Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

Earth & E-nvironment 2: 29-53 University of Leeds Press

Growth rates of sea turtles in Watamu, Kenya

Douglas M. Watson

School of Earth & Environment, University of Leeds, Leeds, W. Yorkshire LS2 9JT; Tel: 0113 3436461

Abstract

Green Turtles (Chelonia mydas) are at the forefront of conservation efforts due to their protected status and this relies on increased knowledge and awareness about them and their characteristics, including growth, from around the world. In Watamu, Kenya on the Western Indian Ocean coastline a capture-mark-recapture (CMR) study was carried out over a period of several years to produce recapture interval data. Growth analysis from changes in length over time found rates are non-monotonic, similar to those observed in the Pacific Ocean and ranged for Green Turtles from 0.468-10.67cm/yr (95% confidence), mean 5.18cm/yr (s.d 2.83). These rates were more rapid than many locations worldwide, with both seasonal and annual variations in growth along with recapture numbers and time. Average growth rates are slightly higher than the second most common species in Watamu: Hawksbill Turtles (Eretmochelys imbricata), which also has protected status. There is evidence for rapid individual increases in size outside the 95% confidence growth rate boundaries. The human measurement error found in association with carapace measurement highlights one of a number of limitations with such research. These findings are fundamental to a greater understanding of lifecycle, growth and morphological changes in the Western Indian Ocean, with limited comparable data from the region. They also have important implications for the successful conservation of not only the species present in Watamu, but also sea turtles in general.

ISSN 1744-2893 (Online) © University of Leeds

29 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

1 Introduction

The existence of sea turtles on earth stretches back in history to the cretaceous period with them generally found on the coast lines of mid latitude countries where they periodically visit beaches to forage and nest. Increased pressure from fishing with more technologically developed methods and impacts from urbanisation has led to a decline in populations. Hence more recently this has resulted in them being at the forefront of conservation efforts to help restore this decline to their pre-exploitation levels. Life History research is imperative to inform management techniques aimed at aiding population recovery. A number of projects have strived to achieve this with respect to the Green Turtle (Chelonia mydas) which was recognized as being globally under threat in 1990 (National Research Council, 1990). It is now listed as endangered by the World Conservation Union (IUCN; Hilton-Taylor, 2000) with populations estimated to have declined by 37-61% over the last 141 years (Seminoff, 2002). Consequently a substantial time and effort has been put into further understanding the species with specific focus on the quantification of growth of Green and Hawksbill Turtles (Eretmochelys imbricata) under natural conditions, normally with the use of capture-mark-recapture (CMR) programmes. The Hawksbill Turtle’s status is Critically Endangered (IUCN; Baillie and Groombridge, 1996) with further research being now fundamental to its future. One such study has been undertaken in Watamu Kenya, where for the last 7 years the local Non-Governmental Organisation (NGO) Watamu Turtle Watch (WTW)/ Local Ocean Trust (LOT) has been working with local people to increase educational awareness and help conserve populations. Analysis from this location is imperative due to the limited quantification of growth rates in Western Indian Ocean sea turtles.

The aim of this study was to investigate the growth of sea turtles, specifically Green Turtles, in Watamu Kenya, with the use of a mixed-longitudinal capture-mark-recapture scheme. To achieve this, the following objectives were set: • Analyse growth data for Green Turtles in Watamu to determine how rates vary throughout the lifecycle, and compare the rates to corresponding values found in locations worldwide. • Quantify the human measurement error associated with the longitudinal study and asses how much impact this has on the findings. • Identify any variations in annual recapture rate/growth and evaluate the success of the CMR programme. • Compare Green Turtles growth rates of to those of Hawksbill Turtles and attempt to estimate the age of the Green Turtles using a recognised growth function.

2 Literature review

2.1 Historical context

The importance in this specific area of sea turtle research is that an understanding of growth and growth-pattern variation helps develop an understanding of potential rates of population decline and recovery (Zug et al., 2002). This can help lead to successful conservation measures like one seen in Hawaii where there has been a significant increase in numbers of Green Turtles following the implementation of strategies stretching back to the 1970’s (Balazs and Chaloupka, 2004a). Further evidence that this is not just simply natural multi-decadal variability comes from the fact that the initial number recovery coincided with the Endangered Species Act 1978 (Hays, 2004). This came centuries after the first conservation legislation in the world against the killing of sea turtles below a specific size, that originated from the Bermuda Assembly in 1620 (Bustard, 1972). Consequently it can be seen that there is a long term emphasis on sea turtle conservation which can only continue to gather momentum with increased knowledge of such species.

30 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

2.2 Study site

Watamu is a small coastal fishing town found on the eastern coast of Kenya, East Africa. Situated around 20km south of Malindi, its coast is part of the wider Watamu/Malindi Marine Parks and Reserve (WMMPR) and has a separate designated Marine Park around the shoreline encompassing three bays. The town is small, friendly and consists of numerous houses, shops, stalls, hotels and amenities spread along the sea front.

2.3 Site context

It has been recognized for years that there are excellent reefs and turtle populations present on the east coast of Kenya around Watamu and Malindi (Frazier, 1995). Consequently Watamu Turtle Watch (WTW) was formed in 1997 following years of work by local naturalist Barbara Simpson to help conserve the local marine ecosystem. WTW specifically focuses on research and conservation of a variety of sea turtle species that regularly forage and nest in the area. In 2002 WTW expanded and formed the Local Ocean Trust (LOT) with a broader emphasis help conserve the WMMPR. Other LOT activities include an environmental education program which includes an information centre in the town centre and scheduled events with schools and local groups. Activities include working with the local people to inform and educate them of the importance primarily the turtles have, and their impact on the greater ecosystem. Issues related to over fishing in inshore waters, the use of illegal fishing methods impacting on the turtle populations, pollution, marine destruction and uncontrolled development are being tackled in the area (WTW, 2006). The education programme is closely connected to a cash reward scheme where fishermen present their turtle catch for measurement, tagging and release with the reward greater for a larger older turtle. This allows over time a CMR scheme to be in effect compiling data about individual turtles.

2.4 Capture-Mark-Recapture (CMR) schemes

Schmidt (1916, in Balazs, 1995) carried out the first recognized attempt to quantify growth and population in the Virgin Islands using the CMR technique; previously they had not been seriously attempted due to the challenges posed with actually capturing the immature turtles (Balazs, 1995). Presently the main challenges to these studies include the fact that sea turtles are relatively slow growing, resulting in long term labour and time investment and the likelihood of recapturing individuals is relatively poor due to the nature of their movements and migration routes (Bjorndal et al., 2001). However, when successfully carried out over a period of time results from CMR studies produce direct growth measurements which can be used to model population and age specific growth rates (Lutz and Musick, 1997). Unfortunately it is difficult to measure growth in the early size range (hatchlings) in the wild due to the high natural mortality (Bjorndal et al., 2001) and the prolonged time they spend at sea before returning to foraging grounds to grow to maturity (Musick and Limpus, 1997). The juvenile to nesting stages are where most recaptures take place. Furthermore anthropogenic impacts in terms of mortality of juveniles and adults (Bjorndal et al., 2001) for meat and trade compounds the already difficult task of measuring growth in wild reptiles.

In order to carry out morphometric measurements and to mark the turtles they must be actually caught, with a number of techniques used in the past. Common methods include scoop nets, tangle nets, basking, (Balazs, 1995) and bullpen or pound nets (Balazs and Chaloupka, 2004b). Also hand capture from a skiff, land (Green, 1993) or small boats and snorkelling/scuba at night (Balazs et al., 1996; Balazs and Chaloupka, 2004a) has proven to be effective. Finally, capture methods can include using turtle rodeo (Limpus and Reed, 1985) which involves jumping on them from the bow of a boat after a pursuit.

Recapturing individuals over time enables profiles to be built up of morphometric data including straight carapace length (SCL) or curved carapace length (CCL) along the midline of the carapace. Also straight carapace width (SCW) or curved carapace width (CCW) at the greatest

31 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

point of width (Balazs, 1995) are taken at first and subsequent recaptures (Lutz and Musick, 1997). Varying opinions are apparent on which measurement techniques are best, though generally SCL is considered more accurate than CCL due to the use of callipers instead of a tape measure across the carapace (Balazs, 1995). Despite this Lutz and Musick (1997) claim there is little basis for using SCL over CCL except for Leatherback Turtles (Dermochelys coriacea). There is a small difference between these two measurements in terms of empirical values but as long as consistency is observed valuable results can be yielded.

2.5 Tagging

After catching, measuring and noting physical characteristics, the turtles had to be tagged to allow for identification upon future recaptures. Typically metal tags attached to flippers have been most successful for long term studies, though initial awareness was raised in the early 1970’s about the success of this technique on wild reptiles due high rates of tag loss (Limpus, 1992). Problems of corrosion in previously used Monel 400 tags resulted in Inconel 625 being used from September 1976 onwards (Balazs, 1995), and other studies have been known to use titanium and even plastic tags in the past (Green, 1993; Lutz and Musick, 1997). Normally tags are attached only to on one flipper but are often duplicated to other flippers to help compensate for tag loss, as initiated by Green (1979).

