envb 40320-assignment 3-tkelly

Population Viability Analysis of the Azores Bullfinch (Pyrrhula murina) of São Miguel, Portugal

Therese KellyWildlife Management and Conservation module towards a M.Sc. in Environmental Sustainability, UCD

ENVB 40320 Assignment 3 Therese Kelly 15203297

Table of Contents1 Species and population description 2

2 Simulation data 4

3 Results 9

3.1 Summary of simulation results 9

3.2 Demographic results 11

3.3 Year by year simulation summary 11

3.4 Suggestions for improved simulation 39

4 Discussion 41

3 Recommendations for future management 42

3 References 43

List of Figures and TablesFigure 1 Map showing location of Azores 2

Figure 2 Map of São Miguel 3

Table 1 Total population estimates of Azores Bullfinch 3

Table 2 Mortality rate calculations 8

Figure 3 First simulation graph 10

Figure 4 Graph showing exponential growth curve 11

Figure 5 Alternate simulation graph 40

Figure 6 Graph of alternate exponential growth curve 41

Figure 5 Alternate simulation graph 40

1


1 Species and population description

The Azores Bullfinch (Pyrrhula murina), also locally known as The Priolo, is an endemic bird species of the island of São Miguel that forms part of the Azores archipelago of Portugal (see Figure 1). It was first described by in 1866 by British ornithologist Frederick Godman. It was formerly regarded as a subspecies of the Eurasian Bullfinch (Pyrrhula pyrrhula), but was split off in 1993 following Ramos (1993), (Birdlife International, 2013). They look distinctly different from the Eurasian Bullfinch and are notoriously difficult to sex (Ramos, 1993). Their general colouration is dark greyish-brown above and buffish below and the rump is buffish, (Bibby et al., 1992). The Azores Bullfinch requires a mosaic of vegetation to complete its annual life cycle (Teodosio, 2009). It relies predominantly on native laurel cloud forest and the associated native vegetation for its niche requirements (Ceia et al., 2009), although it has been observed eating seeds and buds of introduced exotic species during certain times of the year (Ramos, 1994 and 1996 and Ceia et al., 2011).

Figure 1: Map showing the location of the Azores (map borrowed from azoresbirdwatching.blogspot.ie).

2

https://en.wikipedia.org/wiki/Split_(phylogenetics)

https://en.wikipedia.org/wiki/Eurasian_bullfinch

https://en.wikipedia.org/wiki/Subspecies

https://en.wikipedia.org/wiki/Frederick_DuCane_Godman


Figure 2: Map of São Miguel highlighting the protected areas on the East of the island where the Azores Bullfinch occurs (map borrowed from Gil et al., 2015).

A single isolated population is confined to a protected area on the east side of São Miguel, (see Figure 2). The first comprehensive study of this species was carried out by Ramos (1993), who described the species as locally abundant in the 19th century. According to Ramos (1993), its locally abundant status can be traced back at least as far as the early 1920’s when museum specimens were still easy to collect. From then there were no official records until the late 1970’s when a small population (about 30 to 40 pairs) was reported by Le Grand, occurring in native vegetation (Ramos, 1993). See Table 1 for a list of official population size estimates.

Year Population size estimate Source1991 to 1993 120 to 400 individuals Ramos, 19962005 to 2007 1282 to 1934 individuals Monticelli et al., 20102008 760 to 1368 individuals Ceia et al., 20112012 1824 to 7904 individuals Gil et al. 2015Table 1: Table showing the official population estimate counts of the Azores Bullfinch since 1993.

The catastrophic shrinking of the Azores Bullfinch population size and range is attributed to habitat degradation (Ramos, 1993; Teodosio, 2009; Ceia et al., 2011). Since the 1960’s the area

3


of native forest has declined sharply. Firstly, vast tracts of native vegetation were cleared for pasture with some areas reforested with exotic pines (Ramos, 1993; Teodosio, 2009; Ceia et al., 2011). In more recent decades the spread of alien invasive species has negatively affected the native forest by altering community composition (Ceia, 2011). Ceia et al. (2009) showed that the Azores Bullfinch prefers native to exotic vegetation and while it will feed on some exotic species the native vegetation provides a year round supply of vital resources that the exotic species do not.

Under the IUCN’s Red List categories the Azores Bullfinch extinction level is currently classified as Endangered (Birdlife International, 2013). This however, is an improvement in its extinction threat status as it was previously classified as Critically Endangered from 2005 to 2009. Up until 2008, systematic quantitative methods for estimating population size, range and trends were lacking. Ceia et al., 2011 used a quantitative systematic approach to population monitoring that led to the upgrading of Endangered under the IUCN Red List categories.

