NOAA Technical Memorandum NMFS-AFSC-192
 


Harvesting Young-of-the-Year from 

Large Mammal Populations: An 

Application of Systemic Management 

by 

C. W. Fowler, T. E. Jewell, and M.V. Lee 

U.S. DEPARTMENT OF COMMERCE 

National Oceanic and Atmospheric Administration
 


National Marine Fisheries Service
 


Alaska Fisheries Science Center
 


January 2009 
NOAA Technical Memorandum NMFS 

The National Marine Fisheries Service's Alaska Fisheries Science Center 

uses the NOAA Technical Memorandum series to issue informal scientific and 

technical publications when complete formal review and editorial processing 

are not appropriate or feasible. Documents within this series reflect sound 

professional work and may be referenced in the formal scientific and technical 

literature. 

The NMFS-AFSC Technical Memorandum series of the Alaska Fisheries 

Science Center continues the NMFS-F/NWC series established in 1970 by the 

Northwest Fisheries Center. The NMFS-NWFSC series is currently used by 

the Northwest Fisheries Science Center. 

This document should be cited as follows: 

Fowler, C. W.,T. E. Jewell, and M. V. Lee. 2009. Harvesting 

young-of-the-year from large mammal populations: An application of 

systemic management. U.S. Dep. Commer., NOAA Tech. Memo. 

NMFS-AFSC-192, 65 p. 

Reference in this document to trade names does not imply endorsement by 

the National Marine Fisheries Service, NOAA. 
NOAA Technical Memorandum NMFS-AFSC-192


 Harvesting Young-of-the-Year from
 


Large Mammal Populations: An
 


Application of Systemic Management
 


by

 C. W. Fowler1, T. E. Jewell2 and M. V. Lee3 

1 National Marine Mammal Laboratory
 


Alaska Fisheries Science Center
 


7600 Sand Point Way N.E.
 


Seattle, WA 98115
 


phone: 206-526-4031
 


FAX: 206-526-6615
 


e-mail: Charles.Fowler@noaa.gov
 


2 School of Aquatic and Fishery Sciences
 


University of Washington
 


Seattle, WA 98195
 


3 Grinnell College
 


Box 3752, 1115 8th Ave
 


Grinnell, IA 50112
 


U.S. DEPARTMENT OF COMMERCE 

Carlos M. Gutierrez, Secretary 

National Oceanic and Atmospheric Administration

 William J. Brennan, Acting Under Secretary and Administrator 

National Marine Fisheries Service 

James W. Balsiger, Acting Assistant Administrator for Fisheries 

January 2009 
This document is available to the public through: 

National Technical Information Service 

U.S. Department of Commerce 

5285 Port Royal Road 

Springfield, VA 22161 

www.ntis.gov 
ABSTRACT
 


We evaluate the current commercial harvest of harp seal (Pagophilus groenlandicus) and 

proposed subsistence harvests of northern fur seal (Callorhinus ursinus) pups based on intraspecific comparisons. These comparisons utilize a pattern derived from 167 cases of estimated 

consumption rates by large mammals. In all cases, the predation rates involve large mammal 

prey less than 1 year of age. Recent harvests of harp seal pups are exceeded by 20 (about 12%) 

of the estimated consumption rates among the nonhuman species. Although this is not 

statistically significant, further analysis may find this harvest to be unsustainable when we 

account for other factors such as the number of other predators, the number of prey each predator 

consumes, trophic level, the biodiversity of the system, and differences involving terrestrial 

predators preying on marine prey. 

Initially, there is no scientific basis for rejecting a proposed subsistence harvest of 150 

northern fur seal pups on St. George Island, Alaska, or a comparable harvest of 1,125 pups on St. 

Paul Island. The proposed harvests of fur seal pups are exceeded by 162 (97%) of the 167 cases 

of predation among nonhuman predatory species. In both cases, therefore, the harvests represent 

consumption rates in the lower extremes of predation rates observed for nonhuman species. 

Further explicit consideration of relevant factors could lead to a slight reduction in the assurance 

that the harvest of 150 pups is sustainable, but there is a low likelihood that such a harvest would 

prove to be unsustainable. This determination accounts for the complexity of the ecosystems 

involved owing to the integrative nature of the patterns used in the evaluation. The northern fur 

seal population is declining, raising concerns about the addition of a subsistence harvest to the 

mortality this species experiences. In management, a declining population reflects all of the 

iii 
contributing factors to include all human influence. Management is necessary to relieve systems 

of the abnormal effects of our activities whenever human influence is found to be unusual, 

abnormal, or pathological. Such influence involves the full spectrum of human activities to 

include the effects of abnormal fisheries harvests, pollution, and CO2 production. As long as 

harvests of the declining species are not abnormally large, other abnormal human influences are 

the preferred focus of management. 

The comparisons used in our study make the conclusions regarding northern fur seals 

seem conservative, largely because most examples of predation among nonhuman predators 

exceed the harvest rates proposed for this species. Overtly accounting for other factors could 

lead to the conclusion that proposed harvests are less conservative than initially indicated. We 

show, for example, that directly accounting for the number of competing predators is likely to 

show the proposed harvest to be exceeded by a smaller portion of the sample among nonhuman 

predators than when this factor is not explicitly treated. Nevertheless, the mortality rates of the 

proposed harvest are small enough that it is likely that they fall in the lower end of the spectrum 

of most subsets of data for consumption rates among other large mammals – subsets that would 

emerge through explicit consideration of more specific management questions. 

iv 
INTRODUCTION
 

The harvest of young-of-the-year from large mammal populations (by humans) is 

exemplified by the commercial take of the phocid harp seals (Pagophilus groenlandicus) in the 

northwest Atlantic. From a single species perspective, one of the questions facing managers in 

cases like these is: At what rate can we sustainably harvest harp seals? More specifically, the 

question might be: What portion of the pup production by harp seals can be harvested 

sustainably? From the ecosystem perspective, the complimentary question is: What portion of 

the pup production by harp seals should be left unharvested to sustainably preserve the natural 

dynamics of the population of their species and the characteristics of their ecosystem? (Hobbs 

and Fowler 2008). Conventionally, pup harvests would be addressed using models of 'surplus 

production', 'maximum sustainable yield', or 'potential biological removal'. Such approaches are 

simplistic, misleading, often result in overharvesting, and, like all management, lead to 

unintended effects on ecosystems. All harvesting has genetic effects on the resource species – 

many of which are judged to be negative or undesirable. How can management be carried out to 

account for such factors? 

Pups of the northern fur seal (Callorhinus ursinus), have been harvested by the 

indigenous people of North America for centuries (Etnier 2002). In the spirit of cultural 

tradition, the community of St. George Island, Alaska, has proposed that their residents be 

allowed an annual take of 150 male northern fur seal pups. This harvest would be taken from 

about 17,000 pups of both sexes currently born on this island each year (Towell et al. 2006). It is 

now possible to evaluate the sustainability of various levels of take from any large mammal 

population by comparing harvests to patterns in consumption observed among other predatory 


 

species (Fowler and Hobbs 2002, Belgrano and Fowler 2008). This involves implementation of 

the principles of management (embodied in systemic management, Fowler 2003). 

Here we evaluate three harvests: 1) the harvest of harp seal pups in the northwest 

Atlantic, 2) the proposed harvest of northern fur seal pups on St. George Island, Alaska, and 3) a 

hypothetical harvest of northern fur seal pups on St. Paul Island comparable to that proposed for 

St. George (the latter two islands are the two largest in the Pribilof Archipelago in the Bering Sea 

where the largest portion of the global population of northern fur seals breed). These evaluations 

are based on comparisons with observed consumption rates by other large mammal predators in 

their take of juveniles (less than 1 year of age) from large mammal populations. The choice of 

these sets of comparisons overtly accounts for the a priori knowledge that the predator and prey 

(humans and fur/harp seals) are both large mammals and that the prey are young-of-the-year. 

Our analyses of these data exemplify part of the decision-making process in systemic 

management: the process of directly accounting for factors such as number of predatory species, 

body size, taxonomic status, and trophic level. More specific comparisons will have to await the 

results of research to provide information that is missing in current data: other knowledge of 

these or similar systems. The need for research is defined by the management question being 

addressed as explained in the discussion section below, with examples. Refining such questions 

(asking more specific management questions) leads to defining further research. 

METHODS 

The literature on predator/prey relationships was searched for information regarding the 

predation rate of large mammal predators on large mammal prey (from about 5.5 kg to about 

2
 

600 kg adult body size for predators, and from 50 kg to 525 kg as the adult body size for the prey 

species), specifically where the prey taken were less than 1 year of age. This choice was based 

on the objective of achieving a match or consonance1 between management question and the 

pattern used for evaluation or establishing management advice (Belgrano and Fowler 2008). The 

question (e.g., At what rate can we sustainably harvest harp seal [or fur seal] pups?) inherently 

specifies humans as the predator and seals as the prey; in each case, both are large mammals. We 

achieve a match between information and management question when the data used in 

management involves predation patterns that are specific to large mammals in both cases. In 

addition to body size, the question specifies pups or young-of-the-year; thus, the data we 

examined were restricted to young-of-the-year for the prey – continuing to maintain the match. 

