Transect Line Assumptions - General Introduction

Chapter 1 General Introduction

2.4 Discussion

2.4.3 Transect Line Assumptions

To meet the assumptions of distance sampling, we assumed in this study that g(0)=1, meaning that all animal presence on the survey lines was detected, which was also assumed by many other studies (Jefferson 2000; Wang et al. 2007; Chen et al.

2008). Chinese white dolphins in western Taiwan showed no preference to any boats (Wang et al. 2007), not even fishing boats. During data collection, sighting angles were measured by the compass inside the binoculars, which provided an instant value just by aiming in the direction of animals. Distances were mostly measured manually by experienced observers since the use of range finder was not practical in the inshore area.

Group size estimates were reasonably accurate, as the groups in Taiwan typically consisted of 5-6 individuals (Chang 2011). In all, estimation bias resulting from data collection was considered minor and consistent. In so far as the sampling assumption was concerned that the survey lines should be uniform and randomly sampled, the zigzag transect line design used in this study specifically addressed the problems of previous inshore parallel transect lines sampling, which was not quite uniform or random across different parts of the survey area, and which usually allowed the same survey line to be sampled twice every trip for operational convenience, thus causing the autocorrelation issue.

however quite high, presenting a problem similar to Wang’s transect line study (CV=51.6%) in 2007. On the other hand, the sample size of the current study was too small (only 23 sightings out of 26 surveys), considering that it typically required at least 60 sightings to make a relatively precise estimate of density and abundance (Buckland et al. 2001), by continuing the zigzag survey for two years should resolve this problem with CV less than 20% (bootstrap simulation results).

Since the transect line study by Wang et al. 2007 also used similar inshore parallel transect line surveys, its findings were considered comparable to the 2008-2012 inshore transect line data for the purpose of estimating density and abundance in this study. The pooled inshore parallel transect line survey results offered a much better estimate (N=68 individuals) with a lower CV (11.5%). The density (0.31) was much higher than that of the zigzag survey (0.103), highlighting the major difference in the two survey methods, namely, the study area. The abundance estimate of the pooled inshore parallel line survey was similar to that of the whole-area zigzag survey with its low density estimate, and the 95%CI (54-85) was reasonable compared to the previous studies. This comparability suggested that the inshore parallel transect line also provided a good way to estimate these parameters. The reason for this outcome was that the dolphin’s distribution was so limited to the inshore (shallow) area with water depth less than 15m (confirmed by distribution and environmental data above) that the study area defined by the inshore parallel transect lines were enough to cover the dolphin’s potential habitats while the survey fit well the distance sampling model. The results of the present comparative study suggested that considering the limited distribution of Taiwan’s population, the inshore parallel line survey, although not standard for transect line survey design, still served as an effective survey method for population density and abundance estimates vis-à-vis the zigzag transect line survey design. The zigzag survey,

on the other hand, remained valuable in studying the habitat range of Chinese white dolphins in Taiwan, revealing their distribution range that, as discussed above, might be larger than previously assumed. For further studies of their population status by the transect line survey, the zigzag survey provided uniform and systematic survey and estimates among different regions among Taiwan western waters, the regional density and abundance can be approached by continuous surveys, as collecting more distribution and environmental data could be beneficial in defining the real habitat of Chinese white dolphins in Taiwan. Once the habitat range is more precisely estimated, either reducing the study area of the zigzag survey or resorting exclusively to the inshore parallel transect line survey design with some revisions could be considered.

For the inshore parallel transect line survey design, adopting specific offshore survey lines for different habitat distribution patterns could be a good way to ensure “equal coverage probability” (Dawson et al. 2008). In this way a confident survey area could gradually be defined between the overly narrow inshore parallel design and the overly broad zigzag design. Finally, to make the inshore survey more standard, sampling efforts should be systematically even across each region of the survey area and between years. Duplicate sampling on the same survey line should be avoided by surveying the inshore transect line only once per trip.

In conclusion, while the new zigzag survey design provided reasonable estimates with its small sample size (26 surveys with 23 effective sightings), the estimates from the pooled inshore transect surveys performed well for the population in Taiwan since

surprisingly accurate and invaluable preliminary information about the animal’s general inshore distribution, making it possible for the parallel transect lines survey to produce confident density and abundance estimates.