2 Simulation data

This was a very challenging species to obtain information and data on. There are many knowledge gaps in the basic life history of this species. Therefore some simulation data is inferred from a closely related species, the Eurasian Bullfinch (Pyrrhula purrhula). This species was chosen as P. murina was taxonomically categorised as a sub-species of P. pyrrhula up until relatively recently (IUCN Red List). Some other input simulation data is based on estimations from scientific research data, plausible speculation, intuition and the author’s own crude estimates calculated from data in published peer reviewed research.

Scenario Settings: Rationale for selectionScenario name: 100 year extinction forecast for Pyrrhula murinaNumber of iterations: 500- to run a thorough simulation process. Number of years: Default - this was appropriate for the species, i.e. its life

span can relate to the true calendar. Run as individual based model: To obtain a more thorough simulation. Only one

population is being modelled. Enable genetic modelling and demographic stochasticity.

Extinction definition: Default- could not source critical threshold levels.Number of populations: 1- only one global population described.

Sequence of events in each time cycle: EV Breed Mortality Age Disperse

4


Harvest Supplement rCalc Ktruncation UpdateVars Census

Species Description: Rationale for selection

Inbreeding Depression: Default settings were selected due to lack of this data on the species. As only one population remains it is most likely that inbreeding occurs in the population. Default settings taken from O’ Grady et al. (2006)

Reproductive System: Rationale for selection

Monogamy: Short term monogamy was selected as a plausible speculation based on observations of pairs nest building and rearing young (Ramos, 1996; ADW website). As there is no definitive evidence to distinguish whether they may be short or long term monogamous short term monogamy was selected on a point of prudence.

Age of first offspring females: This information is currently unknown. 5 years was selected. This figure is taken from IUCN species assessment. It is the IUCN generation length or average age of parents. Reproduction is occurring at this time but it is most likely a crude over-estimation.

Age of first offspring males: 5 years. Same as previous.Maximum lifespan: This information is currently unknown. 18 years was

selected a plausible speculation based on a close genetic relative, Pyrrhula pyrrhula, having a maximum longevity of 17.5 years (HAGR website).

Max. no. of broods per year: 2. This is a crude estimate (Ramos 1993, Bibby et al., 1992).

Max. no. progeny per brood: 3. This is a crude estimate (Teodosio, 2009). Sex ratio at birth: This information is unknown so the default ratio of 50:50

was selected.Max. age of female reproduction: This information is not currently known so max. age of

speculated longevity was used. This is most likely to be an over-estimation.

Max. age of male reproduction: Same as previous.Density dependent reproduction: No data available so not selected.

5


Reproductive rates: Rationale for selection

% of females breeding: 62%. An estimation based on females with brood patch data from Ramos (1993).

SD due to EV: This information could not be calculated from available data therefore the default value was selected.

Distribution of broods per year: Brood 1 (90%) and Brood 2 (10%). This is a crude intuitive speculation based on research indicating there is more than likely a second brood (Ramos, 1993). Due to the uncertainty the author thought it prudent to place the majority percentage of brood distribution on brood 1.

Any other reproductive rate parameters were set to default as alternative valid data was not available.

Mortality rates:Female annual mortality rates (as percentage): Age 0 to 1: 14 with EV (SD): 10 Age 1 to 2: 41 with EV (SD): 3 Age 2 to 3: 26 with EV (SD): 3 Age 3 to 4: 16 with EV (SD): 3 Age 4 to 5: 10 with EV (SD): 3 After age 5: 6 with EV (SD): 3

Male annual mortality rates (as percentage): Age 0 to 1: 14 with EV (SD): 10 Age 1 to 2: 41 with EV (SD): 3 Age 2 to 3: 26 with EV (SD): 3 Age 3 to 4: 16 with EV (SD): 3 Age 4 to 5: 10 with EV (SD): 3 After age 5: 6 with EV (SD): 3

Rationale for selection: The age specific mortality rates are currently unknown for this species. Therefore, the mortality rates selected are a crude estimation. There were calculated using the following data:

Ceia et al., 2011 had data on the juvenile and adult numbers from a total population estimate of 1064; 870 being adults and 194 being juvenile. The author assumes juveniles to be 0 to 1 years old and a 50:50 sex ratio. Based on these assumptions the population figures can be broken down as thus; 435 adult individuals to each sex and 97 juvenile individuals to each sex.

Ramos, 1993 estimated that the number of juveniles surviving to enter the breeding population is similar to the adult mortality.