Predation rates were recorded for each study as reported in the literature, each rate 

specific to the time period covered by the study. Some studies were designed and carried out 

over a full year; others were shorter studies that resulted in estimates of mortality pertinent to 

only several months. Percentages were converted to portions; thus, a mortality rate of 15% was 

recorded as a crude mortality rate of M = 0.15. 

1

Consonance involves the mapping of management question to pattern developed in 

scientific research. A pattern fully consonant with the management question occurs when the 

pattern and question involve completely identical units of measure, are of identical logical type, 

and are perfectly isomorphic. There is a one-to-one mapping from question to pattern (Belgrano 

and Fowler 2008). 

3
 
The number of predatory species reported to be involved in the overall mortality of 

juveniles in each case was also recorded (when available), in addition to the predation rates 

recorded for specific predators. 

Scientific names were recorded as they were used in the original source documents. This 

means that some of the names used in our results may be outdated by current taxonomic 

standards. 

Cannibalism was not considered to be predation because the management question being 

addressed involves the sustainable consumption of one prey species by a predatory species that is 

different from the prey (using data on cannibalism would result in a mismatch with the 

management question because cannibalism involve one species eating individuals of same 

species). The predatory species about which the management question is being posed is the 

human species, Homo sapiens. Asking the management question (in the case of northern fur 

seals: At what rate can we sustainably harvest northern fur seal pups for human consumption?) 

that specifies humans as the consumer follows an important tenet of management. This tenet 

requires that management be intransitive in regulating or controlling our (human) interactions 

with other natural systems, in this case another species (Fowler 2003). 

Predation rates by the domestic dog were included, as were predation rates estimated for 

unidentified species thought to be large mammals. 

Male and female prey were not distinguished; for this study the predation rates were 

assumed to apply to the 0-1 year-old age class without regard to sex. 

The harvests of harp seals and proposed harvests of fur seals were converted to mortality 

rates expressed in the units reported in the literature for nonhuman predators. The proposed (or 

4
 

comparable) harvests of northern fur seal pups was divided by the estimated population size of 

the newborn portion of the population for each island (17,000 for St. George, and 122,000 for St. 

Paul; Towell et al. 2006) to find the crude mortality rate (M). For example, M for the requested 

harvest on St. George was calculated as 150/17,000 = 0.00824 (= 0.8824%). All crude annual 

mortality rates were converted to log10 scale for comparison with mortality rates similarly 

calculated for the nonhuman predators from the literature used in this study. These conversions 

preserved matching units as required of systemic management so that, in application, no 

conversion is required of, or allowed by, stakeholders (Belgrano and Fowler 2008). 

The human population on St. George is about 100 and on St. Paul the human population 

was assumed to be about 750 (it is probably actually closer to 500 with a 'native' component of 

about 85%). A harvest on St. Paul comparable to the proposed harvest on St. George would, 

under the assumption of a human population of 750, be approximately 1,125 pups. This converts 

to an estimated crude mortality rate of 0.92% (M = 1,125/122,000 = 0.0092). Various harvest 

rates were used for each Pribilof island to evaluate alternatives that covered a span of values 

inclusive of these harvest levels and their corresponding mortality rates. A minimum of 500 fur 

seal pups was used in the harvest options evaluated for St. Paul; the minimum we used for St. 

George was 50 pups. The maximum evaluated in each case was the harvest corresponding to the 

mean consumption rate observed among the studies of the nonhuman species. 

RESULTS 

The first step in our analysis involved compiling the estimated predations rates found for 

167 cases involving populations of predator-prey pairs wherein both the predator and prey 

5
 
0.2 

Crude Mortality Rate (log scale) 

mean = -1.095 

(NW Atlantic Harp Seal Harvest) 0.2 

0.1 

0.1 

0.0 

Portion of species 

species were large mammals and for which the individual prey taken were less than a year old 

(Appendix Table 1 with references shown in Appendix Table 2). The histogram in Figure 1 

summarizes these data. 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

Figure 1.--The harvest of harp seal pups in the northwest Atlantic as it falls in the frequency 

distribution of predator-specific mortality rates (M) on young-of-the-year for large 

mammals (from Appendix Table 1). 

The harvest of harp seal pups in the northwest Atlantic takes about 37% of the pups 

(harvest of about 370,000 out of about 1,000,000 born each year, DFO 2000). This harvest (M = 

0.37) falls within the spectrum of variation in mortality caused by predation among other species 

as shown in Figure 1 [log10(0.37) = -0.43]. Twenty out of 167 cases of predation exceed this 

predation rate. The harvest rate (37% per year) is about 4.5-fold larger than the mean of 

predation rates among nonhuman predators. 

6
 
Portion of species 0.2 

0.2 

0.1 

0.1 

0.0 

Crude Mortality Rate (log scale) 

mean = -1.095 

(700) 

A 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

B
 

Number of Pups 100000 

10000 

1000 

100 

Number of Pups in Harvest 

(9802 at mean of above distribution) 

(3000) 

(1500) 

(500) 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

Figure 2.--Frequency distribution of predator-specific mortality rates on young-of-the-year for 

large mammals (A, from Appendix Table 1) and number of pups that would be taken 

in a harvest of northern fur seal pups on St. Paul Island, Alaska, as determined by the 

corresponding mortality rate (B). 

Figure 2 presents the data from Figure 1 (Appendix Table 1) along with the estimated 

mortality rates for a variety of harvests from 500 to 9,802 pups for the northern fur seals on St. 

Paul Island. Panel A compares a harvest of 700 pups (M = 700/122,000) to the variety of 

consumption rates observed among nonhuman predators. Panel B illustrates the relationship 

between harvest in numbers and M, both in log10 scale. Thus, the 700 pups from panel A, would 

7
 

occur on the line just above and to the right of the 500 in panel B. Figure 3(A) shows the same 

frequency distribution presented in Figures 1 and 2(A) along with the alternative harvest rates for 

northern fur seal pups on St. George (i.e., M = 150/17,000 for the proposed harvest on that 

island). The maximum harvest shown in this case is 1,390, a value corresponding to the mean 

consumption rate for nonhuman predators from a population of 17,000. 

0.2 

Crude Mortality Rate (log scale) 

mean = -1.095 

(150) 

A 

Portion of species 0.2 

0.1 

0.1 

0.0 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

B 

Number of Pups 10000 

1000 

100 

10 

Number of Pups in Harvest 

(1390 at mean of above distribution) 

(500) 

(150) 

(50) 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

Figure 3.--Frequency distribution of predator-specific mortality rates on young-of-the-year for 

large mammals (A, from Appendix Table 1) and numbers of pups that would be taken 

in a harvest of northern fur seal pups on St. George Island, Alaska, as determined by 

the corresponding mortality rate (B). 

8
 
Neither the harvest of northern fur seals nor that of harp seal pups lasts a full year. This 

means that the duration of the season must be accounted for in making comparisons like those 

shown in Figures 1-3. Short studies, especially those focused on the first few months of life, 

might easily result in estimated annual mortality rates that are larger than would be the case for 

studies with a duration of one full year. In other words, short studies conducted just after birth 

might give rise to biased (elevated) estimates of annual mortality compared to studies lasting all 

year or from studies conducted late in the first year of life. 

The data for the nonhuman species in Figures 1 - 3 are for crude mortality rates estimated 

for the duration of the study reported in each publication listed in Appendix Table 2 (i.e., some 

values reported for M are not annual mortality rates). The effect of the length of time over which 

mortality (often reported as survival which we converted to mortality) was measured and 

reported in the literature is shown in Figure 4 where our analysis produced inconsistent results. 

The correlation based on crude rates showed a very slight increase in mortality with the span of 

time covered by the study (Fig. 4A), as would be expected. In contrast (Fig. 4B), we found that 

longer studies tended to result in estimated mortality rates that are slightly lower when the 

analysis is based on a log10 transformation of the data. In view of the small regression 

coefficients in each case, and the inconsistency, we assumed that the measures we found in the 

literature could be pooled for comparison (independent of the length of the study). More indepth analysis of the effects of length of time over which consumption is estimated, and the 

timing of periods of consumption within the first year of life of the prey are needed. 

9
 

0.0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

0.8 

0.9 

1.0 

Crude Mortality Rate 

y = 0.148 + 0.00115x A 

0.00 0.25 0.50 0.75 1.00 

Span of Time Covered (Portion of Year) 

0.00 0.25 0.50 0.75 1.00 

Span of Time Covered (Portion of Year) 

Figure 4.--Estimates of mortality (M = crude mortality rate of Appendix Table 1) as related to 

span of time covered in the original studies (Appendix Table 2) shown as 

untransformed values (A) and log-transformed values (B). 

Whether or not a harvest is too large is one primary concern (especially from the 

perspective of concerns about effects on the environment) in regard to the sustainability of our 

use of natural resources. Such concerns are juxtaposed with the question of whether the harvest 

is too small, where the importance of sustainability for the consumer is at stake. In the case of 

northern fur seals (Figs. 2 and 3), the proposed harvest for St. George, and comparable harvests 

for St. Paul, do not result in mortality rates that are significantly larger than the mortality rates 

-3.0 

-2.5 

-2.0 

-1.5 

-1.0 

-0.5 

0.0 

log(Crude Mortality Rate) 

y = -1.045 - 0.098x B 

10
 

caused through consumption rates exhibited by nonhuman species. For St. George, 162 of the 

167 cases (97%) found in the literature were for predation rates larger than the 0.88% mortality 

that would be caused by the proposed harvest of 150 pups. Although the comparable harvest 

(same per capita harvest) rate for St. Paul is slightly different (pup harvest rate of 0.92% per year; 

M = 0.0092) the same number of nonhuman predation rates were larger in the data set in the 

Appendix (162 out of 167 or about 97%). 

