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This editorial focuses on the Plan’s updated demographic model and Threats Analysis, which are inextricably interdependent and highly consequential. Application of the updated model affected the (1) estimated annual rate of increase in the population, (2) downlisting and delisting criteria, (3) forecasts of when downlisting and delisting criteria might be achieved, (4) life-stage reproductive values, RVs (converted to relative reproductive values, RRVs, used in the Threats Analysis), and (5) prioritization of recovery actions. The Threats Analysis also was used to prioritize recovery actions.
Demographic Model. The KRRT updated the Heppell et al. (2005) demographic model with new information from NMFS & USFWS (2007) and the Plan. The Plan’s updated model is deterministic and based on the concept that population growth occurs when additions (hatchling releases) exceed losses (deaths due to all causes), assuming that additions through immigration and losses through emigration can be ignored because data are available for the entire species (Heppell et al. 2007). Other assumptions underlying the Plan’s application of its updated model were (1) stable (constant) age and life stage distributions, (2) constant age of 12 yr at sexual maturity, and (3) constant survivorship within (but not among) each life stage-ecosystem combination defined in Table A1-2 of the Plan.
Kemp’s ridley age and life stage distributions (i.e., age and life stage structures, indexed by size distributions) have not been stable (see Chavez et al. 1968; Heppell et al. 2007; TEWG 2000; Witzell et al. 2005). They must have changed as new cohorts (year-classes) of increasing numbers of hatchlings were released annually from nesting beaches in Tamaulipas, beginning with restoration of hatchling production in 1966 by Mexico. The step increase in annual hatchling production that occurred in 1978 with implementation of the binational restoration and enhancement program, and the exponential increase in annual production that has occurred since 1985 (Heppell et al. 2007) probably accelerated change in age and life stage distributions. Age and life stage distributions could also have changed as a result of major reductions in at-sea mortality, due to turtle excluder devices (TEDs) and declines in shrimping effort in the Gulf of Mexico (USFWS & NMFS 1992; Caillouet et al. 2008; Nance et al. 2010). Restoration and enhancement of annual hatchling production rebuilt the population’s age and life stage structures and restored population momentum (see Heppell et al. 2005, 2007; Keyfitz 1971; TEWG 1998; Vincent, 1945). Theoretically, a sea turtle population with momentum can continue to grow for a time, even if annual hatchling production immediately declines to replacement level. This continued growth results from accumulated immature age groups that eventually enter the adult life stage and begin reproducing.
To illustrate the accumulation of age groups as one factor in changing age structure in the Kemp’s ridley population, I estimated the minimum number of age groups, gt, in the population in years following 1965 with a simple equation, gt, = t – 1965, where year t > 1965. I assumed (1) age at maturity of 10 yr (Caillouet et al. 1995; Heppell et al. 2005; Marquez-M. 1994; TEWG 1998), (2) lack of annual hatchling production for at least 10 yr prior to 1966 (TEWG 1998), (3) “young” (i.e., neophyte) nesters were distinguishable from the “old” nesters (those that did not originate from hatchling releases that began in 1966 (Marquez-M. 1994), and (4) each age group in the population after 1965 was represented by at least 1 survivor. Marquez-M. (1994) observed that “young” nesters first appeared at Rancho Nuevo in 1976, 10 yr after annual hatchling production was restored; he also noted that no “old” nesters were observed after 1983. “Old” and “young” nesters were distinguished by differences in body weight and by tagging-recapture of nesters (P.C.H. Pritchard, personal communication, August 2009). Age groups represented by “old” nesters during 1966-1983 were not included in my calculations, and that is why gt, is a minimum. Hatchlings (young-of-the-year) were designated age group 0, and included in each year.
There could have been as many as 21 age groups (20 to 0 for year-classes 1966-1986, respectively) in the population in 1986, the year in which the population decline reversed; 10 represented by non-adults (age groups 9 to 0, year-classes 1977-1986) and 11 represented by adults (age groups 20 to 10, year-classes 1966- 1976). The population in 2010 could have contained as many as 45 age groups (44 to 0 for year-classes 1966-2010, respectively), 10 represented by non-adults (age groups 9 to 0, year-classes 2001-2010) and 35 represented by adults (age groups 44 to 10, year-classes 1966-2000). In this illustration, the number of non-adult age groups remains constant once it equals age at maturity. However, the number of adult age groups increases thereafter, and continues to increase until the last survivor in the oldest age group dies. Longevity has not been determined for Kemp’s ridley, but it probably exceeds 44 yr. Although the number of age groups has been increasing linearly (1 per yr) since 1966, cohort size (annual number of hatchlings released) has been increasing exponentially since 1985 (Heppell et al. 2007). The number of individuals in each cohort declined over time due to mortality from all causes, but mortality did not remain constant during 1966 through 2010. Changes in mortality rate combined with restoration of hatchling production in 1966, the step increase in hatchling production after 1977, and the exponential increase in hatchling production after 1985, have been powerful generators of change in age and life stage structures in the population. In other words, Kemp’s ridley population age structure will not stabilize until the longevity is reached and annual hatchling inputs stabilize.