Tags are applied to the fleshy area at the joint of flipper and plastron on the trailing edges to allow for subsequent growth (Balazs, 1995). More distal positions along the rear side of the flippers have proved to be more vulnerable to loss, due to digging and covering when nesting and contact and biting during courtship (Limpus, 1992). Despite the knowledge that Monel tags deteriorate rapidly in salt water (Lutz and Musick, 1997) and are frequently duplicated when tagging, the toxic properties have little effect on the growth rates of those individuals (Balazs, 1995). Tag loss was also higher in studies at nesting grounds compared to foraging grounds (Limpus, 1992) likely to be as a result of the increased level of abrasion associated with nest digging.

Another limitation of tagging is the inability to sufficiently tag hatchlings due to the absence of appropriately system that is suitable for their small size and rapid growth rates (Balazs, 1995). An alternative that is not widely used is injecting magnetically coded wire tags into notches on their carapace (Lutz and Musick, 1997). This methodological limitation is a problem as growth during these ‘lost years’ cannot be quantified, resulting in an incomplete life growth cycle.

Ultimately more research is needed into the efficiency, design and application of metal tags on wild marine species (Limpus, 1992). Clearly there are problems encountered in such research despite the increased success in recent decades which are being eradicated as the knowledge base on this topic continues to grow.

2.6 External factors

The results of sea turtle growth studies differ with geographical area and program as a result of a number of different natural and anthropogenic factors. The density of populations has been proven to impact on growth; turtles grow slower when population density is higher (Bjorndal et al., 2000), potentially as a result of limited food availability. Sea water temperature, food availability and disease are also known to impact on growth. Wood and Wood (1993) found that 66% of their studied turtles were infected with fibropapillomatosis, a disease thought to be connected with polluted waters. Despite no known proven connection between the condition and growth it is inevitable that the disease affects the general health of the individual and is likely to reduce its ability to grow at its maximum potential rate. The disease is becoming increasingly prevalent worldwide (Wood and Wood, 1993) and must be continually monitored to ascertain its future impacts on populations and individual turtles.

32 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

2.7 Alternative methods

A number of activities have been carried out in captivity to asses the growth of turtles including ranching, farming and headstarting which is captive rearing to a certain size to reduce chance of predation before release (Klemens, 2000). These methods have been criticized heavily on the grounds that natural and captive environments are highly different with growth rates varying depending on the conditions they are brought up in (Bustard, 1972). However they are important practices in increasing numbers as less than 1% of hatchlings are estimated to reach maturity (Mortimer, 1998), despite Bjorndal (1985) arguing they have proved to be unreliable and should be steered clear of on scientific grounds. Captive growth rates have been proven to be greater than those in the wild due to the availability of food and reduced foraging effort (Flanagan, 2000). The method is of limited use as it can only be applied to hatchlings and cannot be extrapolated through to adults (Klemens, 2000), though could be used to quantify the effect of other parameters e.g. sea water temperature, on turtle growth.

Other techniques of carrying out growth investigations include the use of skeletochronology which involves looking at growth rings in the tissue of individuals. This a more expensive process burdened with limitations including the humerus remodelling during growth potentially eliminates growth marks, the accumulation of non-cyclic growth marks and patterns of growth being unrecognizable (Bjorndal et al., 1998). It becomes apparent that despite there being several ways to determine turtle growth, CMR initiatives provide the most accessible and hence common technique.

2.8.1 Green turtle - Re-capture rates

Despite the fact that Green Turtles are said to inhabit the waters of 140 countries worldwide (Groombridge and Luxmoore, 1989) there is relatively little known about many of these populations. Individual programs in those areas have produced varying growth rates, recapture rates and associated time intervals. Tagging wild marine reptiles is never guaranteed to produce good recapture rates with the greatest success on the GBR with 68% of the 954 turtles were captured once, 21% captured twice, and 11% captured three times or more (Chaloupka and Limpus, 2005). Similarly of the 313 turtles Balazs et al. (1996) caught, 67.1% were caught once or more with 64.5% of these supplying size increases stretching from 3 months to 14.4 years. This recapture success has profound implications on the quality and reliability of any findings despite the fact that an initial sample size may be huge.

2.8.2 Growth stages

Despite varying time intervals between recaptures it is not always guaranteed that turtles will grow, possibly a result of low time intervals or various limiting factors. This is the case for 34 Green Turtles caught in the Hawaiian Archipelago; interval 2-20 months (Balazs, 1995), with Bustard (1972) also finding no measurable growth in nine out of eleven recaptured turtles. In the latter study those that were displaying size increases were concluded likely to be a result of measurement error. Early studies into tagging turtles and subsequent calculated growth rates in the Hawaiian archipelago can be seen in Table 2.4, though many more have been carried out since then.

33 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

Table 2.4 Results of early studies on growth of Green Turtles (adapted from Balazs, 1995)

Researcher Location No Type Growth rate cm per Size Interval tagged month range (months) Mean Range N Schmidt (1916) Virgin 65 CCL 0.43 0.1-0.69 8 29-57 3.5-11 Island Carr and Caldwell West 43 SCL 0.75-5.26 1 44-58 3-3.5 (1956) Florida Burnett-Herkes Bermuda 19 SCL 0.04 2 <50 12-17 (1974) Limpus (1979) Heron CCL 0.05-0.27 45 40-90 <51 Island

General findings suggest that growth is non linear and non uniform (Zug et al., 2002; Seminoff et al., 2002) with rapid increases in the unknown ‘lost years’ (Carr 1995) and through juvenile status, then a reduced growth increase across mid-length turtles. There is a final spurt before reaching sexual maturity where they continue to grow slowly for a period of time, with levels becoming negligible in large adults (Limpus and Chaloupka, 1997).

The 20-30cm SCL is known to be one of the fastest phases of growth with Zug et al. (2002) reporting a 4.4cm/yr growth rate. This is before they recruit shortly after to benthic foraging grounds at around 40cm CCL, in Australia after a period of time away in the Pacific Ocean (Chaloupka et al., 2004), or 40-45cm as found by Musick and Limpus (1997). Alternative work from Puerto Rico by Collazo et al. (1992) found that the 40-50cm CCL had the highest growth rate with turtles annually increasing at a rate of 5.08 cm/yr, one of the highest recorded around the world for this length. Contradictory to this Balazs et al. (1996) found that in Kiholo Bay, Hawaii, the 50-55cm size class displayed the fastest growth rates at 2.0± 1.1cm/yr, though this is not that unusual given it is still in the juvenile age category, with Zug et al. (2002) recording this around 2.0–2.5 cm/yr . These maximum growth values peak around 60-63cm CCL (Chaloupka and Limpus, 1997), 60–65 cm CCL (Limpus and Chaloupka, 1997) and 65 cm CCL (Chaloupka et al., 2004), where the start of the sub-adult class starts prior to the onset of sexual maturity (Limpus et al., 1994). Sex specific growth becomes prominent at this stage (Limpus and Chaloupka, 1997).

Contrasting findings from the Gulf of California suggest that growth continues to a maximum at around 83-85cm SCL at a rate of 1.55cm/yr before declining to slightly in excess of 1 cm/yr when length is greater than 90 cm SCL (Seminoff et al., 2002). This prolonged increase is supported by Bjorndal et al. (2000) who found that up to 70-80cm SCL there is a chance of a growth spurt as a result of turtles leaving shallow waters to deeper areas with less limiting factors, and so resulting in an increase. The subsequent decline is seen due to turtles approaching adulthood, with first timer nesters usually greater than 80cm SCL (Balazs and Chaloupka 2004a), and proper adulthood coming around 90-100cm (Limpus et al., 1994). Growth slows to less than 1 cm/yr (Zug et al., 2002) or becomes negligible (Limpus and Chaloupka, 1997) at this stage.

Noticeable is the variations dependant on location with most examples coming from West Atlantic and both sides of the Pacific Ocean, with a distinct lack from the Indian Ocean.

2.8.3 Growth rates

There is generally little known about the pelagic stage of the life cycle, though it is estimated to last around 5 years with relatively gradual growth throughout (Zug et al., 2002). This absence of pelagic to benthic juvenile stage growth rates skews the average growth throughout the lifecycle. Despite slow growth past sexual maturity for both sexes (Bustard, 1972), there is a great variation seen in the size-specific rates and the overall mean growth rates recorded in turtle research, as always dependant on location and sample size. Levels ranged from 0.08-0.44 cm/month SCL

34 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

(Balazs, 1995), 0–2.5 cm/yr SCL (Balazs and Chaloupka, 2004), 0.2-3.4 cm/yr SCL (Seminoff et al., 2002), to 1.7± 1.0 cm/yr, though this reduced to 1.4 ± 0.8 cm/yr when only first and last recapture were used (Balazs et al., 1996). Limpus and Chaloupka (1997) found rates varying from 0.1 to 10.8 cm/yr SCL: mean 4.2 cm/yr and median: 4.3cm/yr on the GBR, one of the highest published levels. Zug and Glor (1998) found estimates of growth rates ranged from 3-5.2 cm/yr, and when fed sanitations mean specific growth rates can range from 0.01045-0.01462 (Davenport and Scott, 1993). This quantification of specific growth rates can allow comparisons to be drawn across demographic regions and highlights the variation that occurs for different populations.