Through further analysis of the data in Figure 1 (Appendix Table 1), we explicitly 

accounted for the number of predators involved. Within the full sample, there was information 

enabling a count of predators that consumed young-of-the-year in 165 cases. These counts are 

preliminary, but they contain more information than a hypothetical example; importantly, they 

help specify the kind of product needed from research to address the management question 

before us. Figure 5 shows the relationship between predation rates for a particular predator and 

the total number of predatory species involved in consuming the same prey (i.e., in competition 

with each other, including the species for which the predation rate is plotted). 

As can be seen in the pattern represented in Figure 5, it is likely that there is a decline in 

predation rates as the number of predators increases – a pattern expected in that the increasing 

number of predators are sharing finite resources. For example, if there are a total of three 

competing predatory species, only 4 of the 85 cases (4.7%) represent mortality rates larger than 

those for the commercial harvest of harp seals (Fig. 6 ). Thus, the commercial harvest of harp 

seals is less likely to be sustainable if this species experiences predation by two or more 

nonhuman mammalian predators, than would be the case if based on the data behind Figure 1, 

11
 

without direct consideration of predator numbers. For the case of northern fur seals, 5 (5.9%) of 

the 85 cases where there are three predators are less than the proposed harvest for St. George. log10 (Crude Mortality Rate) -0.5
 

-1.0
 

-1.5
 

-2.0
 

-2.5
 

-3.0
 

1 2 3 4 5 

Number of Predators 

Figure 5.--The pattern of subsets of data from Figure 1 corresponding to the estimated mortality 

rates as they are observed in correlation with the number of mammalian predators 

consuming young-of-the-year from each of the respective prey species. 

12
 

Portion of species 

0.3 

0.3 

0.3 

0.2 

0.2 

0.1 

0.1 

0.0 

Crude Mortality Rate (log scale) 

(700 Fur Seal Pups, 

St. Paul Island) 

(Mean from (NW Atlantic 

Figure 1) Harp Seal Harvest) 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

Figure 6. --The subset of data from Figure 1 (see Fig. 5) corresponding to cases where there were 

three predators involved in the mortality of young-of-the-year (Appendix Table 1), 

showing the mortality rate from the commercial harvest of harp seals and hypothetical 

subsistence harvests of northen fur seals (for St. Paul Island) from the Pribilof Islands, 

Alaska. 

The prey of both harp and northern fur seals are species that consume their own prey, 

each species within its own tropic level. Many of the prey species consumed by both species of 

seal are not strict herbivores whereas many of the prey in Appendix Table 1 are. Trophic level is 

another factor behind the question of sustainable harvests and involves one of the ecosystembased aspects of management. Analyses to treat this factor directly are shown in Figure 7. For 

these data, there is only one case (one of nine, or 11.1%) where the consumption rates of 

nonhuman predators exceed the commercial harvest of harp seals. For northern fur seals, there 

13
 

are no recorded cases where consumption rates by nonhuman predators are less than the proposed 

harvests on the Pribilof Islands. 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

Figure 7.--A comparison of the data from Figure 1 (A) with the subset corresponding to those 

cases from Appendix Table 1, wherein the predators do not consume herbivores (B, 

n = 9). 

DISCUSSION 

At the roots of this work is the extremely generic management question: At what rate can 

we sustainably harvest? Harvest is taken from the biosphere, from ecosystems, and from other 

species (Fowler 2003) and we need to identify the source regarding its hierarchical level (logical 

0.2 

Crude Mortality Rate (log scale) A mean = -1.095 

0.2 

0.1 

0.1 

0.0 

Portion of species Portion of species 0.4 

B 

0.3 

0.2 

0.1 

0.0 

14
 

type). Harvest of either harp or northern fur seals is harvest from a specific species (by humans). 

It is the same as predation on one prey species among nonhuman predatory species – not as 

measured but as defined (they both fall in the category of consumption of one prey species and 

both can be measured and compared). Thus, we have the slightly less general management 

question: At what rate can we sustainably harvest another species? The matching (consonant, 

Belgrano and Fowler 2008) research question is: At what rates do consumer species consume 

their prey species? The empirical pattern consonant with such a general question would have 

been a plot of predation rates observed for predator-prey pairs as diverse as amoebas consuming 

bacteria to lions consuming wildebeests or baleen whales consuming krill. Anything beyond the 

limits of variation observed in such a pattern would be considered an outlier – abnormal and 

unsustainable regardless of other circumstances or relevant factors (Fowler and Hobbs 2002). 

However, the management question behind the specifics of work we are presenting here 

was much more specific. It involved the human (large mammal) take of young-of-the-year from 

other large mammal populations. It is known that many elements of ecological systems show 

patterns related to body size (e.g., Peters 1983, Calder 1984, West et al. 1997, White et al. 2007) 

and here we are dealing with a situation in which both predator and prey are large mammals. 

Progressing to further specificity, size is not the only element implied by 'large mammal' – in 

both cases we are considering mammals. Different taxonomic groups show different behaviors, 

physiological properties, physiological dynamics, evolutionary histories, population dynamics, 

and life-history strategies. Much of what large mammals are and do is determined genetically. 

These factors are to be taken into account in choosing the scientific information used to evaluate 

proposed action and provide management advice. In this study, we specifically chose 

15
 
information from the literature regarding large mammal predators taking large mammal prey to 

match the predator and prey involved in our harvest of seals. 

For both harp and northern fur seals, we are dealing with an even more specific 

management question when harvesting pups: At what rate can we sustainably harvest young-ofthe-year from a large mammal population? In both cases, we are involved in the take of large 

mammal prey. In both cases the individuals harvested are younger than 1 year of age. In both 

cases we want to know if the harvests (or proposed harvests) are sustainable. Thus, the subset of 

literature that we used in our search was that which contained information from studies of 

mortality caused by large mammals taking young-of-the-year from their large mammal prey 

populations, usually reported as the result of studies of prey rather than predators. By doing this, 

we took into account both size and taxonomy explicitly. 

Scientifically, it would be of interest to know how the patterns shown in Figures 1-3, 5 

and 7 fit within the overall pattern of predation, from amoebas to whales as predators, and from 

bacteria to elephants as prey. Factors such as the evolutionary history of the species would be 

taken into account as inherent to the variation seen in the pattern (Belgrano and Fowler 2008). 

Correlative patterns (such as that associated with number of predators, Fig. 5 above) within the 

more general pattern are of great interest. From a practical point of view, they help answer 

specific questions or concerns exemplified by those raised and addressed above, but addressed 

here without the benefit of the more general picture/pattern; estimates of consumption rates exist 

for only a small fraction of the Earth's species. 

Revealing the normal in contrast to the abnormal is a crucial role for science in research 

involving patterns consonant with management questions. It allows for management to avoid the 

16
 

abnormal – systemic management (Fowler 2003). The matter of observing what is normal 

compared to what is abnormal can involve either subsets of data specific to the management 

question (as done in this work) or correlative estimation (that would draw upon more 

comprehensive sets of data). The latter would involve extrapolation or interpolation from the 

general pattern whereas the former makes use of a subset of data specific to the management 

question. Combinations of such approaches would be useful but involves much more research 

than was possible in the confines of this study. 

In this study, we started with a subset of all possible data that matched the generic 

question to which it applies (At what rate can we sustainably harvest young-of-the-year from a 

large mammal population?). As mentioned earlier, an even more specific sub-set of information 

would involve predation on young-of-the-year of the precise age at which northern fur or harp 

seals are taken. Although taken within the first year of life in both cases, the exact ages differ in 

the case of these two species and different sets of information would be used in each case. The 

refined management question for northern fur seals would be: At what rate can we sustainably 

harvest northern fur seals at 3 to 4 months of age?, assuming that the harvest would be taken in 

September and October of each year. 

Our choice of data exemplifies the process of ensuring a match (consonance) between 

management question and guiding information so that the data do not have to be converted in the 

error prone process of conventional management (Belgrano and Fowler 2008). The management 

question specifies the units, conditions, and type of information required of the pattern to be 

found, characterized and displayed through research. The goal is to ensure that the pattern (in 

reality, data representing the pattern) and question match each other (are consonant or isomorphic 

17
 

with each other; Fowler and Smith 2004, Belgrano and Fowler 2008). In our case, the first step 

in achieving a match involved making sure that the units were identical between the pattern and 

the management question; in each case the units were the portion of the population consumed 

each year (M). This match was then maintained throughout the process of finding greater 

specificity in the management question which, early in the process, clearly specified the body 

size, taxonomic category and age of prey that were involved. In taking this approach, there is no 

debate or discussion among stakeholders regarding the translation of partially relevant 

information to the management decision (e.g., body size is partially relevant but not of the units 

required to answer the management question). The guidance for what to do is inherent to the 

data chosen; the pattern exposed by research defined by the question provides the answer to the 

question (i.e., the pattern is in units of M and management avoids abnormal values of M; Fowler 

and Hobbs 2002). 