2.4.5 Annual Variation of Inshore Parallel Transect Estimates

For annual variation estimates, the detection probability and ESW were quite similar between different years and survey designs, indicating that the Chinese white dolphins in Taiwan generally fitted models with a detection probability around 0.3 and ESW around 130m, which could be a good index for later survey designs. The density estimates of the first two years were quite low and very different from 2010-12 estimates, which could be a result of different efforts and study areas. The amount of efforts from 2008-09 was twice or almost thrice that of 2010-12, and the study area was also quite different, making the dataset incomparable. The 2008 surveys only focused on southern Taiwan, from Taichung to Weisangding Sandbar, without covering the northern hot spot known only later, which could in turn bias the overall estimate. The 2009 surveys covered the entire survey area with the most survey efforts in the present datasets and reported the lowest density estimate. In 2009, two massive research projects were carried out in relation to Kuoguang Petrochemical (國光石化) Project proposed for Changhua, a cold spot known later with a very low sighting rate (Chou 2010). This could explain the lowest density estimate in 2009. For the 2010-12 dataset, the sampling efforts were similar. Although the studied area in 2010 was slightly different, the density estimates were quite similar to that of 2011. This similarity could be an indication of population stability from 2010-11. As for the 2011-12 dataset, the study area and survey trips were exactly the same, making it the most comparable

dataset. It should be noted that in 2012 the density and abundance estimates dropped significantly from those of the 2010 and 2011, which could indicate the decline of the population.

A comparison of these annual results showed that the estimates varied with survey efforts, and the more comparable estimates showed that Chinese white dolphins off the western coast of Taiwan had been suffering decline both in population density and abundance over recent years. This was a critical message for conservation: considering that the estimated population sizes from different survey methods were all very small, any loss of individuals would make this population unsustainable.

2.4.6 Conservation Status and Implication

Of all the density estimates for Taiwan and nearby regions, the present zigzag survey reported the lowest estimate, but since the survey covered much offshore area with a very small sample size, a realistic density of Taiwan’s special population should be somewhere between the under-estimated zigzag and over-estimated inshore surveys (i.e. 0.103-0.31). Even considering the over-estimation, the density estimate of the population in Taiwan was still lower than the most sustainable Hong Kong and Dafengjiang populations, which had the highest estimated abundance. Taiwan’s population density and abundance were relatively similar to those of Xiamen and Hepu, two areas already designated as Nature Reserves (Chen et al. 2008, 2009) in China.

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Table 2.1 Efforts of the 2012-13 total area zigzag survey Study date

(2012-2013)

On effort period (hour)

On effort length (kilometer)

1^st season 3^rd-7^th July 24.67 363.88

2^nd season 3^rd-7^th September 31.71 436.27

3^rd season 20^th-21th October, 3^rd-4^th, 10^th, and 22^th November

32.12 402.83

4^th season 8^th-9^th, 13^th March, 14^th-15^th April

30.41 437.67

5^th season 15^th-16^th, 18^th-20^th June 30.03 412.6

Sum 148.94 2053.25

Table 2.2 Parameter estimates of the zigzag transect line surveys

Parameters Estimates CV (%) 95%CI

Probability of detection 0.27 21.2 0.17 0.42

Effective width (m) 136.09 21.2 87.19 212.42

Density (individual/𝐤𝐦^𝟐) 0.103 42.0 0.046 0.23

Abundance (individuals) 64 42.0 29 144

Expected group size 3.18 22.8 1.97 5.12

Table 2.3 Descriptive statistics of environmental factors measured from the survey stations of zigzag transect line surveys (n=949)

Depth

Table 2.4 Descriptive statistics of environmental factors measured from the dolphin contact points of zigzag transect line surveys (n=23)

Depth

Table 2.5 Effort and study area of the 2008-12 inshore parallel survey Survey

trips

Sightings On effort length (km)

SPUE (groups/100km)

Study Area (𝐤𝐦^𝟐)

2008 71 65 4212.47 1.54 141.29

2009 151 76 6001.01 1.27 220.06

2010 63 62 2458.86 2.52 137.05

2011 50 53 2189.82 2.42 149.95

2012 59 56 2395.09 2.34 149.95

2008-12 394 312 17257.23 1.81 220.06

*SPUE=Sightings per unit effort, indicating average sighting groups of 100 km on efforts surveys here

Table 2.6 Parameter estimates of the 2008-12 inshore parallel transect line surveys

Parameters Estimates CV (%) 95%CI

Probability of detection 0.28 8.5 0.24 0.34 Effective width (m) 113.63 8.5 96.17 134.27 Density (individual/𝐤𝐦^𝟐) 0.31 11.5 0.25 0.39

Abundance (individuals) 68 11.5 54 85

Expected group size 3.90 4.8 3.54 4.28

Table 2.7 Comparison of 2008-2012 yearly inshore parallel transect line parameter estimates, 2008-2012 pooled dataset, and 2012-13 zigzag transect line survey.