Along with varying growth levels there is also differing time lengths cited for growth to sexual maturity, which is dependant on location and relative limiting factors. Seminoff et al. (2002) estimated 9-21 years in the Gulf of California, Mexico to reach maturity post recruitment. Few other published estimated values are available party due to the difficulty in calculating this.

2.8.4 Growth curves

Graphic presentations of changing growth rates enable visual comparisons to be made between locations. Monotonic declines were observed in the Southern Bahamas, Atlantic Ocean from recruitment lengths (30cm) to sexual maturity and adulthood (80cm). Similarly one example from the Hawaiian Archipelago, Pacific Ocean, shows a variety of individual sites in this location where a constant decline to negligible rates after a peak in growth was observed. Contrasting findings from Hawaii shows a polyphasic decline in rates, starting at a significantly smaller length. Growth can be seen to decline then level off between 50cm and 80cm SCL before a final decline in adulthood. These graphs highlight the similarities and differences in growth occurring through a turtle’s lifecycle with respect to varying locations.

2.9 Hawksbill growth

Growth rates for Hawksbill Turtles are less well investigated and hence published, partly due to their lesser abundance in the wild. The few studies that have been carried out show varying growth rates from different areas of the world, enabling spatial comparisons to be made. Those found by Diez and van Dam (2002) in Puerto Rico ranged from -0.59 to 9.08 cm/yr with highest rates occurring at sizes 34 and 35cm SCL. In comparison to this on the Great Barrier Reef, Chaloupka and Limpus (1997) found rapid increases up to 60cm CCL where rates hit 2.2cm/yr for females and 1.7cm/yr for males before both diminished to negligible rates around 80cm CCL. Within these studies the lengths of those captured varied highly with 20-84.5cm SCL (Diez and van Dam, 2002) and 39-85cm CCL (Chaloupka and Limpus, 1997), also Kobayashi (2000) used 51.3-96.1cm SCL in further research from Cuban waters. Both Puerto Rico and GBR produced non-monotonic rates with the former similar to other studies in the Caribbean yet higher than associated levels from the latter.

2.10 Analysis

There are various ways turtle growth can be quantified including looking particularly at absolute or specific growth. Absolute growth is the change in length over a given time duration, whilst specific is the absolute growth per unit size expressed as the log of the absolute rate (Lutz and Musick, 1997). It is common that rates decrease with increased length whilst findings also suggest the Atlantic Ocean yields monotonic trends and Pacific Ocean shows non-monotonic, though reasons for this are still unclear (Seminoff et al., 2002). Further to this the absolute rate was not effected by the recapture interval (Chaloupka and Limpus, 1996) which can often be a problem to overcome when the time difference becomes very small. Here it can become difficult to distinguish inter-annual variation in growth rates (Chaloupka and Limpus, 1997). Regardless of time interval it is often genetic variations which cause dissimilar growth rates within a population, and potentially environmental factors can also cause differences between foraging areas within the same population (Chaloupka and Musick, 1997; Balazs and Chaloupka, 2004b). These factors

35 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

would ideally be determined when analysing growth rates as they play a fundamental role in the ability to successfully quantify the increased levels.

2.11 Modelling

Numerous studies have fitted growth models to similar types of turtle data (Frazer and Ehrhart, 1985; Frazer and Ladner, 1986; Boulon and Frazer, 1990) with logistic, Gompertz and von Bertalanffy being the most common models. Despite Jones and Hartfield (1995) finding that von Bertalanffy provided a better fit than the logistic model, backed up by similar findings by Kennet (1996), this model is plagued with problems. It is said that it has very poor statistical qualities resulting in unreliable growth functions (Ratowsky, 1986) and concern must be addressed when extrapolating beyond the range of the data collected (Day and Taylor, 1997), as with many models. Extrapolation here can result in monotonic growth rates where no empirical data was used (Lutz and Musick, 1997) which are not representative of the truth. Other functions such as Gompertz and Logistic are known to have better statistical qualities, though a further option in the form of the Richards function is problematic (Ratowsky, 1990) due to its generalization and very poor statistical qualities (Lutz and Musick, 1997). In some cases split stick regression has been used to estimate the size of the carapace when growth changed from juvenile growth to slower adult growth with the age-size curve matching age found from the physical adding up of plastral annuli (Kennet, 1996). Consequently despite the use of models in growth analysis they are fraught with inconsistencies and must be used with appropriate caution.

In connection with the various models applied to turtle data, computer programs have been implemented to perform length frequency analysis to estimate growth rates and value of age classes in the southern Bahamas (Bjorndal et al., 1995). MULTIFAN was used to compare results to nonlinear regression analysis using 5-cm sections of the turtle sizes, consistent with Balazs et al. (1996) who also broke down the measurements into these same sized length classes, despite it being more common to use 10cm length increments as seen in Table 2.6. The frequency of this analysis is limited due to time and financial constraints associated with such a technique.

2.12 Limitations

Research on wild sea turtles is fraught with limitations exacerbated by Green Turtles being slow growing, wide ranging and thought to take the longest time to reach maturity of any species (Hirth, 1997). The reliability of marking methods is a concern (Lutz and Musick, 1997). In some cases all recaptures under 12 months apart in time for an individual are removed from the data set to reduce measurement error when calculating growth rates (Balazs and Chaloupka, 2004b). Problems with measurement include errors associated with human discrepancies so many researchers take repeat measurements to quantify so allowances can be made for it. Seminoff et al. (2002) performed this with SCL measurements consistent to 0.1cm and Bjorndal and Bolten (1989) finding precision consistent to 0.046cm.

Growth rates may vary as a result of changing environmental conditions resulting in compensatory growth which can also skew results. This is possibly connected with food availability and water temperature (Bjorndal et al., 2003). This phenomenon also occurs in relation to density dependant factors though further research is needed into nutritional growth and population densities to fully understand these effects (Bjorndal et al., 2000). The lack of contact with turtles in the range less than 35 cm CCL has serious detrimental consequences when attempting to model growth over the life spans of turtles (Balazs, 1995), side by side with the fact that extrapolation of growth out of the empirical measured size range is highly problematic (Chaloupka and Musick, 1997).

The literature provides an overview of the process of quantifying sea turtle growth including capture, techniques, modelling and limitations. Evidence can be seen from a number of studies on Green and Hawksbill Turtles that have reported varying growth rates and curves from locations worldwide.

36 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

3 Methods

3.1 Research questions

1. How fast are turtles growing in Watamu compared to other locations, and how does this change throughout their lifetimes? 2. How much human error is there with respect to the techniques used to measure turtle growth, and does this have a bearing on the results? 3. How often are turtles caught, at what time of the year and is the technique the best option for quantifying growth over time? 4. Are there differences between species growth in the study area and approximately how long does it take for turtles to grow to maturity?

3.2 Research design

In order to answer the research questions, decisions in terms of design and data collection must be thoroughly justified to enable reliable conclusions to be drawn. To assess growth rates there needs to be a number of consistent and quantitative measurements taken over time to determine the increase in length of the turtles. Qualitative assessments in this case would ultimately produce be too vague and unreliable. With respect to this study no specific boundary was determined for the sample region and the data set was composed of turtles caught by the local fishermen over an area of approximately 12km of coastline and Mida Creek. Due to the turtles protected status research had to rely on incidental capture, and hence the sampling technique was defined by the activities of the local fishermen.

Depending on the time interval the individual had been out of the ocean a decision was made on the spot whether to carry data collection out on site, or return to the WTW office where there were increased numbers of researchers and repeat conditions could be observed. The number of such repeat measurements was also affected by the occurrence of turtles available to use in the sample, which could vary potentially from 1 to more than 10 per day for the given time data was collected. To be able to asses the error associated with the design of such a study, repeat measurements were obtained to increase reliability and validity. The site was chosen due to the nature of the ongoing conservation efforts being carried out in the area as a result of the presence of local foraging grounds and nesting beaches for the turtles.

3.3 Methods and techniques

Due to the nature of the mixed longitudinal study, methods for catching turtles vary across the world depending on the resources available, dictated by financial backing and support and strictly limited by legislation. For this study the turtle sample was caught through local fishermen who accidentally trap them in fishing nets. The resources were not available to perform intentional captures and the intentional captures of endangered and critically endangered species would need thorough justification. The captures occurred in a number of different ways, explained by the field manager of the NGO: • Uzio- net placed in shallow water at low tide slightly away from the shore line supported by long sticks from coconut plants. As the tide comes in so do the fish, marine organisms and inevitably sea turtles. Then as the tide retreats the trap is flooded and the reptiles are trapped; • Hand- when individual turtles become stranded in pools/ponds whilst trying to forage when the tide retreats; or simply cant swim due to illness; • Spear gun- turtles are shot though the fishermen usually claim they are caught in nets as it is illegal to capture them in this way. Most turtles caught by spear guns tend to be slaughtered though instead of brought to the project;

37 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

• Fishing line – longlines are used where a line is placed between two buoys anchored to the sea bed with many hooks spaced periodically 1 meter apart hanging from the line. These sometimes catch turtles as well as fish and can injure them severely in some cases, though it is claimed few are caught in this manner (Hillestad et al., 1995); • Jariffe nets- placed in deeper waters purposefully to catch bigger fish, with a thicker stringed net structure and are left for up to a day before the fishermen return to collect their catch. Unfortunately turtles caught in Jariffe nets often drown as they cannot reach the surface for air and nets are not collected frequently enough to save them; • Shallow water nets are used and the fish/turtles are chased into the net before closing the circle small enough to be manageable; and • Washed ashore- onto beaches, though this generally only occurs when they are sick.