From our treatment of Figures 1-3, it was clear that we merely initiated the process of 

refining the management question. Further research would help define the relationship between 

estimates of M and the length of time covered by a study. However, further or improved research 

is distinct from the process of refining the management question to direct such research to 

account for more of the complexity of reality. This process is exemplified above in our 

consideration of predator numbers and trophic level; the data in hand were analyzed to produce 

an overt consideration of these factors. Factors such as body size, taxonomic category, age of 

individuals taken, and the fact we that we were considering predation (as the influence of one 

species on another) where inherent to the data chosen. As we added further direct consideration 

of number of predator species and trophic level, we were involved in refinement of the initial 

18
 

management question, followed, in step, by ensuring a match between the data we used and the 

refined question. This process continues as further concerns are raised. Stakeholders and 

scientists are free to contribute to the refinement of the question with their concerns and 

information. Such concerns are to be translated to refinement of the management question rather 

than debate about the objective to achieve in management. Following the systemic course, 

decisions regarding what should be done are based on empirical information rather than debate, 

political bias, economic factors, or other human values (Belgrano and Fowler 2008). Refinement 

of the management question further defines the pattern needed for advice (or evaluation). 

Scientists are led to investigations that have increased focus on more specific patterns and 

correlative relationships within more general patterns (Fowler 2003). 

Most scientists will have little, if any, difficulty understanding that part of the variance 

observed in the data shown in Figure 1 is explained by research techniques (as scientists we 

always strive to conduct research according to established standards but cannot be perfect). 

Other factors contributing to observed variation include the variety of details involved in each 

specific case (e.g., size of the study area, location, behavioral factors, season, and weather). Few, 

if any, of the data represent predation rates that apply to the full population of any prey species or 

the full population of any predatory species. Thus, there is real potential for not only reducing 

the variance involved in the data representing the real world pattern we most need, but also for 

finding bias. If it becomes possible to conduct the needed field work, it would be very helpful to 

explore these factors, both in assuring the quality of science needed to avoid bias and errors of 

estimation and in assuring consonance with our management questions. With more fully 

representative data in hand, it would then be possible to deal with the biodiversity of these 

19
 

systems directly (Fowler 2008). A more comprehensive treatment of the harp seal harvest would 

almost surely find it to be unsustainable – especially in regard to measures bringing biodiversity 

into the analysis directly. 

We note here that what we have presented above leads to the conclusion that when our 

interactions with another biological system (e.g., a species) fall within the normal range of 

natural variation of a generic pattern, it does not guarantee sustainability. Conversely, if they fall 

outside the normal range of natural variation of such patterns, harvest rates are not sustainable; as 

outliers, they result in abnormal or unsustainable influence on the nonhuman. For example, the 

harvest of harp seals at the upper end of the normal range of natural variation seen in Figure 1 

may or may not be sustainable in regard to the effects of the harvest on the harp seal species and 

its ecosystem. The same holds true at the lower end of the spectrum of natural variation. 

Sustainability is not guaranteed at the lower end of the normal range of natural variation in that 

the consumption may not be sufficient to sustain the predator population. A harvest of 150 pups 

would not sustain a population of 100 residents on St. George Island without other sources of 

food – these kinds of connections and consequences lead to many other management questions. 

It is thus obvious that there are many concerns which can be brought to bear in systemic 

management. Many involve the refinement of management questions. One, for example, 

involves the number of other prey used by predatory species – a matter of ecological interest. 

How does this lead to further refinement of our management question? We start with a different 

scientific question: How many other sources of food do we humans utilize? The matching 

(comparable/consonant) management question is then: How many species can we sustainably 

harvest? We must avoid abnormality in both the harvest of each species and the number of 

20
 

 

resource species harvested. Coming back to the matter of harvesting seal pups, this issue leads to 

a further and quite interesting scientific question: Are predation rates a function of the number of 

prey species taken? This prompts another management question relating to pup harvests: At 

what rate can we harvest harp seal pups (or northern fur seal pups) knowing that they are 

species that consume X species of prey (where X is the count of species in their diet)? 

A very similar concern is that of the number of predators for with the prey serve as a 

resource (Fig. 5). We are adding ourselves to the list of predators taking northern fur seals and 

harp seals when we harvest them. This gives rise to the scientific question: What are the effects 

of our harvests when we (humans) are one of two, compared to one of five, predators consuming 

a particular prey species? We can use the latter issue to illustrate further refinement of the 

management question central to our consideration of northern fur seals. The management 

question we began with was: At what rate can we sustainably harvest young-of-the-year from a 

large mammal prey base, with Homo sapiens as a large mammal predator? This specified the 

science necessary for observing the pattern used for a preliminary evaluation of the proposed 

harvest of northern fur seal pups on St. George Island (Fig. 3), comparable harvests on St. Paul 

Island (Fig. 2) and the harvest of harp seals in the northwest Atlantic (Fig. 1). 

Moving beyond the initial question, we can now explicitly account for the number of 

predators involved in the consumption of young-of-the-year (retaining the focus on both the 

predator and prey as large mammals). This requires refinement of the management question so 

that it accounts for predator numbers (the numbers of predators feeding on a particular species of 

prey). Human harvesting contributes to the number of predators involved in the competition for 

the prey resource by increasing the predator count by one. In the case of both northern fur seals 

21
 

and harp seals, we are injecting ourselves into a system where the prey are already taken by other 

predators (regardless of type; e.g., sharks). The new management question becomes: At what 

rate can we sustainably harvest young-of-the-year from a large mammal prey base, when, by 

taking a harvest, the total number of predators (including humans) is N? The corresponding 

research question is: At what rate are young-of-the-year consumed from a large mammal prey 

base when the total number of predators is N? This was the research question and science 

behind the production of Figures 5 and 6, confining the predators, in this case, to mammalian 

predators. A piece of missing information, at this point, is an exact count of the number of 

mammalian predator species that include northern fur seals (or harp seals) in their diets. Our 

hypothetical case of three species would include two nonhuman species (e.g., killer whales and 

Steller sea lions). Adding our predation by harvesting pups on the Pribilof Islands would bring 

the total to three. The refined management question then becomes: At what rate can we 

sustainably harvest young-of-the-year from large mammal populations subject to predation by 

three mammalian predators? As exemplified above, research to produce the necessary matching 

(consonant) pattern, as information for use in management, could focus on the correlative 

relationship (Fig. 5) between predation rates and numbers of predators that are mammals 

(without dropping the issues of body size and age of prey).

 Continuing to assume that humans bring the total count of mammalian predators to 

three, another approach involves examining only cases in the literature (or conducting field 

studies) confined to studies of prey with three species of mammalian predators using them as 

prey (as shown in Fig. 6). Both approaches continue to support the conclusion that the proposed 

harvest is of little concern for northern fur seals or their ecosystem (meaning that the proposed 

22
 

harvest is an acceptably sustainable harvest). In view of the preliminary nature of the data, 

however, we need more information to better characterize the relationship between numbers of 

predators and the predation rates on their prey. We are faced with defining research to produce 

the information needed to guide management or evaluate proposed management action in the 

case that there is such a relationship. Preliminary information indicates that there is. log 10 (Density, nos. per k2 ) 

5 

4 

3 

2 

1 

0 

-1 

-2 

-3 -2 -1 0 1 2 3 4 5 

log10(Weight,kg) 

Figure 8.--The empirical pattern in the relationship between population density and body size 

(From Damuth 1987). 

Another obvious concern involves the status of the prey population. In the case of 

northern fur seals, the eastern Pacific populations are listed as depleted under terms of the U.S. 

Marine Mammal Protection Act. We know that, in ecological systems, predator/prey interactions 

involve what are called functional and numerical responses to population density of prey (an 

23
 

example of an ecological principle). Predation rates typically drop as the density of prey 

declines. With this knowledge, we can proceed with further refinement of our management 

question and further specify the research needed to guide decision-making. The treatment of 

predator numbers, and trophic level, above involves examples of overt or explicit treatment of 

general principles inherent to (accounted for by) patterns (Belgrano and Fowler 2008). 

Consideration of functional response curves offers the promise of another. 

A starting place in this process involves noting a different pattern – that involving a 

relationship between population density and body size (Fig. 8). Research is needed to determine 

if this kind of relationship exists for marine species. If such a relationship exists, the relative 

density of species the size of northern fur seals could be determined from their position relative 

to the regression line (i.e., a regression line for marine species such as the line for terrestrial 

species shown in Fig. 8). The predation rates observed for all large mammal prey, including 

those for terrestrial systems from Appendix Table 1, could then be examined as they relate to the 

relative density of prey in each case evaluated in relation to the respective regression line. It is 

conceivable (although only a hypothesis at this point) that a pattern with a mode shifted even 

farther to the left than that of Figure 5 compared to Figure 1 would emerge for species that are as 

depleted as northern fur seals are relative to the average population size or density expected for 

species of their body size. Because the population of northern fur seals remains one of the larger 

among the various species of marine mammal in the north Pacific (and that of harp seals in the 

Atlantic), it is also possible that their density is close to the mean expected for species of their 

body size and the matching pattern would fall more in the central part of the range covered by 

Figures 1-3. 

