynx. And even non-stalking predators such as stray dogs could adopt a stalking strategy to catch local birds (Li et al. 2017; Yang et al. 2019). Therefore, keeping vigilance unpredictable was very essential for the survival of these rare Black-necked Cranes.

    Similar to our previous findings during winter period (Li et al. 2017; Che et al. 2018), Black-necked Cranes also kept their vigilance unpredictable during the breeding season, meaning that both instantaneous randomness and sequential randomness were supported. Keeping a vigilance pattern with randomness or unpredictability is beneficial to the survival and reproduction of the Black-necked Cranes, which are facing with both cruel natural environments and high predation risks.

    LY, Y. Li, Y. Luo and YW did the field survey and collected data. Y. Li and ZL analyzed data. Y. Li and LY drafted the paper. ZL reviewed and edited the paper. All authors read and approved the final manuscript.

    We thank Wang Lin and Jiabu for their help with fieldwork.

    The authors declare that they have no competing interests.

    The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

    Not applicable.

    This is an observational study; all observations were made 300 m away from the focal animals to minimize observer effects. All the observational procedures in this study were approved by the Chinese Wildlife Management Authority.

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