WTW have devised a communication system whereby after capture the turtle(s) are retrieved from the fishermen as quickly as possible to minimize stress on the individuals. The fishermen responsible, his/her town, the landing site where the turtle was caught, the method used and the time of capture were recorded before morphometric measurements were taken. After measurement and tagging the turtle(s) were returned to the sea at the nearest suitable landing site, usually away from the developed tourists areas.

Common methods of measuring and profiling turtle growth vary between researchers and studies. For this study despite its decreased accuracy as a result of irregularities and unsmooth shapes on the carapace surface (Bjorndal and Bolten, 1989), CCL and CCW were used. The reasons for this include the fact that tape measures were less expensive and easier to transport (Bolten, 1999). This makes them the more common method in sea turtle studies (Limpus and Chaloupka, 1997). Measurements were taken from the anterior point at midline (nuchal scute) to the posterior notch at midline between the supracaudals, recommended by Bjorndal and Bolten (1989). CCW was measured across the widest point of the carapace (fig 3.1). A plastic tape measure was used with calibration against other tape measures to maintain accuracy, as opposed to using metal tape measures which are know to deviate away from the surface due to their rigidness, and can be subject to corrosion over a period of time (Bolten, 1999).

Figure 3.1 Measurement of CCW with a tape measure over the widest point of the carapace

Physical characteristics such as any diseases, barnacles, missing parts of the body, notches and distinguishing features were recorded and tag number noted if it had previously been captured and tagged. If it was a first time capture a tag was fitted and the new identification code documented. If there was a tag present but signs that it may be on the verge of falling off, or if the individual was from a rarer species and hence more vital that its identification was prolonged, an extra 2nd tag was fitted as two tags increases the chance at least one would stay attached. Nesting turtles were predominantly tagged on the fleshy part inside of the front flipper due to the mid-tip being in the active area of the flipper where most friction and potential catching on rocks and sticks occurs during nest disguising, and hence causing injury to the turtle. Immature and juveniles were tagged on the rear right flipper with a simple self piercing Monel and Inconel tag with simplified locking system.

38 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

This was done using a pair of pliers, inserting the tag through the flesh with one sharp short squeeze to minimize pain to the turtle. The tag is positioned so that there is enough room for growth in subsequent years (Balazs, 1999), but not too much as to decrease its chances of staying attached. 66% attached with 33% free is the optimum distance away from the attached flesh. Unfortunately as with many sea turtle studies the age of the turtle was unknown and could not be recorded (Bjorndal et al., 1998). It is almost impossible for sex to be determined with only the external physical characteristics available (Bjorndal et al., 2000) and the limited time before release, required to minimize the physiological impacts on the turtles.

3.4 Analysis methods

Data were manipulated into a manageable form. The turtles were sorted into tag order then recapture chronology for each individual enabling the size change over time to be quantified. From this and the time difference between recaptures, the specific growth rates were calculated. The species were separated to allow comparisons to be made and all recaptures less than 100 days time difference were removed, to eliminate the majority of negative rates resulting from measurement or recording errors which decreased the reliability of the data. This included 59% of the recapture events for Green and 62% for Hawksbill Turtles. Then to observe average rate changes per length more reliably, the growth rates were broken down into 5cm increments, as seen in Bjorndal et al. (1995). This technique is imperative in allowing a single figure to be calculated for each size increment, representing an average growth value per size category for all the turtles in that specific length range.

Using all recapture data if several recaptures were made, as opposed to only the first and last recaptures as Green (1993) did, yields a significantly higher number of growth rates and hence a greater reliability. This is in contrast to Lutz and Musick (1997) who claim it is common practice to only use the first capture and last recapture. Results were then drawn from the calculations.

4 Results

4.1 Summary tables

Table 4.1 Main results for Green and Hawksbill Turtle captures

Factor Green Hawksbill Lengths (cm CCL) 32.9-114.9 20.2-96.8 Mean (cm CCL) 48.4 40.9 Time interval (months) <1-71.8 <1-60.9 % caught only once 64.5% 81% Growth (cm/yr) (95% confidence) 0.468-10.67 0.151-13.9 Mean (cm/yr), s.d 5.18, 2.82 4.59, 4.55 Highest size category of growth (cm CCL) 60-65 65-70

Table 4.2 Number of turtles captured in each 5cm length increment for Green and Hawksbill species

Length increment (cm CCL) Number of turtles caught per length increment Green Hawksbill 30-35 0 1 35-40 5 6 40-45 43 5 45-50 73 2

39 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

50-55 49 1 55-60 27 1 60-65 12 1 65-70 5 1 70-75 4 1 75-80 3 0 80-85 1 0 85-90 2 0 100-105 1 0 105-110 1 0 110-115 1 0

4.2 Green Turtles

In total 1666 captures of Green Turtles were measured between January 1999 and July 2005, with 563 of these subsequent recaptures of previously caught individuals. Individual Green Turtle recapture amounts varied from a single capture to 19 recaptures with 1012 (64.5%) caught only once, a further 14.3% re-captured on one occasion. Overall recapture time differences varied from less than 1 month to 71.8 months; mean 4.5 months, with 59% caught before the 100day cut off point and hence omitted from growth analysis. Those Green Turtles captured then recaptured at least once ranged from 32.9cm to 114.9cm in length, mean 48.4cm CCL. Growth rates varied between 0.468 and 10.67cm/yr CCL, average 5.18cm/yr (95% confidence), with the highest average level coming in 60-65cm and lowest in 105-110cm length increment (table 4.1). Other individuals outside these brackets showed significantly higher rates between recaptures, though this may have been a result of a number of factors to be discussed later. In terms of capture methods nearly 82% were caught using a standard net, 10% a longline, 4% by a line, and only a small percent by Uzio, hand, found stranded and washed ashore.

4.3 Hawksbill Turtle

In comparison to this the Hawksbill Turtle only registered 240 captures varying from 20.2 - 96.8cm CCL, mean 40.9cm. Recapture time varied from less than 1 month to 60.9 months and 9 recaptures for an individual the greatest number of times one Hawksbill Turtle was caught. 81% were only caught once and a further 11% re-caught on one occasion. Despite this only 19 turtle recaptures qualified above the 100 day cut off for the time difference between captures, with length ranging from 32.8-74.0cm CCL; mean 46.2cm. Growth for the Hawksbill’s ranged from 0.151-13.9cm/year and averaged 4.59cm/yr or 0.38cm/month (95% confidence) with the highest average rates coming in the 65-70cm CCL increment size.

5 Analysis

5.1 Growth of Green Turtles

Green Turtles in Watamu exhibit non-monotonic growth rates similar to those observed in the pacific and contrary to the Atlantic. Growth rates increase from hatchling to 50-55cm, level out, decrease between 65-75cm before a final spurt around 80cm and eventually slow down to negligible levels around 100cm onwards (fig 5.1, corresponding values fig 5.2). The slight increase at the end of their size range is likely to be more a result of a lack of data in the corresponding length increments, as opposed to an actual increase in growth rates. The statistically significant R2 value indicates a very strong fit of the data to the polynomial trend line which shows an increase in growth rates up to around 60cm before declining when the turtles move towards adulthood. The corresponding width growth rates show similar patterns, though with the strength of data being not as good, there are certain widths with no data available and it tends not to show the same peaks and troughs when plotted with the length analysis. The width peaks at 50-55cm CCW

40 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

and declines in a more linear fashion indicating it is less impacted on by varying growth rates than the length parameter. This graph also shows some negative rates that maybe a result of a higher uncertainty with width measurements due to greater methodological errors.

length ave rate ave in 0.6 (cm) cm/month cm/yr 0.5 0 0 0 R2 = 0.8349 h 35-40 0.310 3.725 t n 0.4 40-45 0.343 4.117 mo 0.3 45-50 0.421 5.050 m/ c 50-55 0.553 6.635 ( h t 0.2 55-60 0.500 6.006 w Series1 o r 0.1 60-65 0.559 6.702 G polynomial trendline 65-70 0.465 5.584 0 70-75 0.252 3.021 -0.1 0 20 40 60 80 100 120 75-80 0.390 4.684 Length (cm CCL) 80-85 0.388 4.651 85-90 0.222 2.663 Figure 5.1 Change in Green Turtles growth rates with respect to length 100-105 0.016 0.187 105-110 0.005 0.064 110-115 0.041 0.497

Figure 5.2 Values of average growth per increment

5.2 Hawksbill growth and graph

Hawksbill Turtle growth was determined on less data than that of Green Turtles (table 4.2) with rates differing considerably at certain points through their cycle. Again they show and steady increase up to a peak between 45-50cm CCL reaching a rate of 0.71cm/month before decreasing after this point to 55-60cm where there is another slight increase in rates. Ensuing rates decline to 0.06cm/month between 60-65cm before a significant increase to 0.82cm/month which distorts the set, between 65-70cm. This is the penultimate available recorded length and given the fact this is a single individual turtle and not an average of several it must be recognized with caution. The final point (70-75cm) shows lower growth but still high in comparison to increments. The relative R2 value is not significant and this is a result of the final two increments which cannot be eliminated due to a single recapture providing the data for these length increments (table 4.2). The corresponding growth rates with respect to width measurements show a similar pattern with the curve being distorted by the final two increments, potentially again due to the small sample size.