24
 
Questions different from those raised above are also relevant to management – such 

questions involve different aspects of the management process. The matter of trophic level was 

treated in Figure 7. There is little evidence that direct consideration of trophic level with a larger 

sample size would provide grounds for changing our conclusions with regard to either the harvest 

of harp seals or northern fur seals; in other words, panel B of Figure 7 appears to show little if 

any difference from a random sample of cases from panel A. Further research to test this 

hypothesis and to provide a larger sample size would clearly be useful. 

Another issue of concern involves population trends. For example, the population of 

northern fur seals has been declining over the past 20 years (Towell et al. 2006). If it continues, 

the question arises: When would a harvest of 150 pups on St. George become unsustainable? 

The pattern in consumption rates among nonhuman predators as they relate to population status 

of their prey would be used to determine such sustainability – following the approach outlined 

above for population status in general. For example, the population of northern fur seals on St. 

George would have to drop to a level where only 1,867 pups were born in the population each 

year in order for a harvest of 150 to correspond to the mean mortality rate observed in the data 

from Appendix Table 1. This is approximately 10% of the current population. This example, 

however, fails to account explicitly for functional responses (discussed above), numbers of 

predators (e.g., Fig. 5), and other elements of complexity, more of which are outlined below in 

showing how such factors can be accounted for in refined management questions. 

Also of concern in managing our harvest of resources is the issue of the location or 

distribution of harvests in geographic space. On the Pribilof Islands, this is a matter of asking a 

number of different management questions. Assuming that we are still specifically treating 

25
 

harvests of young-of-the-year of northern fur seals, one such question would be: What portion of 

the island-wide harvest should be taken from each rookery area? To make this question specific 

to St. George (the same can be done for St. Paul), it would be: What portion of the island-wide 

harvest on St. George should be taken from each rookery area? A simple answer to this 

question might be found by assuming that nonhuman predators consume pups from the rookeries 

in proportion to the number of pups born on each rookery. This being the case, we can assume 

that pup numbers are distributed in proportion to the number of adult male northern fur seals that 

hold territories with females in their territories for each rookery (these are counted each year). 

Under these assumptions, 14 of the 150 pups proposed to be harvested on St. George would be 

taken from Zapadni rookery, 32 from South, 54 from North, 12 from East Reef, 30 from East 

Cliffs, and 8 from Staraya. If studies were to show a different distribution of harvest rates among 

nonhuman predators, the pattern observed could be used to allocate the harvest in a similar 

distribution. If there is variation among predators in their allocation of predation among the 

various rookeries, this would be used to conclude that similar variation is an option for the 

subsistence harvest. 

A different approach would be to assess the question: Is the proposed harvest of 150 pups 

on St. George Island sustainable if taken from any one rookery area? Figure 9 shows the 

resulting rookery-specific mortality rates in comparison to observed mortality among nonhuman 

predators, again assuming that pup numbers are distributed among rookeries in proportion to the 

distribution of adult territorial male with females in their territories. In other words, Figure 9 

shows the mortality rates that would result from taking all 150 pups from each one (but only one) 

of the six rookery areas, with one mortality rate for each rookery area (each rookery area is 

26
 
Portion of species 

identified by its corresponding letter above the arrow depicting the mortality rate for that rookery 

area). Thus, in Figure 9, these mortality rates are again compared to the mortality rates listed in 

Appendix Table 1 and shown in earlier evaluations of the island-wide mortality rates. 

0.4 

Crude Mortality Rate (log scale) 

0.3 mean = -1.095 

0.3 

a b c d e f

0.3 

0.2 

0.2 

0.1 

0.1 

0.0 

-2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 

log(M) 

Figure 9.--The rookery-specific mortality rates for St. George Island, assuming that the harvest 

would be 150 northern fur seal pups in each case, in comparison to predator-specific 

mortality rates on young-of-the-year for large mammals shown in a frequency 

distribution of the data from Appendix Table 1. The individual rookeries are (letters 

corresponding to arrows depicting the associated mortality rates): a: North, b: South, 

c: East Cliffs, d: Zapadni, e: East Reef, f: Staraya. 

The results of this comparison show that each rookery-specific case of mortality caused 

by a harvest of 150 pups falls within the normal range of natural variation observed among 

nonhuman large-mammal predators in their take of young-of-the-year from other large mammal 

populations. In all cases, of course, the mortality rate is larger than would be the case if the 

27
 

harvest were spread evenly among all rookeries (Fig. 3). However, if taken from only one 

rookery, it is also clear that the harvest should be taken from North rookery, the largest rookery 

on the island (arrow a, the smallest mortality rate in Fig. 9). This would amount to choosing a 

rookery where the impact would be most sustainable (in terms of minimizing effects on the 

population and ecosystem). The distribution of harvests within a rookery are of similar concern 

and should also be dealt with to avoid abnormality. 

The examples we have presented and discussed above serve to illustrate the process of 

asking questions, refining questions, and conducting research to obtain the match needed among 

the questions and patterns that serve as guiding information. As indicated above, this match 

involves identical units of measure, identical logical type, and isomorphism, or what is known as 

consonance (Fowler and Smith 2004, Belgrano and Fowler 2008). Further progress would be 

seen in research looking for patterns in predation rates related to latitude and the extent of 

overlap in the geographic ranges of predator and prey. In the cases of humans harvesting marine 

mammals, we would want to know if there are correlative patterns within the information from 

Appendix Table 1 related to cases where terrestrial species are predators on marine mammals 

species. 

Many such questions can be asked regarding issues related to birth rates, environmental 

conditions, life history and reproductive strategy. As research questions, these include: Are there 

patterns in which the predation rates on prey species that give birth primarily to twins different 

from those that give birth to single offspring? Are there patterns in which predation rates differ 

between years of El Niño events and non-El Niño events? Are there patterns in the predation 

rates of prey when they are highly migratory species (such as the northern fur seal)? The timing 

28
 

of the short studies within the first year of life also undoubtedly contributes to the variance 

observed in the overall pattern, in spite of the lack of evidence for such a pattern in this study. In 

view of the survivorship/age relationship seen in most species (and specifically northern fur 

seals, Barlow and Boveng 1991), we would expect a relationship (pattern) observed in a 

correlation between mortality rate and age, specific to the weeks and months within the first year 

of life. What is that relationship? These are scientific questions important in refining the 

management question; the management question specifies the combination of such factors which, 

in turn, determines the pattern to be produced by research that matches the management question. 

Thus, a few of the factors listed in the preceding paragraphs can be used to generate a 

management question reflecting a bit more of the complexity of the situation faced in the harvest 

of young-of-the-year from harp and northern fur seals. The complexity behind such factors is 

endless as would be a complete list of such factors. However, we can think of a few such factors 

and our best efforts would be brought to bear in making the list as extensive as possible. An 

example for northern fur seals (assuming a harvest in October) would be initiated with: At what 

rate can we sustainably harvest 

- young-of-the-year 

- taken in the fourth month of life 

- for a highly migratory 

- pinniped (inferred to be a large mammal) 

- in the Bering Sea (thus including marine compared to terrestrial) 

- with a population less than 50% of its historically observed peak 

- during years of non-El Niño events, 

29
 
- and already subject to predation by 6 species of predators 

- for a predator that is a terrestrial large mammal? 

If the related analyses of variance of data such as those shown in Figure 1 show sub-patterns or 

correlations with the identified factors (as was demonstrated in Figs. 5 and 6), these patterns can 

be used to demonstrate the normal (sustainable) and abnormal (unsustainable), with much more 

clarity regarding what is unsustainable to account for the circumstances involved in each of the 

three cases we are treating. 

Things are too complex to be able to assume that the job of management is finished by 

addressing and implementing management regarding any one of the individual management 

issues listed above. Even the questions above fail to explicitly address all the aspects of 

management (complexity) involved. To account for complexity as best we can, we need to 

formulate as many questions as possible – bringing into the question-asking phase of 

management the concerns of all stakeholders. As such concerns are raised, the related issues 

must be addressed through either refined management questions, or distinctly different 

management questions. Refined management questions were exemplified in cases such that 

behind Figs. 5 - 7 above. A distinctly new management question was exemplified above, when 

we raised the issue of distribution of harvests (keeping in mind that management questions are, in 

reality, all interrelated). It was a question distinct from the questions related to harvest rates. 

Another distinct question stems from knowledge that ecological systems vary. Is it 

realistic to implement management based on a specific fixed number for harvests? The proposed 

harvest of 150 pups on St. George could over-simplistically result in policy requiring that exactly 

150 pups (no more an no less) be taken each year. Or, a take of no more than 150 pups might be 

30
 

written into regulations. Is this realistic? We saw that continued reduction in the northern fur 

seal population could result in reduced harvests – one form of change, or temporal variation. 

What about the situation where little else is known to be changing? We are brought to the 

management question: How much year-to-year variation should there be in the harvest of 

northern fur seal pups from St. George Island? 