Year Selected

*P: detection probability; ESW: effective strip width; D: density (individual/km²); CV: coefficient of variance; A: study area; N: abundance (individuals); CI: confident interval

Table 2.8 Comparison of density and abundance estimations of Chinese white dolphins in Chinese and Taiwanese waters.

Region Country D N Reference

Dafengjiang River China 0.326 114 Chen et al. 2009

Hepu China 0.111 39 Chen et al. 2009

HongKong and adjacent area

China 0.409 1028 Jefferson, 2000

Xiamen China 0.124 87 Chen et al. 2008

Western Taiwan inshore waters

Taiwan 0.193 99 Wang et al. 2007

Western Taiwan waters

Taiwan 0.103 64 This study

Western Taiwan inshore waters

Taiwan 0.310 68 This study

* D: density (individual/km²), N: abundance (individuals)

Fig. 2.1 Total area zigzag survey design in 2012-2013

Fig. 2.3 Zigzag survey tracks of the five survey seasons in 2012-2013

Fig. 2.5 Best fit model’s detection probability function (curve) and observed perpendicular distances (histogram) of the total area zigzag survey.

(a)

(b)

(c)

(d)

(e)

(f)

Fig. 2.6 Density histogram of environmental factors measured at the regular survey stations (dotted line) and at the contact points (solid line) during the 2012-13 zigzag survey: (a) Salinity (ppt), (b) Temperature (°C), (c) Water depth (m), (d) pH value, and (e) Turbidity (NTU) (f) Distance to shore (km)

(a) (b)

(e)

Fig. 2.9 Best fit model’s detection probability function (curve) and observed perpendicular distances (histogram) of the 2008-2012 inshore parallel survey.

Chapter 3 Population trend of Chinese white dolphins (Sousa chinensis) in the western coastal waters of Taiwan-by mark-recapture method

ABSTRACT

Since the small and closed population of Chinese white dolphin (Sousa chinensis) in the western coastal waters of Taiwan was categorized at “critically endangered”

status in IUCN red list, precise monitoring of its annual trend and life history parameters is of paramount baseline information for its conservational plans progress.

In this study, I used the mark-recapture method, specifically the robust design model, to investigate the population trend and related reproductive and migratory parameters of this small population. Based on the photo-ID database that consisted of over 120 thousand of photos taken from 323 effective group sightings of 75 identified individuals as well as other unidentified calves and juveniles, the yearly abundance was first estimated to be 65, 66, 69, 65, and 63, respectively, from 2008 through 2012. By considering the unmarked calves and juveniles in the population, the total population sizes were then corrected to be 74, 74, 75, 74, and 64, respectively, with a significant drop in the unmarked ratio in 2012 (2.7%). In terms of reproductive parameters, while mortality increased from 1.5% in 2009 to 8.5% in 2012, the crude birth rate decreased from 7.14% in 2009 to 4.82% in 2010, and dropped sharply to zero in 2012 with no

anthropogenic threats facing the population as well as improve its habitat for the sustainability of the population in Taiwan.

3.1 Introduction

Chinese white dolphins (also Indo-Pacific hump-back dolphins, Sousa chinensis) are widely distributed from western Africa to Australia. The Taiwanese population inhabits the shallow western coastal waters (Yeh 2011) and is believed to be isolated from populations in adjacent waters such as Xiamen and Hong Kong (Wang et al. 2008).

The population is closed and estimated to contain less than 80 individuals (Chang 2011;Wang et al. 2012; Yu et al. 2010). The conservation status of this regional population is so critical that it was listed in the IUCN Red List of Threatened Species as

“critically endangered” (Reeves et al. 2008).

Population abundance is one of the most important baseline data for ecological studies. Not only does it play an important role in planning conservation actions, but studying this parameter annually allows a better understanding of the population trend of a species, especially when the species faces a wide range of anthropogenic threats such as industrial and fishing activities, as is the case of the Chinese white dolphin population in Taiwan (Ross et al. 2010).

Two major methods, the transect line survey and mark-recapture method, have been widely used to estimate the population abundance of Chinese white dolphins off the western coasts of Taiwan (Wang et al. 2007; Wang et al. 2012; Yu et al. 2010) as well as other cetaceans around the world (regarding the transect line survey: Forcada &

perpendicular distances from the sighting points to the transect lines over the course of the survey period (Buckland et al. 2001). Transect line survey researches have been conducted on Chinese white dolphins in Hong Kong, Xiamen, Dafengjang, and Hepu (Jefferson and Hung 2004; Chen et al. 2008; Chen et al. 2009). With regard to the Taiwanese population, previous studies using transect line surveys estimated its

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