Exceptions to the average growth rate (4.59cm/yr) can be seen in some individual Hawksbill Turtles that showed marked increase in length. For example one individual averaged 0.86cm/month or 9.78cm/year taking only 4 years and 3 months to grow from 32.7cm to 74.0cm CCL, nearly twice the average rate stated above. Contrary to this another individual took 16 months to grow from 62.5 to 63.5cm CCL, demonstrating the differences in possible growth of such wild marine reptiles.

41 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

0.9

0.8 2 h t R = 0.2428 n 0.7 o m / 0.6 growth m

(c 0.5 trendline te 0.4 ra

th 0.3 w o r 0.2 G 0.1 0.0 0 1020304050607080 Length (cm)

Figure 5.3 Growth rate with respect to length (CCL) for Hawksbill Turtles in Watamu

5.3 Recapture times

The variation in numbers of both species of turtles caught between months and years show some interesting results (figures 5.4 and 5.5). Across both species there has been a relatively constant increase in returns since the project started to gain the support of the local fishermen in 1998 and 1999. This trend would be expected, though there is an obvious decrease in hawksbills from 2003 where numbers fell from around 65 to less than 30, drastically continuing the overall decline which started in 2001. The decline in Green Turtles from 2003 to 2004 is less extensive in terms of percentage of the total given the larger numbers involved.

600 90 80 500 70 i

400 60 E Cm f f o r o 50 r 300 e e b

b 40 m m 200 30 Nu Nu 20 100 10 0 0 1998 1999 2000 2001 2002 2003 2004 2005 year Cm Ei

Figure 5.4 Number of turtles caught in each year in Watamu, Kenya for Green (Cm) and Hawksbill (Ei) Turtles

The low levels observed for both species in 2005 is a result of the data only representing the first seven months of the year and so values are not representative of the total catch for a whole year. Calculations based on the average captures per month with respect to the total set indicate that the trend was set to continue for the whole of 2005 with numbers again not matching the previous years total for both species. These declines cannot easily be explained and could relate to changing environmental factors, periodic cycling of local turtle density or local fishing practices.

42 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

200 40 180 35 160 m 30 i

C 140 f E f

o 25

r 120 o e r b 100 20 e b m

80 15 m Nu

60 Nu 10 40 Chelonia mydas Eretmochelys imbricate 20 5 0 0 123456789101112 month of the year

Figure 5.5 Average number of Green (Cm) and Hawksbill (Ei) Turtles caught over the year in Watamu, Kenya

The variation in numbers of turtles caught throughout the year can also be seen to be significant (fig. 5.5). Green Turtles were caught most during the months of April, July, November and December with significantly lower values for January, February and August. Hawksbill Turtles vary slightly less with higher levels in June and October and less numbers in January, February, August and September. The differing numbers may relate to the migration patterns and ability to utilize habitats at different times of the year with respect to food availability. The differing species do show reduced numbers around the same time of year indicating maybe that external factors are affecting the numbers in the waters around Watamu as opposed to species related factors.

5.4 Annual growth rates

Fig 5.6 shows the varying growth rates per year for the two species. It can be seen that rates for Green Turtles fluctuates and appears to be relatively stable. However the reliability of this graph must be questioned though due to the number of data points available for the first 3 years. This analysis should be repeated in future years with a greater sample size to more reliably quantify any trends. Rates appear to be higher in 2001 and 2003 with a significant decrease in 2004. Two sample assuming unequal variance T-tests can be applied to the original individual values to analyze whether the fluctuations are statistically significant or not. The only year a significant difference is observed is between 2003 and 2004 where the drop in average growth rate is substantial for Green turtles. The reasons behind increased and decreased rates in different years is due to a complex system encompassing limiting factors of turtle growth which include food availability and sea temperature. The fluctuations may also simply be a result of the increased amount of data for particular years as opposed to overall increasing growth rates.

43 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

9

) 8 Cm 7 Ei 6 5 4 3 2 1 Average growth (cm/year 0 1999 2000 2001 2002 2003 2004 2005 Year

Figure 5.6 Average yearly growth for Green Turtles (Cm) and Hawksbill Turtle (Ei)

The same analysis on the differing growth between years was also carried out for the Hawksbill’s. However despite the apparent trend which seems to show a decline in overall growth rates there was insufficient data and no statistically significant pattern could be detected. This was also the case for Chaloupka and Limpus (1997) who could not be conclusive from their limited data set.

5.5 Error

The use of a measured error allows a higher level of statistical validity to be present with respect to the growth rates. Values of 0.3cm for CCL and 0.6cm for CCW were found from the multiple measurements taken on each turtle by the differing experimenters. These values represent the 95th percentile of the total error away from the respective combined mean value found for each individual turtle. The increased value for CCW is a result of the higher levels of uncertainty associated with the technique for measuring CCW, with these values higher than that observed by Seminoff et al. (2002) (0.1cm SCL) and Bjorndal and Bolten (1989) who reported 0.046cm precision. The observed values were deemed not to significantly affect the results with CCL used to calculate the growth rates, which showed a lower error level associated with human measurement. Also the significance of the error was reduced by virtue of the recaptures less than 100 days being removed for analysis purposes, which error would have affected more due to the relatively smaller changes in length occurring between recaptures.

5.6 Growth at age

In order to fully value the growth data it is imperative to be able to determine the growth at age and hence the age at maturity. This permits the complete lifecycle analysis on the turtles for the area to be examined and allows comparisons of these findings to other locations around the world. Despite no available ages for any of the Green Turtles in Watamu it is possible to estimate them with the use of a form of the von Bertalanffy equation used by Fabens (1965), described by Frazer and Ladner (1986):

-kt Lt = a(1-be ) Where Lt represents length at age t a= asymptotic length= longest turtle length found = 117.4 cm b= parameter related to size at birth e= base of natural log k= constant growth rate t= time

44 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

b can be calculated using rearrangement of Lo=a(1-b) where Lo is hatchling length (birth) (average from Watamu =5.61cm), and a is 117.4 (above) This gives b= 1-(5.61/117.4) b= 0.95 -k d k can be calculated using Lr = a - (a - Lc) e (Fabens, 1965), where Lr is length at recapture, Lc is length at first capture, d is time interval. Using one example of a turtle with significant time interval and growth (turtle tag KE0532 was used as it had a time interval of 3.43 years and its growth rate was very similar to that of the average rate of all Green Turtles found at Watamu), this could be calculated giving:

60.7 = 117.4 – (117.4 – 43.2) e- 3.43k

Rearranged k = 0.0683, consistent with Frazer and Ladner (1986) who calculated 0.075

e-0.068t Therefore: Lt = 117.4 (1- 0.95 )

From this equation by altering time t in years the length at age (Lt) can be calculated and plotted to graphically present a length at age graph for Green Turtles in Watamu (fig 5.7).

130 120 110 2 R = 0.9334 ) 100 L

C 90

C 80

m 70

(c 60 h t

g 50 n 40

le length polynomial trendline 30 20 10 0 02040age (years) 6080100

Figure 5.7 Estimated length at age for Green Turtles in Watamu based on the Von Bertalanffy growth function

Based on this graph in Watamu it would take 28.8 years for a female to reach nesting maturity assuming both sexes grow at equal rates, and based on the smallest known nesting female to be 101.7cm CCL, and approximately 103 years for it to reach the maximum length known to exist at this location: 117.4cm CCL. This is relatively similar to Seminoff et al. (2002) who estimated 9-21 years in Mexico to reach maturity after recruitment, and 9-24 years for estimated age at first maturity (Ehrhardt and Witham, 1992). The R2 value of 0.933 indicates a very strong fit of the data to the trend line increasing the significance of the results. This extrapolation to sizes outside the range of the empirical data, or in areas where no data is available, must be observed with caution due to the general unreliable properties of this method, especially when dealing with the von Bertalanffy function. Despite this, these values are the only available estimation from the Western Indian Ocean of the ages and corresponding lengths Green Turtles achieve in their life cycles.