This question can be addressed in parallel with other questions as raised above, but would 

require its own set of question-specific data. Science would again focus on description and 

analysis of a pattern that matches the management question. In this specific case, research to 

provide the guidance would involve studies to determine the variance in year-to-year predation 

rates among nonhuman predators in their consumption of young-of-the-year. Most useful here 

would be data on the coefficient of variation so that the issue of the magnitude of the rates 

themselves can be left to be treated with data such as those presented above. To then be 

realistically applied, management would require that there be year-to-year variation in the harvest 

to mimic variation seen in empirical data from real-world cases observed for nonhuman predatorprey systems. As with the other examples above, the matters of body size, extenuating 

circumstances, trophic level, and other factors would be used to refine the question and provide 

more quantitative substance to the intraspecific patterns that match the question. A priori, it is 

clear that it would be unrealistic to implement management that would confine the harvest to a 

fixed level – no other predator species consumes it prey at a fixed rate. 

As noted repeatedly, and specifically in the last paragraph, extenuating circumstances 

cannot be ignored in management. A major factor to acknowledge in today’s world is that of 

human influence on our environment. The systems from which data are collected and the 

31
 
systems about which we are asking the management question are all influenced by factors such as 

pollution, global warming, harvests of other species . . . . the list is essentially endless, especially 

in view of the many indirect effects of such factors. The extent and nature of the effects of many 

such influential factors are nearly impossible, if not impossible, to clearly establish in a 

convincing scientific manner. One of the major advantages of using natural patterns as a basis 

for decision-making is that they integrate (include being a product of, so as to reflect) the effects 

of human influence (Belgrano and Fowler 2008), and specifically the effects listed above. Thus, 

the position and nature of patterns such as those shown in Figure 1 (including any trends or 

changes involved), automatically account for the collective effects of such human ‘disturbance’ 

whether it be of global warming, pollution, past harvests of cetacean species, or oceanic 

acidification. 

Knowing that such factors contribute to variance and its limitations, however, fails to 

provide specificity with respect to management questions and informative patterns. An 

overt/explicit accounting for such factors is possible in two ways. First, they can be addressed 

with different or distinct management questions (At what rate can we sustainably produce CO2? 

At what rate can we sustainably produce pesticides? At what rate can we sustainably consume 

other resource species? – see Fowler and Hobbs 2002, and Fowler 2008 for examples of patterns 

to be used in addressing such questions). Second, they can be addressed in correlative/subpattern analysis to refine the management question. In this case, a set of elements would be 

added to the list above; for example, 

- under conditions of current global temperature regimes, 

- with pollution levels currently observed, and 

32
 
- when other species are subjected to existing harvests by humans. 

Such a list can be extended indefinitely. If none of the observed predation rates (spatial 

allocations or variance in predation rates) among nonhuman species can be found to show a 

correlation with any of these factors, we are left with the confidence that they are already 

accounted for in the data, implicitly – data that can be used to account for other known 

correlative patterns, explicitly (keeping mind, always, the inherent quality of the data and the 

quality of the research that produces them). The precautionary reversal of the burden of proof 

(Peterman 1990, Gerrodette et al. 2002) is inherent to this process. 

Another factor of concern involves the genetic effects of harvesting. The proposed 

harvest of northern fur seal pups from the St. George community is for 150 males; males would 

be selected in preference to females and the harvest would be of only (or primarily) one sex. The 

proposed selectivity can easily be understood, based on the fact(s) that there was a commercial 

harvest of subadult males that lasted decades without discernable negative effects on the 

population. Population models show that a harvest of males has a much smaller effect on 

production than does either a harvest of both sexes selected randomly, or a harvest of only 

females (Fowler et al. 1980). Northern fur seals are a species with an extreme polygynous 

breeding system (Gentry and Kooyman 1986); higher natural mortality is observed among males 

than females (and, therefore, there is a highly skewed sex ratio), and nearly all species depend on 

females for reproduction more than they depend on males. In view of these isolated facts, a male 

harvest seems to make sense. The situation is much more complicated than this, however, and 

management needs to be consistent in its various applications and particularly needs to be 

evolutionarily enlightened (Thompson 2005) by accounting for selectivity (Etnier and Fowler 

33
 

2005). If we are to meet these demands, especially to account for the effects of selectivity, the 

sex-composition of the harvest would match the sex-composition of the seals taken in the 

consumption by predators. This is probably quite close to the sex composition of the 0-1 yearold age class in the population. If the focus on males is approved as a management decision, it 

must be recognized as an example of conventional management rather than systemic 

management. As conventional management, it would be application of what Belgrano and 

Fowler (2008) call misdirected reductionism, subject to the consequences of abnormal 

selectivity, and would only partially account for the complexity of factors that need to be brought 

to bear in decision-making. The same concerns apply to size: selective harvesting of large 

healthy pups could easily have a genetic effect that is quite abnormal compared to that of the 

nonhuman predators. 

Conventional approaches to evaluating the harvest of pups would entail a variety of 

options one of which might be an analysis in which a simulation model of the population would 

be used to make predictions of population decline that can be attributed to the harvest. In 

conventional thinking, this option is emphasized in the case of northern fur seals because of the 

observed decline and depleted status of the population of this species. Such an approach invites 

the judgment of experts or other stakeholders. This introduces bias and error. A team of 

managers and scientists, for example, would translate the information regarding projected decline 

to a management decision – a harvest restriction. This conversion is an example of how current 

management inherently involves human error, bias, limitations, and values. The conversion is 

essentially guesswork. This happens, for example, if it were to be shown that a harvest of 150 

pups on St. George Island leads to a population 3% less than otherwise expected after 25 years. 

34
 

The decline, a measure of temporal change in expected population level, would be converted to 

predation rates – they are two different things and cannot be converted in the debate of a 

decision-making process. In other words, temporal population change would be converted to 

predation rates in an artificial process; the resulting subsistence harvest would be a result of the 

management decision based on consideration of the population decline out of context – an 

illogical connection. The units or dimensions of the management (those specified by the 

management question – predation rates) would not match the information being used (difference 

in projected population level). Concern about that effect (the difference in projected population 

level) would result in restrictions on the harvest that would replace action taken to correct other 

anthropogenic abnormalities in the northern fur seal’s ecosystem which would go uncorrected. 

In systemic management the other abnormalities would be dealt with systematically on a case by 

case basis. Mitigating action to deal with those factors places the burden on other elements of 

the overall system. In this case, denying the people of the Pribilof Islands their request to harvest 

northern fur seals is a form of mitigation that avoids dealing directly with other problems clearly 

measurable as human abnormality. 

SUMMARY 

Data for 167 cases of predation by nonhuman predators on large mammal prey less than 1 

year old were used to evaluate the harp seal harvest in the northwest Atlantic and a proposed 

harvest of 150 northern fur seal pups on St. George Island, Alaska. A similar potential harvest of 

1,125 pups on St. Paul Island (same number of pups per island resident with an assumed human 

population of 750) was also evaluated. The harp seal harvest is exceeded by only 20 (about 12%) 

35
 

of the 167 cases with no further analysis of the overall pattern. This rate may be unsustainable if 

other factors are taken into account – specifically factors such as numbers of predators involved 

and the trophic levels of these species. Only 4.7% of the cases where there are three predators (4 

of the 85 of the original 167) have estimated predation rates larger than that of the commercial 

harvest of harp seal pups in the northwest Atlantic. Other factors to consider overtly include the 

number of alternative prey predators consume, and the fact that humans are a terrestrial predator 

preying on marine prey (which would lead to comparisons involving nonhuman terrestrial 

predators feeding on marine mammal young-of-the-year). Further research is needed, but the 

harp seal harvest is probably not sustainable (i.e., is probably abnormal compared to other 

species when the complexity of the system is accounted for directly). 

For northern fur seals, the overall pattern among nonhuman large mammal species (for 

both predator and prey) provides no scientific basis for rejecting the proposed harvest of 150 

pups on St. George Island, Alaska (or a comparable harvest of 1,125 on St. Paul, Island). This 

conclusion is based on evaluations using the pattern among nonhuman species as an integrative 

pattern to account for the complexity of the full suite of factors involved in natural systems 

(including ecosystems and the biosphere; Fowler 2003, Belgrano and Fowler 2008). Concerns 

about a declining northern fur seal population emphasize the need to focus overtly, or explicitly, 

on a variety of these factors (in addition to body size, taxonomic category, and age already 

accounted for explicitly). As mentioned above, there is need to deal overtly with patterns in 

functional response dynamics to ensure that we avoid abnormal harvest rates in accounting for 

the decline in northern fur seals. But there is also a very important need to examine patterns 

regarding the sustainability of the numerous other human activities and influences that directly or 

36
 

indirectly are related to both the pattern we used and the decline of northern fur seals through the 

interconnected nature of ecosystems and the biosphere. These factors include fisheries harvests, 

pollution, and CO2 production (related to oceanic acidification and global warming). 

Management to relieve systems of abnormal human influence based on patterns related to such 

issues would replace complete prohibition of the harvest of pups. Harvesting pups obviously 

will contribute to declining trends but management action to prohibit such harvests would be 

carried out only if the harvest rates themselves are found to be abnormal for existing 

circumstances. Because nonhuman predators would terminate their consumption of their prey 

species when the prey population reaches certain low threshold levels (with a minimum of zero), 

the harvest would be prohibited under similar circumstances. 