I am unaware of any published, long-time-series tabulations of the annual numbers of “young” or presumed neophyte nesters compared to annual numbers of “old” or presumed non-neophyte nesters in Tamaulipas, despite all the observations made on nesters beginning in 1966 (Márquez-M. 1994; Leo Peredo et al. 1999). Even though presumed neophyte nesters may not all be true neophytes (i.e., first-time nesters), the proportion they represent of the total annual nesters would be useful to demographic modeling.
Results of demographic modeling are sensitive to assumed age at maturity (Heppell et al. 2005, 2007; NMFS & USFWS 2007; TEWG 1998, 2000). Considerable uncertainty surrounds the estimation of Kemp’s ridley age at maturity from size-age relationships. The Plan discussed monophasic (von Bertalanffy) and polyphasic size-age relationships in free living Kemp’s ridleys (Chaloupka and Zug 1997; Snover et al. 2007). Both monophasic and biphasic relationships have been fitted to size and known-age data for head started Kemp’s ridleys released into the Gulf of Mexico (Caillouet et al. 1995; Snover et al. 2008). Challenges in the estimation of sea turtle age at maturity were thoroughly discussed by Chaloupka & Musick (1997) who suggested use of a polyphasic model to describe Kemp’s ridley growth. Day & Taylor (1997) demonstrated that the von Bertalanffy growth equation should not be used to estimate size and age at maturity, but it has been widely applied to estimate Kemp’s ridley age at maturity (Snover et al. 2007). Chaloupka & Zug (1997) indicated that the von Bertalanffy growth equation should not be used to describe growth or estimate age at maturity in Kemp’s ridley. Heino et al. (2002) recommended a probabilistic (stochastic) approach to estimating size and age at maturity. In the face of uncertainty about estimates of age at maturity, Heppell et al. (2005) and TEWG (1998, 2000) wisely ran models assuming 8, 10, and 12 yr at maturity then compared their goodness of fit to selected time series of annual numbers of nests and hatchlings. Models assuming 10 yr at maturity produced the best fits to selected time series of annual number of nests (Heppell et al. 2005; TEWG 1998). Interestingly, to the degree such models represent Kemp’s ridley population dynamics, they might offer another useful approach to estimating Kemp’s ridley age at maturity; i.e., by simulation. Marquez-M. (1994) gave an account of Kemp’s ridley nesting at Rancho Nuevo, Tamaulipas, Mexico during years in which the population was declining. It provided evidence of age 10 yr at maturity, based on his observation that “young” nesters first appeared at Rancho Nuevo 10 yr after annual hatchling production was restored. It would have been informative had Marquez-M. (1994) presented the annual proportions that “young” nesters represented of the total nesters (“young” plus “old”) each year. In any case, age 10 yr. should not be taken as a minimum age at maturity, because some “young” females that nested in 1976 might have nested in prior years and not been observed (see Pritchard 1990). Neither should it be taken as maximum age at maturity. Marquez-M. (1994) concluded that Kemp’s ridleys “begin to mature” at ages 10-18 yr, based on the disappearance of “old” nesters by 1984 (i.e., 1984 − 1966 = 18 yr), but he offered no persuasive evidence supporting such a wide range in age of neophyte nesters. In the absence of information from tagging hatchlings and later recapturing them as nesters with tags linking them to a particular year-class, the disappearance of “old” nesters is not sufficient evidence. Interestingly, Francis (1978) believed that transplantation of thousands of eggs from Rancho Nuevo to South Padre Island, Texas in the 1960s by Deal Adams and other volunteers (Sizemore 2002) resulted in 3 nestings (and other observations of adult females) in South Padre Island in the 1970s. Examination of the data (Francis 1978; Sizemore 2002) suggest a time lag around 10 yr. Notwithstanding uncertainty in estimates of age at maturity, the KRRT picked only one (12 yr) for modeling, without adequate explanation or justification.