45 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

6 Discussion

6.1 Green Turtles- Growth comparisons

The maximum growth rates found in Watamu, Kenya (10.67cm/yr) is significantly higher than those found in the Eastern Pacific and Western Atlantic, similar to research on the Great Barrier reef, and lower than specific studies in West Florida (Carr and Caldwell, 1956 in Balazs, 1995) which found growth ranged between 9-63.1cm/yr (converted from cm/month). This maximum value is the largest ever found (table 6.1). The lower limit of the range in Watamu (0.468cm/yr) produces slower rates than Balazs and Chaloupka (2004) (0cm/yr), Seminoff et al. (2002) (0.2cm/yr) and Limpus and Chaloupka (1997) (0.1cm/yr) as the lowest value in the respective ranges. Similar findings on the lower range may be affected by the age of the sampled turtles with few studies taking in the whole life span of lengths from post-recruitment to nesting turtles; most focus on the juvenile and sub adult stages. These very low levels are only found in turtles that have reached sexual maturity and whose growth rates have declined to negligibility.

The top of the range Watamu at 10.67cm/yr is greater than Hawaii (Balazs, 1995; Balazs and Chaloupka, 2004; Zug et al. 2002), Mexico (Seminoff et al., 2002), Florida (Zug and Glor 1998) and Heron Island (Limpus, 1979 in Balazs, 1995), comparable to Virgin Island (Schmidt, 1916) and fractionally less the GBR (Limpus and Chaloupka, 1997) where 10.8cm/yr was observed (table 6.1). In terms of mean values again Limpus and Chaloupka on the GBR found comparable levels at 4.2cm/yr and Schmidt (1916) in Virgin Island, U.S.A at 5.16cm/yr. Schmidt’s (1916) results should be used with caution as they were the first results worldwide and had limited data available.

These high rates found in the Western Indian Ocean may be a result of decreases in limiting factors such as food availability and population density impacts. No easily comparable data was available on population and density dependant factors but it is widely thought that the Atlantic and Pacific have higher numbers of turtles. The high rates could also be a result of the population having multiple foraging grounds and not having to travel distances to forage, or rather that any particular spatial distribution it could be simply the available foraging grounds provide more optimum conditions for growth.

Table 6.1 Alternative findings on Green Turtle growth rates, * Values converted from cm/month to cm/yr to allow for comparisons Researcher Location Range Mean Method Balazs (1995) Hawaiian 0.96-5.28cm/yr SCL Archipelago Balazs and Chaloupka Hawaiian 0–2.5 cm/yr SCL (2004a) Seminoff et al (2002) Mexico 0.2-3.4 cm/yr 1.4 cm/yr SCL Balazs et al (1996) Hawaii 1.7± 1.0 cm/yr Limpus and Chaloupka Great Barrier 0.1 to 10.8 cm/yr 4.2 cm/yr CCL (1997) Reef Zug and Glor (1998) Florida 3-5.2 cm/yr, Zug et al. (2002) Hawaii 0.6-4.4cm/yr 2.3cm/yr SCL Schmidt (1916) Virgin Island 1.2-8.3 cm/yr* 5.16 cm/yr* CCL Carr and Caldwell (1956) West Florida 9-63.1 cm/yr* SCL Burnett-Herkes (1974) Bermuda 0.48 cm/yr* SCL Limpus (1979) Heron Island 0.6-3.24 cm/yr* CCL

Watson (2006) Watamu, Kenya 0.468-10.67cm/yr 5.18cm/yr CCL

46 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

Possible reasons for higher growth rates may be a result of reduced density dependence with exploitation levels relatively high in Watamu and hence decreased competition for food (Zanre, 2005). Also some unique records of carnivory and/or omnivory have been made in the area which could contribute to the high growth rates.

6.2 Green Turtles- size specific increments

Comparisons of specific growth by length increment from around the world are similar compared to the rates of 4.58cm/year found in Watamu for the 40-50cm increment (adapted from 40-45 and 45-50 averages). From table 6.2 it can be seen that these rates are very similar to those found in the Bahamas, U.S Virgin Islands and Puerto Rico, and significantly higher than the Galapagos, Northwest Hawaiian Archipelago and Australia.

Table 6.2 Growth rates for the different increments, adapted from Green (1993)

Area Researcher Mean growth (cm/yr) 40-50cm 50-60cm 60-70cm Galapagos Green (1993) 0.40 0.45 0.15 GBR, Australia Limpus and Walter (1980) 0.75 0.95 1.43 Northwest Hawaiian Bjorndal and Bolten (1988)* 1.0 1.1 1.4 Archipelago Central Hawaiian Bjorndal and Bolten (1988)* 2.5 4.5 3.6 Archipelago Bahamas Bjorndal and Bolten (1988) 4.9 3.1 1.8 U.S Virgin Islands Boulon and Frazer (1990) 4.67 3.48 1.87 Puerto Rico Collazo et al. (1992) 6.0 3.8 3.9 Florida lagoon Mendonca (1981) - 3.14 2.81

Although overall growth rates are significantly higher than other areas, except for GBR, certain increments show very similar rates to Watamu. This may be a result of the differing range of the lengths used in the analysis with this research using full lifecycle data from recruitment at 39cm through to 117.4cm, the largest nesting females.

This study took into account the size at birth (hatchlings) and the whole post-recruitment phase, though growth rates were not known for the hatchlings. This is similar to Limpus and Chaloupka (1997), however only a very small proportion of turtles in the Watamu sample were sexually mature, unlike the sample from Australia. This entire lifespan is unseen in many studies across the world, particularly Bjorndal et al. (2000), allowing with a few assumptions a more detailed analysis of growth rates and relative influencing factors to be accounted for. This in depth analysis has not been carried out for Western Indian Ocean Green Turtles populations and the continuation of data collection by WTW and neighbouring projects is of paramount importance to confirm these growth rates and to enable the detection of potential changes that may result from anthropogenic impacts such as over-fishing and climate change. Such long term studies are critical for further development of conservation management plans.

From the findings on growth rates it can be seen that growth is non-monotonic with multiple phases and peaks of growth, similar to that witnessed in the Pacific and contrary to the Atlantic. Population densities may have a profound impact on the growth rates with the Pacific and Atlantic having much higher numbers of turtles which mite have a limiting effect on growth. Bjorndal et al. (2000) argue that further research is needed into nutrition, population dynamics and density dependence to more clearly understand the interactions of these factors on growth in the varying locations.

The growth graphs produced are similar to that seen in various foraging grounds in the Hawaiian archipelago which show overall increases in growth up to a varying certain point dependant on

47 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

location then decreases in a polynomial fashion to the maximum length caught. This is dissimilar though to alternative Hawaiian research by Zug et al. (2002) who found that growth rates decreased, from initial rapid growth in the small length increments, in a polyphasic fashion through the life cycle of the turtles.

6.3 Hawksbill Turtles- growth

The growth of Hawksbill Turtle in Watamu was comparable to that found in Puerto Rico of -0.59- 9.08cm/yr (Diez and van Dam, 2002) though maximum growth was observed at 45-50cm and 65-70 CCL lengths as opposed to 34 and 35cm SCL. These findings in terms of length increments are more similar to the southern GBR (Chaloupka and Limpus, 1997) where it was observed that despite only reaching 1.7cm/yr and 2.2cm/yr for males and females respectively, 60cm CCL was the length at which the greatest growth rates occurred. They also observed rates to decline around 80cm. Unfortunately the sampled turtles in Watamu did not reach this length and so comparisons cannot be made.

6.4 Hawksbill growth curve

The anomaly at 65-70cm increment (fig 5.3) shows a significant increase in growth in comparison to prior and subsequent increments. This may be a result of increased growth rates in 2002 and 2003 when the recaptures occurred. More likely though it is a result of the sample size being only one (table 4.2), which showed excessive growth between these recaptures and is not representative of what would be expected in a larger sample. This is more apparent when observing the subsequent increment (70-75cm), which shows a reduced rate with respect to this point, which is the same and only individual in the two increments. Due to the long time length between recaptures further analysis of why this anomaly occurs is difficult to distinguish. Potentially it could be a result of a number of complex interactions and changes in the abiotic factors affecting that individual turtle’s growth.

6.5 Recapture lengths

In terms of recapture intervals the range for Green Turtles (<1 month to 71.8 months) is significantly greater than documented times by Balazs (1995) of 2-20 months, but significantly less than the maximum of 13 years observed by Balazs and Chaloupka (2004). This is due to the time length of the longitudinal study and comparable times should be aimed for in Watamu. Also comparable recapture success was found with 64.5% caught once and 14.5% more than once, to Chaloupka and Limpus (2005) 68% and 21%. In contrast Balazs et al. (1996) obtained results of only 32% re-caught once, 27% twice with maximum recapture time at 7.3 years. These values are symbolic of the nature of the CMR technique as a result of the difficulty in tagging wild marine reptiles, but show that Watamu has achieved great success with a relatively new program and has the potential to be better than any other in collecting data of this kind.

6.6 Recapture times

The drop in recaptures in 2004 (see fig 5.4) is due to number of possibilities. Either there was a shortage of available food in the locality and the turtles foraged elsewhere, disease spread through the population, or perhaps even if food availability stayed constant other foraging grounds offered more optimum conditions that year. Fishing practices may also play a role. If there was a lack of fish more may have been slaughtered by the locals instead of giving them to WTW, or perhaps fishing methods changed for the better resulting in fewer turtles being caught. Further to this monthly variation may reflect cycles in fish stocks being available to fishermen, and yearly changes possibly accounting for a shift in employment in the area with increasing tourism providing alternative, more prosperous economic opportunities to fishing. Unfortunately no data is available to confirm this speculation.