In the case of proposed northern fur seal harvests (for both Pribilof islands), the resulting 

predation rates under existing circumstances would be well below the bulk of predation rates 

observed for nonhuman species, regardless of circumstances that we have examined. Further 

refinement of the management question, could lead to the conclusion that a larger portion of 

nonhuman predation rates are larger than such harvests would represent, but the harvest rates are 

small enough to fall in the lower end of the frequency distribution of most subsets of data for 

other large mammals. This means that the proposed annual harvest of 150 pups on St. George 

Island (and comparable harvests on St. Paul Island) can be considered sustainable for the 

foreseeable future. Continued monitoring and research, especially of the kind exemplified in this 

paper, is needed. 

37
 

ACKNOWLEDGMENTS
 


Foremost in our gratitude are all of the field biologists who’s time, labor, and dedication 

are behind the production of the data that we are synthesizing and interpreting here. Included 

are those whose names count among the authors listed in Appendix Table 2. We thank Jason 

Baker, John Bengtson, Tom Gelatt, Bruce Robson, Rod Towell, Mike Williams, and Phil Zavadil 

for their thoughtful comments, suggestions, and further questions that contributed and 

exemplified either the question-refinement processes or the raising of new questions in the 

collaborative nature of systemic management. We thank Gary Duker and James Lee for the 

editorial suggestions and experience they brought to the improvement of this paper. 

38
 

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52
 

- - -

APPENDICES 

Appendix Table 1 lists prey species and their predatory species for which the references 

in Appendix Table 2 served as sources of estimated mortality rates on young-of-the-year for the 

prey population as caused by the population of each specific predator. Also included in 

Appendix Table 1 are counts of the large mammal predators known to be predators on the prey 

populations as reported in the studies listed in Appendix Table 2. 

Appendix Table 1.--List of prey for which young-of-year mortality rates caused by specific 

predators were found in the literature as identified by the reference number 

(found in the literature cited section as identified in Table 2). 

Prey Predator 

Citation 

Number 

Mortality 

Rate 

(M) 

Number 

of 

Predators 

Acinonyx jubatus Crocutta crocutta 50 0.025 5 

Acinonyx jubatus Panthera leo 50 0.393 5 

Alces alces Canis lupus 7 0.060 3 

Alces alces Canis lupus 16 0.175 3 

Alces alces Canis lupus 45 0.147 1 

53
 
Appendix Table 1.--Cont. 

Alces alces Canis lupus 

Alces alces Canis lupus 

Alces alces Canis lupus 

Alces alces Canis lupus 

Alces alces unidentified predator 

Alces alces unidentified predator 

Alces alces Ursus americanus 

Alces alces Ursus americanus 

Alces alces Ursus americanus 

Alces alces Ursus americanus 

Alces alces Ursus americanus 

Alces alces Ursus americanus 

Alces alces Ursus arctos 

Alces alces Ursus arctos 

Alces alces Ursus arctos 

Alces alces Ursus arctos 

Alces alces andersoni Ursus americanus 

Alces alces gigas Canis lupus 

Alces alces gigas Canis lupus 

Alces alces gigas Canis lupus 

Alces alces gigas unidentified bear 

Alces alces gigas unidentified predator 

54
 

45 0.194 1 

48 0.120 3 

49 0.041 

55 0.070 3 

7 0.020 3 

16 0.025 3 

7 0.340 3 

16 0.035 3 

48 0.030 3 

55 0.090 3 

57 0.091 1 

62 0.034 1 

7 0.060 3 

16 0.410 3 

48 0.520 3 

55 0.520 3 

66 0.440 1 

6 0.020 2 

18 0.014 3 

22 0.020 3 

18 0.027 3 

6 0.020 2 
Appendix Table 1.--Cont. 

Alces alces gigas unidentified predator 

Alces alces gigas unidentified predator 

Alces alces gigas Ursus americanus 

Alces alces gigas Ursus americanus 

Alces alces gigas Ursus arctos 

Alces alces gigas Ursus arctos 

Alces alces gigas Ursus arctos 

Alces gigas Canis lupus 

Alces gigas Canis lupus 

Alces gigas unidentified predator 

Alces gigas Ursus americanus 

Alces gigas Ursus arctos 

Antilocapra americana Aquila chrysaetos 

Antilocapra americana Aquila chrysaetos 

Antilocapra americana Canis latrans 

Antilocapra americana Canis latrans 

Antilocapra americana Canis latrans 

Antilocapra americana Canis latrans 

Antilocapra americana Lynx rufus 

Antilocapra americana Lynx rufus 

Antilocapra americana Lynx rufus 

Antilocapra americana unidentified predator 

55
 

18 0.027 3 

22 0.039 3 

18 0.350 3 

22 0.333 3 

6 0.430 2 

18 0.027 3 

22 0.294 3 

25 0.092 3 

26 0.630 1 

25 0.078 3 

25 0.393 3 

25 0.031 3 

3 0.010 2 

35 0.029 2 

3 0.010 1 

32 0.339 3 

35 0.500 2 

61 0.333 2 

3 0.250 2 

32 0.032 2 

61 0.167 2 

32 0.065 2 
Appendix Table 1.--Cont. 

Antilocapra americana unidentified predator 

Arctocephalus australis Otaria byronia 

Arctocephalus gazella Hydrurga leptonyx 

Arctocephalus pusillus pusillus Canis mesomelas 

Callorhinus ursinus Eumetopias jubatus 

Capreolus capreolus Canis familiaris 

Capreolus capreolus Canis lupus 

Capreolus capreolus Lynx lynx 

Capreolus capreolus Vulpes vulpes 

Capreolus capreolus Vulpes vulpes 

Cervus canadensis Puma concolor 

Cervus canadensis Puma concolor 

Cervus canadensis unidentified predator 

Cervus canadensis Ursus americanus 

Cervus elaphus Aquila chrysaetos 

Cervus elaphus Canis familiaris 

Cervus elaphus Canis latrans 

Cervus elaphus Canis latrans 

Cervus elaphus Canis lupus 

Cervus elaphus Lynx lynx 

Cervus elaphus unidentified bear 

Cervus elaphus unidentified predator 

56
 

35 0.202 2 

19 0.067 1 

10 0.344 1 

9 0.375 1 

28 0.051 1 

49 0.011 3 

49 0.021 3 

49 0.031 3 

36 0.467 1 

40 0.450 1 

8 0.140 1 

59 0.094 2 

59 0.075 2 

59 0.472 2 

15 0.008 3 

49 0.003 3 

13 0.028 2 

15 0.087 3 

49 0.070 3 

49 0.017 3 

15 0.024 3 

15 0.008 3 
Appendix Table 1.--Cont. 

Cervus elaphus Ursus americanus 13 0.076 2 

Cervus elaphus Ursus americanus 15 0.008 3 

Cervus elaphus Ursus arctos 15 0.087 3 

Equus caballus Puma concolor 47 0.173 1 

Equus caballus Puma concolor 52 0.451 1 

Lama guanicoe Puma concolor 46 0.473 1 

Odocoileus hemionus Aquila chrysaetos 67 0.083 

Odocoileus hemionus Canis latrans 1 0.276 2 

Odocoileus hemionus Canis latrans 21 0.120 2 

Odocoileus hemionus Canis latrans 29 0.270 1 

Odocoileus hemionus Canis latrans 33 0.385 1 

Odocoileus hemionus Canis latrans 34 0.130 3 

Odocoileus hemionus Canis latrans 38 0.723 1 

Odocoileus hemionus Canis latrans 44 0.325 1 

Odocoileus hemionus Canis latrans 67 0.250 1 

Odocoileus hemionus feline (Lynx rufus or Puma 34 0.039 3

 concolor) 

Odocoileus hemionus Lynx rufus 1 0.035 2 

Odocoileus hemionus mostly Canis latrans 14 0.570 1 

Odocoileus hemionus mostly Canis latrans 14 0.120 1 

Odocoileus hemionus Puma concolor 8 0.040 1 

Odocoileus hemionus Puma concolor 21 0.130 2 

57
 
Appendix Table 1.--Cont. 

Odocoileus hemionus unidentified predator 21 0.190 2 

Odocoileus hemionus Ursus americanus 34 0.039 3 

Odocoileus hemionus Canis latrans or Ursus 64 0.063 2

 columbianus americanus 

Odocoileus hemionus Puma concolor 64 0.188 2

 columbianus 

Odocoileus hemionus crookii Canis latrans 60 0.231 1 

Odocoileus hemionus crookii unidentified predator 60 0.154 1 

Odocoileus virginianus Canis familiaris 24 0.055 2 

Odocoileus virginianus Canis familiaris 30 0.084 4 

Odocoileus virginianus Canis familiaris 31 0.016 3 

Odocoileus virginianus Canis familiaris 42 0.020 2 

Odocoileus virginianus Canis familiaris 51 0.027 3 

Odocoileus virginianus Canis familiaris 53 0.034 2 

Odocoileus virginianus Canis familiaris 63 0.020 2 

Odocoileus virginianus Canis latrans 4 0.250 2 

Odocoileus virginianus Canis latrans 4 0.167 2 

Odocoileus virginianus Canis latrans 5 0.360 2 

Odocoileus virginianus Canis latrans 24 0.040 2 

Odocoileus virginianus Canis latrans 30 0.370 4 

Odocoileus virginianus Canis latrans 38 0.321 1 

Odocoileus virginianus Canis latrans 39 0.217 2 

58
 
Appendix Table 1.--Cont. 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Odocoileus virginianus 

Canis latrans 

Canis latrans 

Canis latrans 

Canis latrans 

Canis latrans 

Canis lupus 

Canis lupus 

Lynx rufus 

Lynx rufus 

Lynx rufus 

Lynx rufus 

Lynx rufus 

Lynx rufus 

Lynx rufus 

unidentified predator 

unidentified predator 

unidentified predator 

unidentified predator 

unidentified predator 

Ursus americanus 

Ursus americanus 

Ursus americanus 

59
 

43 0.083 3 

44 0.514 1 

51 0.054 3 

53 0.276 2 

58 0.059 3 

42 0.039 2 

63 0.210 2 

4 0.075 1 

5 0.020 2 

30 0.056 4 

31 0.095 3 

43 0.014 3 

51 0.027 3 

56 0.255 3 

31 0.175 2 

43 0.056 3 

51 0.027 3 

53 0.034 2 

58 0.059 3 

30 0.141 4 

39 0.174 2 

43 0.073 3 
Appendix Table 1.--Cont. 