Survivorship of benthic life stages vulnerable to incidental capture in shrimp trawls has not been constant, but increased post- 1990 (TEWG 1998, 2000; Heppell et al., 2005, 2007). Therefore, post-1990 increases in time-lagged (by age at maturity) annual numbers of nests were more rapid than could be explained by increases in numbers of age groups and hatchlings released (i.e., cohort size) years earlier. Estimation of a post-1990 instantaneous mortality multiplier was incorporated into demographic models to account for post-1990 increases in survival of benthic life stages (TEWG 1998, 2000; Heppell et al., 2005, 2007). These increases in survival of benthic life stages not only reflected the use of turtle excluder devices (TEDs) in shrimp trawls but also a decline in shrimp trawling effort in the northern Gulf of Mexico (Caillouet et al. 2008; Heppell et al. 2005, 2007; Nance et al. 2010; NMFS 2007; TEWG 1998, 2000; the Plan). The relative effects of TEDs and the decline in shrimping effort on the Kemp’s ridley population have not been evaluated.
Model-estimated rates of increase in annual number of nests were also sensitive to the time-series of nests and hatchlings chosen for modeling (Heppell et al. 2005, 2007; TEWG 1998, 2000). When time series were updated, the estimated annual rates of increase in nests increased (Heppell et al. 2007). This suggests that additional unknown factors related to updating of the time series were responsible, apart from hatchling inputs, effects of TEDs, and decline in shrimping effort. The post-1990 multiplier was also sensitive to the chosen time series of nests and hatchlings and assumed age at maturity (TEWG 1998, 2000; Heppell et al. 2005, 2007). Perhaps the combination of assumed age at maturity and selected time series acted together to accelerate the estimated population growth rate. Such phenomena emphasize the importance of updating the data time series and parameter estimates, and employing more than one age at maturity in demographic modeling simulations. The time series used by Heppell et al. (2005) and the Plan ended with year 2003, but such data were available through 2009, according to the Plan. In defense of the KRRT, its updated model and Threats Analysis were developed early in the planning process <http://www.fws.gov/kempsridley/meetingminutes.html>, but they were out of date by the time of peer-review in 2006 and they are more out of date now.
The Plan stated, “Juvenile Kemp’s ridleys spend on average 2 years in the oceanic zone …”, and duration of the “oceanic stage” apparently was assumed to be 2 yr for purposes of modeling (Heppell et al. 2005; TEWG 1998, 2000). Caillouet et al. (1997) showed that head started Kemp’s ridleys reached 19.5 cm in estimated mean straight carapace length (SCL) in 1 yr., based on a growth curve fitted to combined SCL and age data from 15 year-classes (1978- 1992). The range in mean SCL at age 1 yr, estimated individually for each year-class separately, was 14.7-24.6 cm. Sizes of these head started 1-yr-olds are comparable to those of post-pelagic juveniles (i.e., “21 cm SCL”) mentioned in the Plan; but, the Plan implicitly defined “oceanic” juveniles as “< 20 cm” SCL. Granted, the head started turtles were reared in captivity and fed manufactured, floating food pellets. However, management of feeding methods and levels improved over the years, with later year-classes receiving less food than earlier ones, yet there was no significant trend in estimated mean SCL at age 1 yr over the year-classes. In addition, the Plan stated, “… coloration changes significantly during development from the grey-black dorsum and plastron of hatchlings, [to] a grey-black dorsum with a yellowish-white plastron as post pelagic juveniles…” Head started Kemp’s ridleys have the same coloration pattern as 1-yr-old free-living post-pelagic juvenile. The Plan’s catch curve analysis indicated that 2-yr-olds were considered to be in the benthic juvenile stage (see also TEWG 1998, 2000; Heppell et al. 2005), and not in the “hatchling swim frenzy, transitional stage”. Therefore, I believe it more likely that the duration of the “hatchling swim frenzy, transitional stage” is 1 yr rather than 2 yr, especially in the Gulf of Mexico. However, the “hatchling swim frenzy, transitional stage” could easily last more than a year in colder Atlantic waters along the eastern U.S. coast. I suggest such discussion be added to the Plan, primarily because the assumed amount of young-of-the-year Kemp’s ridleys spend in the pelagic stage affects results of demographic modeling. Model simulations using 1 yr in the “hatchling swim frenzy, transitional stage” might be revealing.