48 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

7 Limitations

Due to the nature and difficulty of a longitudinal study of wild marine reptiles, a number of limitations and anomalies occur in the methodology, data recording, analysis of results and interpretation of findings which must be recognized and appropriately acknowledged to ensure the reliability and success of such research.

Firstly due to the temporal design of the study there have been a variety of different staff responsible for taking morphometric measurements in Watamu, which may have resulted in inconsistencies in technique. Taking the mean of repeat measurements helps average out the error but in certain extreme circumstances (if an experimenter constantly over or under measures) does not compensate for the error.

Secondly identification and recording errors occur with corroded tags being unidentifiable and miscommunication resulting in notation errors which can in turn contribute to anomalous results of recapture time and growth, and these should be screened for and removed whenever possible. An example of this is where a turtle has grown 10cm in a month; this is obviously an error of some sort. In this case that point was ignored and the subsequent recapture information was used.

Thirdly, a number of considerations had to be addressed when calculating growth rates. A number of zero or negative rates were found which could be a result of errors in measurement, identification, and recording or could simply be due to the turtle not growing or shrinking. These were included in the analysis where deemed not to be an error, as this phenomenon is known to occur and there is no valid reason not to include them (Chaloupka and Limpus, 1997), or statistical basis (Lutz and Musick, 1997). Many of these were eliminated in the first cut of the data when those turtles with recapture intervals of greater than 100days which removed the labour involved in checking through the rest of the data.

Another limitation of the data was that growth was considered in increments only with no means of incorporating other variables which may have influenced growth between two samples of an individual turtle e.g. seasonal changes. More complex multi-variable analysis might be possible in the future when the data set increases in size.

The relatively abundance and lack of data pints in certain increments results in varying levels of reliability. Some increments have high sample sizes and are more reliable, whilst others have significantly lower sample sizes and hence anomalous records within these small samples having a higher affect on the growth rate for that specific increment. In general most of the data lies in the mid-length increments with less at the ends of the range. This reduces the reliability when comparing rates between increments and in cross species analysis. In some cases where there are very few values it is impossible to judge whether points are anomalies or not as suspect records cannot be eliminated as they are the only reference point in that increment. This is seen specifically with Hawksbill Turtle where there is a lower level of initial empirical data in a number of increments (table 4.2).

In addition to the disadvantages of very short recapture intervals, long recapture intervals are also problematic. Some turtles grew through several size increments between recaptures, (e.g. 65-70 to 75-80) particularly if the time interval was long using the average gain over the two periods may not representative either increment category correctly. Extrapolation beyond the known growth using the von Bertalanffy growth function is also of uncertain accuracy and caution must be observed when applied in this way (Bjorndal et al., 2000). This is the case for the 90-95 and 95- 100cm increments, for which no empirical data was available.

When plotting growth against time a series of problems occur. One such example is if a recapture occurs at the start of the month it may have little or no relation to that corresponding month.

49 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

This is because most of the growth would have occurred in the months preceding the point it was recaptured, and hence is not representative of that particular month.

In an ideal world the results would have been compared against a comparative analysis from a different technique. For example skeletochronology could have been used to back up the length based growth rate analysis. This would have helped determine which proportions of the growth curves are more, or less, reliable and would facilitate a more accurate estimation of the age from length data.

8 Further work

• The use of growth functions to estimate age from size opens up a range of new options for data analysis for WTW and can assist in determining the life history traits of local Green and Hawksbill turtles. However, detailed comparisons of turtle’s size at age and growth at age are beyond the scope and objectives of this research. A more in-depth investigation could be continued culminating in an estimation of the age structure of the population in Watamu. • Other further work in this area could include the different sex specific growth rates, as at present no recording of the sex takes place in Watamu. However this is very difficult to identify from physical characteristics alone. • A repeat of this study in the future would not only provide a greater reliability in the findings here, but allow for results to be put into a wider context. Recapture patterns, monthly and annual variations in growth rates could be analysed over longer time periods helping eliminate the need for extrapolation of results out of the empirical boundaries constricting this research. • Comparisons in the variation of sea turtle growth rates with geographical latitude has had limited input of both time and finance, with potential trends occurring in the observed rates with respect to this variable. Further research into this area may result in a wider appreciation of the influence of this variable in terms of sea water temperature on the growth of sea turtles. • The correlation between weight, growth and age is another area of limited study which could be further investigated by WTW. • Since growth rate research is yet to be identified in conjunction with abiotic and anthropogenic impacts, WTW may consider future data collection relating to these factors.

9 Conclusion

Watamu has yielded highly varied growth rates both among Green and Hawksbill Turtles, with overall rates being similar to those observed in Australia. A non-monotonic increase was observed like that witnessed in the Pacific and contrary to those found in the Atlantic. No comparison was possible to other Western Indian Ocean data due to lack of published material from this area, emphasising the importance of this data set as the only representative of this region. Comparison between species found Green Turtles have higher average growth and with respect to specific length increments, but Hawksbill Turtles have a greater range with individuals exhibiting rapid rates. However the observations must be treated with caution due to limitations in data structure and sample size. Individual increment averages fit significantly better to similar averages found worldwide for Green Turtles and the estimation of age with respect to length gives an indication of the time taken for the average individual to reach different stages of the lifecycle in Watamu. The variation in yearly recaptures and growth are a result of external environmental factors, with determination of these beyond the scope of this study. The associated human errors found with the measurements highlight the potential problems

50 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

associated with the design of the research, though were not deemed to have a significant impact on the calculation of growth rates.

Acknowledgements

Serious thanks go to Watamu Turtle Watch and staff: Steve Trott, Jane, Kahindi, Jonathon and Nelson for their efforts in long term data collection and support in making this research possible. Also special thanks to Kathleen Calf for assistance in development of data analysis techniques and Alison Cameron, WTW volunteer co-coordinator, for help in project idea development, both formerly of Leeds University. Also thanks to tutor Andy Dougill for proof reading (School of Earth and Environment, Leeds University).

References

Baillie J & Groombridge B (1996) 1996 IUCN Red List of Threatened Animals. IUCN, Gland, Switzerland. Balazs GH (1995) Growth rates of immature green turtles in the Hawaiian Archipelago, in Bjorndal K A (ed), Biology and conservation of sea turtles revised edition, University of California, Smithsonian institute press. pg 117-124 Balazs GH, Rice M, Murakawa SKK & Watson G (1996) Growth rates and residency of immature Green Turtles at Kiholo Bay, Hawaii,, In press. Proceedings of the Sixteenth Annual Symposium on Sea Turtle Biology and Conservation, February 27-March 2, Hilton Head, South Carolina. Balazs GH (1999) Factors to consider in tagging of sea turtles, in Eckert K L., Bjorndal K A., Abreu- Grobois F A and Donnelly M (eds), Research and Management Techniques for the Conservation of Sea Turtles, IUCN/SSC Marine Turtle Specialist Group Publication No. 4 Balazs GH & Chaloupka M (2004a) Thirty-year recovery trend in the once depleted Hawaiian green sea turtle stock Biology Conservation 117, 491–498 TBalazs GH & Chaloupka M (2004b) Spatial and temporal variability in somatic growth of green sea turtles (Green Turtles) resident in the Hawaiian Archipelago Marine Biology 145 (5): 1043-1059 Bjorndal KA (1985) Nutrition ecology of sea turtles Copeia 1985; 736-751 Bjorndal KA & Bolten AB (1988) Growth rates of immature green turtles, Green Turtles, on feeding grounds in the southern Bahamas Copeia 3, 555-564 Aug 3 Bjorndal KA & Bolten AB (1989) Comparison of straight-line and over the curve measurements for growth of green turtles (Chelonia mydas), Bulletin of marine Sciences 45:189-192 Bjorndal KA, Bolten AB, Coan AL & Kleiber P (1995) Estimation of green turtle (Chelonia-mydas) growth- rates from length-frequency analysis Copeia (1): 71-77 Bjorndal KA, Bolten AB, Bennett RA, Jacobson ER, Wronski TJ, Valeski JJ & Eliazar PJ (1998) Age and growth in sea turtles: Limitations of skeletochronology for demographic studies Copeia (1): 23-30 Bjorndal KA, Bolten AB & Chaloupka MY (2000) Green turtle somatic growth model: Evidence for density dependence Ecological Applications 10 (1) 269-282 Bjorndal KA, Bolten AB, Koike B, Schroeder BA, Shaver DJ, Teas WG & Witzell WN (2001) Somatic growth function for immature loggerhead sea turtles, Caretta caretta, in south-eastern U.S. waters, Fish. Bull. 99:240–246 Bjorndal KA, Bolten AB, Dellinger T, Delgado C & Martins HR (2003) Compensatory growth in oceanic loggerhead sea turtles: Response to a stochastic environment Ecology 84 (5): 1237-1249 Bolten AB (1999) Techniques for Measuring Sea Turtles, in Eckert K L., Bjorndal K A., Abreu-Grobois F A and Donnelly M (editors), Research and Management Techniques for the Conservation of Sea Turtles, IUCN/SSC Marine Turtle Specialist Group Publication No. 4 Boulon RH jnr & Frazer NB (1990) Growth rates of wild juvenile Caribbean green turtles, Chelonia mydas, Journal of Herpetology 42:441-445 Burnett-Herkes J (1974) Returns of green turtles (Chelonia mydas Linnaeus) tagged at Bermuda Biology Conservation 6: 307-308 Bustard R (1972) Sea turtles- natural history and conservation, William Collins sons & Co Ltd Glasgow. Pg 25, 137-139 Carr A (1995) Notes on the Behavioural Ecology of Sea Turtles, in Bjorndal K A (ed), Biology and conservation of sea turtles revised edition, University of California, Smithsonian institute press, 19 Chaloupka MY & Limpus CJ (1996) Robust statistical modelling of Chelonia mydas growth rates- southern great barrier reef proc 15th annual symp. Sea turtle biology and conservation. Chaloupka MY & Limpus CJ (1997) Robust statistical modelling of hawksbill sea turtle growth rates (southern Great Barrier Reef) Marine Ecology-Progress Series 146 (1-3): 1-8