Odocoileus virginianus Ursus americanus 

Odocoileus virginianus Vulpes or Urocyon spp. 

Odocoileus virginianus Vulpes vulpes or Urocyon 

 cinereoargenteus
 

Oreamnos americanus Canis latrans 

Oreamnos americanus Puma concolor 

Oreamnos americanus unidentified predator 

Oreamnos americanus Ursus americanus 

Ovis canadensis Puma concolor or Canis 

 latrans 

Phoca hispida Alopex lagopus 

Phoca hispida Ursus maritimus 

Rangifer tarandus Aquila chrysaetos 

Rangifer tarandus Aquila chrysaetos 

Rangifer tarandus Aquila chrysaetos 

Rangifer tarandus Aquila chrysaetos 

Rangifer tarandus Canis latrans 

Rangifer tarandus Canis lupus 

Rangifer tarandus Canis lupus 

Rangifer tarandus Canis lupus 

Rangifer tarandus Canis lupus 

Rangifer tarandus Gulo gulo 

60
 

58 0.176 3
 

31 0.016 3
 

56 0.085 3

41 0.103 3
 

41 0.051 3
 

41 0.026 3
 

41 0.128 3
 

37 0.452 1

20 0.261 1 

12 0.287 1 

2 0.038 3 

17 0.070 3 

23 0.080 3 

23 0.010 3 

17 0.040 3 

2 0.011 3 

17 0.274 3 

23 0.160 3 

23 0.170 3 

23 0.010 3 
Appendix Table 1.--Cont. 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

Rangifer tarandus 

 groenlandicus 

Ursus americanus 

Ursus americanus 

Lynx canadensis 

unidentified predator 

unidentified predator 

unidentified predator 

Ursus americanus 

Ursus arctos 

Ursus arctos 

Ursus arctos 

Ursus spp. 

Vulpes vulpes 

Canis lupus 

Lynx rufus 

Puma concolor 

54 0.080 3 

17 0.090 3 

23 0.070 3 

23 0.060 3 

54 0.080 3 

2 0.011 3 

23 0.130 3 

23 0.190 3 

17 0.156 3 

54 0.004 3 

65 0.060 2 

68 0.043 3 

68 0.043 3 

61
 

Appendix Table 2.--Citations as listed in Table 1. 

Citation Citation 

Number 

1.	 Trainer, C.E. (1975). 

2.	 Whitten, K.R., G.W. Garner, F.J. Mauer, and R.B. Harris (1992). 

3.	 Beale, D.M., and A.D. Smith (1973). 

4.	 Carroll, B.K., and D.L. Brown (1977). 

5.	 Cook, R.S., M. White, D.O. Trainer, and W.C. Glazener (1971). 

6.	 Ballard, W. B., T.H. Spraker, and K.P. Taylor (1981). 

7.	 Franzmann, A.W., C.C. Schwartz, and R.O Peterson (1980). 

8.	 Hornocker, M.G. (1970). 

9.	 Oosthuizen, W.H., M.A. Meyer, J.H.M. David, N.M. Summers, P.G.H. Kotze, and 

S.W. Swanson (1997). 

10.	 Boveng, P.L., L.M. Hiruki, M.K. Schwartz, and J.L. Bengtson. 1988. 

11.	 Lucas, Z., and W.T. Stobo (2000). 

12.	 Hammill, M.O., and T.G. Smith (1991). 

13.	 Smith, B.L., and S.H. Anderson (1996). 

14.	 White, G.C., R.A. Garrott, R.M Bartmann, L.H. Carpenter, and A.W. Alldredge 

(1987). 

15.	 Singer, F.J., A.T. Harting, K.K. Symonds, and M.B. Coughenour (1997). 

62
 
Appendix Table 2.--Cont. 

16. Larsen, D.G., D.A. Gauthier, and R.L. Markel (1989). 

17. Adams, L.G., B.W. Dale, and L.D. Mech (1995). 

18. Franzmann, A.W., and C.C. Schwartz (1986). 

19. Harcourt, R. (1992). 

20. Smith, T.G. (1976). 

21. Bishop, C.J., J.W. Unsworth, and E.O. Garton (2005). 

22. Bertram, M.R., and M.T. Vivion (2002). 

23. Adams, L.G., F.J. Singer, and B.W. Dale (1995). 

24. Huegel, C.N. R. B. Dahlgren, and H.L. Gladfelter (1985). 

25. Osborne, T.O., T.F. Paragi, J.L. Bodkin, A.J. Loranger, and W.N. Johnson (1991). 

26. Mech, L.D. (1966). 

27. Unsworth, J.W., D.F. Pac, G.C. White, and R.M. Bartmann (1999). 

28. Gentry, R.L., and J.H. Johnson (1981). 

29. Hamlin, K.L., S.J. Riley, D. Pyrah, A.R. Dood, and R.J. Mackie (1984). 

30. Ballard, W.B., H.A. Whitlaw, S.J. Young, R.A. Jenkins, and G.J. Forbes (1999). 

31. Ricca, M.A., K.M. Kilbride, and M.R. Dunbar (2002). 

32. Barrett, M.W. (1984). 

33. Steigers, W.D., and J.T. Flinders (1980). 

34. Pojar, T.M., and D.C. Bowden (2004). 

63
 
Appendix Table 2.--Cont. 

35.	 Gregg, M.A., M. Bray, K.M. Kilbride, and M.R. Dunbar (2001). 

36.	 Aanes, R., and R. Andersen (1996). 

37.	 Ross, P.I., M.G. Jalkotzy, and M. Festa-Bianchet (1997). 

38.	 Lingle, S. (2000). 

39.	 Kunkel, K.E., and M.D. Mech (1994). 

40.	 Jarnemo, A., S. Lockowandt, A. Olsson, and K. Wahlstrom (2004). 

41.	 Festa-Bianchet, M., M., Urquhart, and K.G. Smith (1994). 

42.	 Fuller, T.K. (1990). 

43.	 Vreeland, J.K., D.R. Diefenbach, and B.D. Wallingford (2004). 

44.	 Whittaker, D.G., and F.G. Lindzey (1999). 

45.	 Hayes, R.D., A.M. Baer, U. Wotschikowsky, and A.S. Harestad (2000). 

46.	 Sarno, R.J., W.R. Clark, M.S. Bank, W.S. Prexl, M.J. Behl, W.E. Johnson, and 

W.L. Franklin (1999). 

47.	 Turner, J.W., M.L. Wolfe, and J.F. Kirkpatrick (1992). 

48.	 Gasaway, W.C., R.D. Boertje, D.V. Grangaard, D.G. Kelleyhouse, R.O. 

Stephenson, and D.G. Larsen (1992). 

49.	 Okarma, H., B. Jedrzejewska, W. Jedrzejewski, Z.A. Krasinski, and L. Milkowski 

(1995). 

50.	 Laurenson, M.K. (1995). 

51.	 Decker, T.A., W.M. Healy, and S.A. Williams (1992). 

52.	 Turner, J.W. Jr., and M.L. Morrison (2001). 

64
 
Appendix Table 2.--Cont. 

53. Long, R.A., A.F. O'Connell Jr., and D.J. Harrison (1998). 

54. Mahoney, S.P., H. Abbott, L.H. Russell, and B.R. Porter (1990). 

55. Ballard, W.B., S.D. Miller, and J.S. Whitman (1990). 

56. Epstein, M.B., G.A. Feldhammer, and R.L. Joyner (1983). 

57. Boer, A.H. (1998). 

58. Mathews, N.E., and W.F. Porter (1988). 

59. Schlegel, M. (1976). 

60. Dickinson, T.G., G.E. Wampler, G.W. Garner, and C.D. Simpson (1980). 

61. Tucker, R.D., and G.W. Garner (1980). 

62. LeResche, R.E. (1968). 

63. Nelson, M.E., and L.D. Mech (1986). 

64. Welker, H.J. (1986). 

65. Miller, F. L., E. Broughton, and A. Gunn (1988). 

66. Steward, R.R., E.H. Kowal, R. Beaulieu, and T.W. Rock (1985). 

67. Wenger, C.R., and J.T. Springer (1981). 

68. LeCount, A.L. (1987). 

65
 


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