I have one additional concern about the description and application of the updated model. I was unable to determine from the Plan’s description of the model how the estimated remigration rate (2 yr) was applied to first-time (neophyte) nesters as compared to its application to repeat nesters. If applied in the same way to first-time nesters, it might lower the number of nests laid by first-time nesters by half. Such an effect would propagate over time and affect model forecasts of numbers of nests and hatchlings, as related to downlisting and delisting criteria. My perception could be wrong, but regardless, this requires clarification in the Plan.
Threats Analysis. Clark et al. (2002) and Lawler et al. (2002) examined large samples of recovery plans and concluded that they could be improved by a focus on threats. In response, the KRRT prepared a Threats Analysis adapted from the recovery plan for the Northwest Atlantic loggerhead (Caretta caretta) (<http://www.nmfs.noaa.gov/pr/pdfs/recovery/turtle_loggerhead_atlantic.pdf>). Because of this, my comments about the Plan’s Threats Analysis also apply to its prior application to loggerheads. The Plan defined six life stages (nesting female, egg, hatchling, transitional*, juvenile, and adult), three ecosystems (terrestrial, neritic, and oceanic), and seven threat categories (resource use-fisheries bycatch, resource use-non-fisheries, construction, ecosystem alterations, pollution, species interactions, and other factors). Some cells of the summary tables (“threats matrices”) in Appendix 1 contained results of the Threats Analysis, and some were annotated by imbedded explanatory comments that pop up when the cursor is placed over them.
*Hatchling frenzy stage and post-hatchling transitional stage combined.
Two major components of the Plan’s Threats Analysis were (1) RRV for each life stage, and (2) annual mortality indices based on hypothetical, geometrically-scaled annual mortality class intervals associated with each threat category and life state-ecosystem combination. The Plan stated, “Because of the potential volatility of reproductive value as a scalar, the threat tables presented here should be viewed qualitatively rather than quantitatively, and be updated with new monitoring data on a regular basis.” However, the Threats Analysis based on RRVs and the annual mortality indices were clearly quantitative, as stated elsewhere in the Plan; i.e., “To facilitate quantifying and presenting the threats affecting the Kemp’s ridley, the three elements (life stage, ecosystem, and specific categories of threats) were combined into a matrix using Microsoft Excel (Table A1-2).”
The Plan’s definition, explanation, and estimation of reproductive value were inadequate. The Plan gave the following definition of reproductive valued: “An individual’s potential for contributing offspring to future generations is its reproductive value (RV, Table A1-4 in the Plan). The reproductive values were developed using an updated stage-based demographic model for the Kemp’s ridley (S. Heppell, Oregon State University, unpublished data, see Demographics section for detail on the model inputs).”
Fisher (1930) introduced the concept of reproductive value, which is used to study populations with age structure and other kinds of structure (Grafen 2006). Below is Grafen’s (2006) description of reproductive value, paraphrased with added terminology from the Plan: (1) Reproductive value is a quantitative measure, for individuals or subsets of individuals in a population, that indicates their relative importance in evolutionary processes. In other words, an individual’s reproductive value measures its contribution to the gene pool of future generations. (2) Subsets of a population can include individuals and groupings of individuals such as age groups, life stages, sexes, size classes, and the like. Such subsets have reproductive values which should be used as weights in calculating an average gene frequency over the whole population. (3) Reproductive value of a subset, apart from possible re-scaling for convenience (e.g., converting RV to RRV in the Plan), equals the aggregate of reproductive values of individuals in the subset. Reproductive value of a subset measures its genetic contribution to future generations. (4) An offspring has a reproductive value, and each parent has a share of it, dependant on the fraction of the offspring’s genes it contributed. Reproductive value of a parent is the sum of its shares in the reproductive value of its offspring. (5) Natural selection tends to maximize the number of offspring.
Fisher’s (1930) concepts of reproductive value were genetic and evolutionary (Grafen 2006). The Plan’s definition of RV does not mention genetics or evolution. The relationship between Fisher’s (1930) reproductive value and the Plan’s RV should be elaborated in the Plan. Charlesworth (2000), Engen et al. (2009), and Galindo (2007) provide additional informative discussions of Fisher’s (1930) reproductive value.