Monticelli et al., 2010 calculated an adult survival rate is 0.38, therefore the mortality rate is 0.62.

6


The adult mortality rate of 0.62 was applied to 97 male and female juveniles and then expressed separately as a percentage of the total estimated population of 1064 individuals.

The remaining juvenile survivors were added to the age class 1 to 2 years and the Monticelli et al., 2010 adult mortality rate of 0.38 was applied.

Expired numbers from each age class were subtracted sequentially prior to applying the mortality rate for subsequent age classes. See Table 2 for mortality rate calculations.

The EV (SD) values were set at default as there was no available data on which to calculate them.

Catastrophes: Rationale for selection

Habitat degradation: Research concludes that habitat degradation encompasses a decline in the range of native forest, severe fragmentation and alien invasive species (Ramos, 1993; Teodosio, 2009; Ceia et al., 2011; Birdlife International, 2013 and Gil et al., 2015). These factors were grouped together and the % frequency value of 14% is based on Reed et al. (2003). The severity level of 0.5 was selected with an assumption of there being no or not as much conservation efforts to remove invasive species and replant with native species. That conservation work is currently subject to short-term funding.

Severe storm event: This was selected based on Ramos (1993), where two historical severe storms occurred with a time span of c. 120 years between them. The author allowed for the possibility of one catastrophic storm event to occur within the 100-year simulation, i.e. a frequency value of 1%. Severity of 0.5 is intuitively based on the following; while severe storms have been shown to increase diversity of native forests (Ramos, 1993) such a catastrophe could be fatal on a single remaining isolated population.

Mate monopolisation: Rationale for selection

% males in breeding pool: 81% is a crude estimation that may be overestimated. Data of 870 mature individuals from a total population estimate of 1064 individuals (Ceia et al., 2011) a figure of 435 adult males was deduced (assuming a 50:50 sex ratio). Assuming that all adult males are capable of breeding then 81% represents their proportion of the total population.

7


Initial population size: Rationale for selection

Initial population size: A total mean population estimate of 1064 individuals (Ceia et al., 2011). There is more current research on a total population estimate from Gil et al., 2015. However, I chose to use Ceia et al.’s, 2011 data as they had more population data available that was needed to help define the simulation parameters. Also Ceia et al.’s, 2011 population data more comparable to Monticelli et al.’s (2010) estimates than Gil et al.’s (2015) population estimate. All other parameters were set to default as there was no other available data.

Carrying Capacity (K): Rationale for selection

As there was no available carrying capacity data, K was estimated by multiplying the total sample area of 15 200 hectares by an estimated density of 0.23 birds per hectare(Ceia et al., 2011). This gave K = 3496 individuals. All other parameters were left atdefault as there was no other available data.

Males FemalesAge Number of

individualsMortality

rateNumber

died% of total

male populatio

n

Number of individuals

Mortality rate

Number died

% of total female

population

0 to 1 97 0.62 60 14 97 0.62 60 141 to 2 472 0.38 179 41 472 0.38 179 412 to 3 293 0.38 111 26 293 0.38 111 263 to 4 181 0.38 69 16 181 0.38 69 164 to 5 112 0.38 43 10 112 0.38 43 105+ 70 0.38 26 6 70 0.38 26 6

Table 2: showing how mortality rates were calculated. This is based on Ceia et al.’s (2011) population estimate of870 adults and 194 juveniles. The juvenile mortality rate is inferred from Ramos (1993) and the adult mortality rateis taken from Monticelli et al., 2010. A male to female sex ratio of 50:50 is assumed.

8


3 Results

3.1 Summary of simulation results

In 500 simulations of 100-year extinction forecast for Pyrrhula murina, 232 went extinct and 268 survived (see Figure 3 graphical simulation output). This gives a probability of extinction of 0.46400 (0.02230 SE), or a probability of success of 0.53600 (0.02230 SE). 232 simulations went extinct at least once. Of those going extinct, the mean time to first extinction was 70.01 years (1.30 SE, 19.74 SD). The population showed an increase from initial population size 14 times and a corresponding decrease in population size 86 times from the initial population size of 1064 individuals. At year 100 the mean population size across extant populations was 529.78 individuals (52.14 SE; 853.53 SD). This corresponds to a decrease of 50.21% in population size over 100 years. The number of extant alleles declined by 97.12% over the same period indicating, a significant loss in genetic variation within the population. In year 100, 2.84 lethal alleles were in a total population of 529.78 individuals. The population growth rate while positive was quite low at 0.0002 as was the net replacement rate of 1.0015. Under exponential growth rate conditions the population never reached carrying capacity over the 100 year time span (see Figure 4). Mean generation length was significantly higher than that reported by the IUCN Red List.