51 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

Chaloupka MY & Musick JA (1997) Age, growth and population dynamics. In: Lutz PL, Musick JA (eds) The biology of sea turtles, chap 9. CRC Marine Science Series, CRC Press, Boca Raton, Fla., pp 233– 276 Chaloupka MY, Limpus C & Miller J (2004) Green turtle somatic growth dynamics in a spatially disjunct Great Barrier Reef metapopulation Coral Reefs 23:325–335 Chaloupka MY & Limpus C (2005) Estimates of sex- and age-class-specific survival probabilities for a southern Great Barrier Reef green sea turtle population Marine Biology 146 (6): 1251-1261 CIA (2006) World Factbook: Kenya, http://www.cia.gov/cia/publications/factbook/geos/ke.html [26/02/06] Collazo JA, Boulon R & Tallevast TL (1992) Abundance and Growth-patterns of Chelonia mydas in Culebra, Puerto-Rico Journal of Herpetology 26 (3): 293- Davenport J & Scott CR (1993) Individual growth and Allometry of young Green turtles (Chelonia-mydas L) Herpetological Journal 3 (1): 19-25 Day T & Taylor PD (1997) Von Bertalanffy’s growth equation should not be used to model age and size at maturity. Am. Nat. 149:381–393. Diez CE & van Dam RP (2002) Habitat effect on hawksbill turtle growth rates on feeding grounds at Mona and Monito Islands, Puerto Rico Marine Ecology-Progress Series 234: 301-309 Ehrhardt NM & Witham R (1992) Analysis of Growth of the Green Sea-Turtle (Chelonia mydas) in the Western Central Atlantic Bulletin of Marine Science 50 (2): 275-281 Fabens AJ (1965) Properties and fitting of the von Bertalanffy growth curve Growth 29: 265-289 Flanagan J (2000) Disease and health considerations, in Klemens M W, 2000, Turtle Conservation, Smithsonian press, pg 94 Frazier J (1995) Status of Sea Turtles in the Western Indian Ocean, in Bjorndal K A (ed), 1995, Biology and conservation of sea turtles revised edition, University of California, Smithsonian institute press, pg 385 Frazer NB & Ladner RC (1986) A growth curve for green sea turtles, Chelonia mydas, in the U.S Virgin Islands, 1913-14 Copeia 1986: (3) 798-802 Frazer NB & LM Ehrhart (1985) Preliminary growth models for green, Chelonia mydas, and loggerhead, Caretta caretta, sea turtles in the wild: Copeia 1985:73–79. Green DJ (1979) Double Tagging of Green Turtles in the Galapagos Islands, Marine Turtle Newsletter, 13 4-9 Green DJ (1993) Growth Rates of Wild Immature Green Turtles in the Galapagos Islands, Ecuador Journal of Herpetology 27 (3) 338-341 Groombridge B & Luxmoore R (1989) The Green Turtle and Hawksbill (Reptilia: Cheloniidae): World Status, Exploitation and Trade. Secretariat of the Convention on International Trade in Endangered Species of Wild Fauna and Flora, Lausanne, Switzerland, 601 pp. Hays GC (2004) Good news for sea turtles Trends in Ecology and Evolution 19, 7, 349-351, July 1 Hillestad HO, Richardson JI, McVea C jnr & Watson JM jnr (1995) Worldwide Incidental Capture of Sea Turtles, in Bjorndal K A (ed), Biology and conservation of sea turtles revised edition, University of California, Smithsonian institute press, 489-491 Hilton-Taylor C (2000) IUCN Red List of threatened species: IUCN, Gland, Switzerland. Hirth HF (1997) Synopsis of the biological data on the green turtle, Chelonia mydas (Linnaeus 1758). United States Fish and Wildlife Service Biological Report 97-1. 120 Jones RL & Hartfield PD (1995) Population-size and growth in the turtle Graptemys oculifera Journal of Herpetology 29 (3): 426-436 Kennett R (1996) Growth models for two species of freshwater turtle, Chelodina rugosa and Elseya dentata, from the wet-dry tropics of Northern Australia Herpetologica 52 (3): 383-395 Klemens MW (2000) Turtle conservation, Smithsonian institution press, Washington and London. Pg 86, 110 Kobayashi M (2000) An analysis of the growth based on the size and age distributions of the hawksbill sea turtle inhabiting Cuban waters Japanese Journal of Veterinary Research 48 (2-3): 129-135 Limpus CJ (1992) Estimation of tag loss in marine turtle research Wild. Res. 19 (3) 457 Limpus C & Chaloupka M (1997) Nonparametric regression modelling of green sea turtle growth rates (southern Great Barrier Reef) Marine Ecology-Progress Series 149 (1-3): 23-34 Limpus CJ, Couper PJ & Read MA (1994) The green turtle, Chelonia mydas, in Queensland: population structure in a warm temperate feeding area. Mem. Queensland Mus. 35, 139–154. Limpus CJ & Reed PC (1985) The green turtle, Chelonia mydas, in Queensland: a preliminary description of the population structure in a coral reef feeding ground. In: Grigg G, Shine R, Ehmann H (eds) Biology of Australasian frogs and reptiles. Royal Society of New South Wales, Sydney, Australia, pp 47–52 Lutz PL & Musick JL (1997) Biology of sea turtles, by CRC Press LLC pg 234+

52 Watson DM (2006) Growth rates of sea turtles in Watamu, Kenya Earth & E-nvironment 2: 29-53

Mortimer JA (1988) management options for sea turtles: re-evaluating priorities. Florida defenders of the environmental bulletin 25:1-4 Musick JA & Limpus CJ (1997) Habitat utilization and migration in juvenile sea turtles. In: P.L. Lutz and J.A. Musick (eds) The Biology of Sea Turtles, pp. 137-164. CRC Press, Boca Raton, Florida. National Research Council (1990) Decline of sea turtles: causes and prevention. National Academy Press, Washington D.C. Ratowsky DA (1986) Statistical properties of alternative parameterizations of the von Berlantafy growth curve Canadian journal of fisheries and aquatic science 43 742 Ratowsky DA (1990) handbook of non linear regression models, Marcel Dekker, New York, 1990 Seminoff JA, Resendiz A, Nichols WJ & Jones TT (15/08/02) Growth rates of wild green turtles (Chelonia mydas) at a temperate foraging area in the Gulf of California, Mexico Copeia (3): 610-617 Seminoff J (2002) 2002 IUCN Red list global status assessment, green turtle, Chelonia mydas. IUCN Marine Turtle Specialist Group Review, 93 Schmidt J (1916) Marking experiments with turtles in the Danish West Indies. Meddeleiser fra Kommissionen for Havundersogelser Serie Fiskerie, 5, 1-26 Wood F & Wood J (1993) Turtles, Chelonia mydas, in the waters surrounding the Cayman-islands Herpetological Journal 3 (3): 84-89 Worldatlas. (2006), Outline of Africa map, http://worldatlas.com/webimage/countrys/africa/afoutl.htm, [26/02/06] WTW. (2006) Watamu Turtle Watch- Local Ocean Trust, http://www.watamuturtles.com/index.htm, [10/11/05] Zanre R (2005) Report on Watamu Turtle Watch’s sea turtle bycatch release programme, Watamu, Kenya, April 1998- May 2004, unpublished, http://www.watamuturtles.com/reports.htm [10/01/06] Zug GR, Balazs GH, Wetherall JA, Parker DM & Murakawa SKK (2002) Age and growth in Hawaiian green sea turtles (Chelonia mydas): an analysis based on skeletochronology. Fish Bull 100:117–127 Zug GR & Glor RE (1998) Estimates of age and growth in a population of green sea turtles (Chelonia mydas) from the Indian River lagoon system, Florida: a skeletochronological analysis Canadian journal of zoology-Revue Canadienne de Zoologie 76 (8): 1497-1506

53