The KRRT rescaled (i.e., converted) the model-estimated RVs into RRVs by dividing each life stage RV by 209 (the RV for adult females; Table A1-4 in the Plan). Therefore, RRV for adult females equaled one, and the RRVs of all other life stages a proportion less than 1. Each of the youngest life stages (egg, hatchling stage, and transitional) was assigned the same RRV of 0.005; thus, the adult female RRV was 200 times higher than that for each of the three youngest life stages. According to the Plan, RVs of each life stage were based on the updated model. Life stage RVs depended on estimated age structure. The Plan indicated that the updated model was used to estimate age structure, but it was not clear how this was done, or which year or years were used in the estimation. This is important in light of changes in age structure mentioned above. In any case, my comments concerning assumptions underlying the updated model, age at maturity, duration of the early pelagic stage, survivorship, and data time series apply likewise to the model’s use in estimating RVs. Therefore, they also apply to estimated RRVs of life stages other than adult females (for which RRV is constant) that affect the Threats Analysis.
The second component of the Threats Analysis also is especially problematical (Caillouet 2006). The KRRT constructed hypothetical, geometrically-scaled, annual mortality class intervals (Table A1-3 in the Plan), ostensibly to bracket available estimates of annual mortality for each threat category and combination of life-stage and ecosystem (Table A1-5 in the Plan). Threats were shown as column headings, and life stage-ecosystem combinations were shown as row headings, in Threat Analysis tables (e.g., Table A1-7 in the Plan). Apparently, no actual annual mortality estimates went into the Threats Analysis. The hypothetical annual mortality class intervals, and their geometric midpoints, and their rounded geometric midpoints (referred to as Value in the Plan’s threats tables), were as follows:
Value (Table A1-3 in the Plan) is an index of hypothetical annual mortality. For each life stage-ecosystem combination, cell entries of Value were summed over all threat categories (e.g., Table A1-7 in the Plan). Each row sum was then multiplied by the RRV of the life stage to derive its “Total Estimated Adjusted Annual Mortality (# of adult females).” Apparently, these products of row sums and RRVs were used to prioritize recovery actions. I elaborated general concern about this multiplication step in peer-review comments on an earlier version of the Plan and in Caillouet (2006). Since then, I have reviewed literature on reproductive value and scrutinized the Threats Analysis in the Plan, to improve my understanding. While it may have served the KRRT’s purpose of categorizing (quantitatively) the relative impacts of threats to Kemp’s ridley life stage-ecosystem combinations, it is not based on actual annual deaths of Kemp’s ridleys caused by threats. In addition, the RVs from which RRVs were derived already captured the effects of annual mortality, because they reflect age structure. Age structure determines life stage structure; it reflects hatchling releases (cohort sizes), number of age groups, turtle growth, and mortality. Therefore, this multiplication seems redundant, if not incorrect. As an example, Wallace et al. (2008) assessed the impacts of bycatch of loggerheads (Caretta caretta) in various fisheries from different geographic regions, using RVs and mortality rates, but they did not multiply them. If the Plan’s Threats Analysis did not represent the best available science (i.e., regarding the estimation of RVs, RRVs, as well as the multiplication step in question), its use of the Threats Analysis in prioritization of recovery actions should be revisited and revised as appropriate.
Recommendations for Revision of the Plan. (1) Reexamine parameters of the updated model and determine whether each represents the best available science. If not, update them accordingly in the Plan. (2) Update the time series of annual nests and hatchlings through 2009, and rerun the updated model for each of three assumed ages at maturity (8, 10, and 12 yr). Include in these reruns the updated parameters from item (1). Determine which if any rerun scenario produces a best-fitting model. Present all the results in the Plan. (3) If modeling outputs under item (2) differ significantly from those based on the Plan’s updated model, data series, and assumed 12 yr to maturity, then the KRRT should consider making appropriate revisions regarding annual rate of increase in the population, downlisting and delisting criteria, forecasts of when downlisting and delisting might occur, life-stage RRVs, Threats Analysis, and prioritization of recovery actions. (4) The KRRT should revisit its Threats Analysis, in the context of my comments and recommendations (1)-(3), as well as questions about the multiplication of sums of Value entries times RRVs. The discussion of RV should be expanded in the Plan to include an explanation of its relationship to Fisher’s (1930) reproductive value.(5) The Plan should include a priority action aimed at intermittent updating, improving, and running demographic models and Threats Analyses (using improved parameter estimates and updated time series of annual numbers of nests and hatchlings).
It is my understanding that a demographic model exists as a Microsoft Excel program (Heppell et al. 2005, as updated by the KRRT in the Plan), and the same is true for the Threats Analysis tables in the Plan. Both should be relatively easy to re-run after incorporating the best available science. If results of recommended re-runs warrant revisions in the Plan, the additional time required should be relatively short compared to time already invested in recovery planning. If the KRRT chooses to accommodate these recommendations, I believe the results should be included in the Plan along with appropriate revisions.