Means across all populations (extant and extinct):Mean final population was 284.02 (30.32 SE; 678.03 SD).

Age 0 1 2 3 4 Adults Total 0.00 37.47 20.04 13.73 10.98 59.13 141.36 Males 0.00 37.94 19.86 13.75 11.14 59.98 142.67 Females

Means across extant populations only:Mean final N for extant populations was 529.78 (52.14 SE; 853.53 SD).

Age 0 1 2 3 4 Adults Total 0.00 69.91 37.40 25.62 20.49 110.31 263.72 Males 0.00 70.78 37.05 25.65 20.79 111.90 266.17 Females

Across all years, prior to carrying capacity truncation, mean growth rate (r) was -0.0395 (0.0016 SE, 0.3252 SD)

Final expected heterozygosity was 0.9223 (0.0053 SE; 0.0874 SD)Final observed heterozygosity was 0.9626 (0.0036 SE; 0.0590 SD)The initial number of extant alleles was 2128 (0.00 SE; 0.00 SD) and the final number of extant alleles was 61.29 (3.69 SE; 60.38 SD)Final number of mt haplotypes was 17.38 (0.99 SE; 16.13 SD)Final lethal alleles / diploid was 2.841 (0.034 SE; 0.550 SD)Mean Ne calculated from loss of heterozygosity in extant populations: 66.30

9


Figure 3: Graph showing 500 simulations of a 100-year extinction probability event based on the input data in the Results section.

3.2. Demographic Results

VORTEX calculated deterministic results by creating a life table based on input data. The intrinsic population growth rate was low at 0.0002. Similarly, other results were low; the rate of change was 1.0002 and the net replacement rate was 1.00015. The exponential growth curve was almost linear and did not increase significantly above the initial population size (see Figure 4). The generation time for: females = 9.36 and males = 9.36 was significantly high owing to the estimated generation length being used as an age for first offspring.

Stable age distribution: Age class Females Males 0 0.124 0.124 1 0.099 0.099 2 0.054 0.054 3 0.037 0.037 4 0.029 0.029 5 0.024 0.024

10


6 0.021 0.021 7 0.018 0.018 8 0.016 0.016 9 0.014 0.014 10 0.012 0.012 11 0.010 0.010 12 0.009 0.009 13 0.008 0.008 14 0.007 0.007 15 0.006 0.006 16 0.005 0.005 17 0.004 0.004 18 0.004 0.004

Ratio of adult males to adult females: 1.000

Initial population size, N = 1064Initial carrying capacity, K = 3496

Figure 4: Graph showing the exponential growth rate of the population over 100 years.

3.3. Year by year simulation summary

Project: 100 year extinction forecast for Pyrrhula murina

Scenario: 100 year extinction forecast for Pyrrhula murina

11


Population 1: Population1

Year 0 N[Extinct] = 0, P[E] = 0.000 N[Surviving] = 500, P[S] = 1.000 Mean size (all populations) = 1064.00 (0.00 SE; 0.00 SD) Means across extant populations only: Population size = 1064.00 (0.00 SE; 0.00 SD) Expected heterozygosity = 0.9995 (0.0000 SE; 0.0000 SD) Observed heterozygosity = 1.0000 (0.0000 SE; 0.0000 SD) Number of extant alleles = 2128.00 (0.00 SE; 0.00 SD) Number of mt haplotypes = 1064.00 (0.00 SE; 0.00 SD) Lethal alleles / diploid = 3.14 (0.00 SE; 0.05 SD)



Year 3 N[Extinct] = 0, P[E] = 0.000 N[Surviving] = 500, P[S] = 1.000 Mean size (all populations) = 1077.30 (19.05 SE; 425.87 SD) Means across extant populations only:

12


Population size = 1077.30 (19.05 SE; 425.87 SD) Expected heterozygosity = 0.9987 (0.0000 SE; 0.0006 SD) Observed heterozygosity = 1.0000 (0.0000 SE; 0.0000 SD) Number of extant alleles = 1165.59 (16.11 SE; 360.23 SD) Number of mt haplotypes = 567.02 (7.92 SE; 177.08 SD) Lethal alleles / diploid = 3.14 (0.00 SE; 0.08 SD)