Conclusions. In my compilation (circa 1999) of Marine Turtle Newsletter articles (<https://seaturtle.org/mtn/special/kemps.shtml>), I wrote, “Now that the Kemp’s ridley population appears to be recovering, the more recent articles in the series focus on explaining why …” Obviously, the current status and exponential increase in the Kemp’s ridley population are due to past conservation efforts to date (Heppell et al. 2007). However, it is still important to determine the relative contributions of various conservation approaches (Caillouet 2006). An examination of the chronology of conservation efforts and other factors is useful in this regard. Early conservation efforts created a powerful feed-back loop between hatchling releases and time-lagged increases in nesters and nests which, when coupled with reductions in mortality of benthic life stages, led to reversal of the population’s decline, restoration of population momentum, and an exponential trajectory toward recovery. TEDs could not have enhanced the production of hatchlings that contributed to reversal of the population decline in 1986 (Caillouet 2006). This reversal occurred before any TED regulations were in place (Yaninek 1995; Epperly 2003), and 6 yr before the current recovery plan (USFWS & NMFS 1992) was approved. TEDs were not required in all shrimp trawls, in all areas, and at all times until 1992 (Yaninek 1995; Epperly 2003). On the other hand, phase out of shrimping by the U.S. fleet in Mexico’s Gulf of Mexico waters during 1976-1979, and the decline in the Mexican shrimping fleet that followed, probably increased survival of all benthic life stages vulnerable to incidental capture in shrimp trawls (Iversen et al. 1993; TEWG 1998, 2000; Heppell et al. 2005, 2007). In other words, the cumulative effects of restoration and enhancement of hatchling production, coupled with a declining threat from shrimp trawling in Mexico’s waters, overwhelmed all natural and anthropogenic threats by 1986 (Caillouet 2006). Thereafter, the combination of TED use and declines in shrimping effort in the northern Gulf of Mexico contributed to the post-1990 rate of population increase in the population. Obviously, incidental capture in shrimp trawls may remain a threat, because Kemp’s ridley strandings continue to occur during shrimping seasons. Despite decline in shrimping effort, reasons for continued linkage between sea turtle strandings and shrimping have not been adequately addressed. This offers an important opportunity for further research, which should be made a priority action in the Plan. One possibility is that multiple recapture of individual Kemp’s ridleys that escape properly-installed, tuned, and operated TEDs (i.e., in full compliance with regulations) may lead to exhaustion and death (Caillouet et al. 1996).
Once the Plan is approved it could remain in effect for decades. Therefore, the Plan’s modeling, threats analysis, and all aspects of the Plan affected by them, should be revised based on the best available science. This would be in keeping with the overarching recommendation of sea turtle status and trends report (Bjorndal et al. 2010): “The most serious demographic data gaps to be addressed include in-water abundance, hatchling-cohort production, survival of immature turtles and nesting females, age at sexual maturity, breeding rates, and clutch frequency. More precise estimates of anthropogenic mortality are needed to evaluate impacts. All sources of data should be evaluated for quality, consistency, spatial and temporal heterogeneity and trends, and data gaps.”
The good news is that recovery of the Kemp’s ridley population seems highly likely, and recovery actions identified in the Plan should increase the probability of recovery. It is not too soon to begin considering conservation and management actions that may be required to sustain a delisted Kemp’s ridley population. However, the bad news is that the BP-Transocean-Macondo well blowout and oil spill during spring and summer 2010 threatened Kemp’s ridley life stages, habitats, and prey species in the northeastern Gulf of Mexico. Some of the hatchlings that entered the surface circulation of the western Gulf of Mexico during the spill could have been transported to the northeastern Gulf of Mexico and negatively impacted by the oil (Collard & Ogren 1990; Putnam et al. 2010). Juveniles and adults could have migrated from the western Gulf to areas impacted by the oil. It will take time to determine the extent of oil spill’s impacts on the Kemp’s ridley population. In any case, revisions of the Plan’s coverage of oil spill response and effects of petroleum on Kemp’s ridley are in order. For anyone interested, more extensive public comments concerning the Plan can be downloaded at regulations.gov, by entering “Caillouet Kemp’s” in the “read comments” window, clicking “search”, then the title of my comments, and finally on the “view” icon. These comments may not be available at this web site for very long.
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