Year 7

13


N[Extinct] = 0, P[E] = 0.000 N[Surviving] = 500, P[S] = 1.000 Mean size (all populations) = 1099.75 (29.57 SE; 661.27 SD) Means across extant populations only: Population size = 1099.75 (29.57 SE; 661.27 SD) Expected heterozygosity = 0.9977 (0.0001 SE; 0.0018 SD) Observed heterozygosity = 1.0000 (0.0000 SE; 0.0002 SD) Number of extant alleles = 809.52 (16.21 SE; 362.49 SD) Number of mt haplotypes = 368.08 (7.31 SE; 163.47 SD) Lethal alleles / diploid = 3.14 (0.00 SE; 0.09 SD)



Year 10 N[Extinct] = 0, P[E] = 0.000 N[Surviving] = 500, P[S] = 1.000 Mean size (all populations) = 1110.37 (37.82 SE; 845.63 SD) Means across extant populations only: Population size = 1110.37 (37.82 SE; 845.63 SD) Expected heterozygosity = 0.9968 (0.0001 SE; 0.0028 SD) Observed heterozygosity = 0.9999 (0.0000 SE; 0.0005 SD) Number of extant alleles = 656.32 (15.54 SE; 347.58 SD)

14


Number of mt haplotypes = 277.42 (6.36 SE; 142.19 SD) Lethal alleles / diploid = 3.13 (0.00 SE; 0.11 SD)





15






Year 18

16






17







18






Year 29

19






20







21






Year 40

22






23







24






Year 51

25






26







27






Year 62

28






29







30






Year 73

31






32







33






Year 84

34






35







36






Year 95

37






38





3.4. Suggestions for improved long-term viability of the species:

A second extinction forecast was simulated with only one parameter changed that produced far more reassuring results for the future prospect of the Azores Bullfinch. Under ‘Catastrophes’ the level of severity from Habitat Degradation was reduced from 0.5 to 0.75. All other simulation parameters were identical to the first simulation. As can be seen from Figure 5, a reduction in habitat degradation prevented the species from going extinct over a 100 year time span in this extinction simulation. In 500 simulations of 100 year extinction forecast for Pyrrhula murina, 0 went extinct and 500 survived. This gives a probability of extinction of 0.00000 (0.00000 SE), or a probability of success of 1.00000 (0.00000 SE). The population grew from 1064 (0.00 SE; 0.00 SD) individuals in year 0 to 2735 individuals (37.00 SE; 827.29 SD) in year 100. Inbreeding depression reduced the number of extant alleles from 2128 in year 0 to 259.94 in year 100 indicating a loss of genetic variation. Compared with the previous simulation an improved growth rate of 0.0041 and net replacement rate of 1.4829 was calculated. The exponential growth reached carrying capacity in less than 30 years (see Figure 6).

39


A third extinction forecast was simulated using a reduced time to first offspring of 2 years old for both sexes. All other parameters were identical to the first simulation. This reduced to generation length to 4.08 years for each sex which is a more compatible figure with that of Birdlife International’s (2013) 4.8 years. The intrinsic growth rate increased to 0.0201 and exponential growth reached its carrying capacity at about 60 years. However the probability of extinction was slightly higher at 47.4% than the first simulation at 46.4%.

Means across all populations (extant and extinct):

Mean final population was 2735.30 (37.00 SE; 827.29 SD). Age 0 1 2 3 4 Adults Total 0.00 364.65 200.82 133.97 104.98 564.79 1369.21 (Males) 0.00 364.31 200.18 134.17 104.37 563.06 1366.09 (Females)

Figure 5: Alternate extinction forecast with a less severe catastrophic impact from habitat degradation.

40


Figure 6: Exponential growth of Azores Bullfinch after a reduced level of severity from habitat degradation.

4 Discussion

The results from the first simulation show that there was a significant, i.e. 46.4% chance, of the only remaining population of the Azores Bullfinch going extinct by 100 years’ time with a mean time to the first extinction of just over 70 years. From the available input data the extinctions are most likely to occur due to environmental stochastic events, i.e. habitat degradation (a reduction of native habitat due to fragmentation and invasive alien species). This is compatible with the majority of research done on the population trends of the species relative to the availability of native forest (Ramos, 1993; Ramos, 1994a,; Ramos, 1994b; Monticelli et al., 2010; Ceia et al., 2009; Ceia et al., 2011). In addition, Teodosio (2009) identifies the limited area of suitable habitat as a critical impact on the survival of the species. Therefore the long-term sustainable forecast for this species requires an increase in habitat area. It should be noted that the level of severity of habitat degradation was most likely an over-estimation for this simulation. This was done with caution in mind as the current resources for habitat management are short-term and subject to successful funding bids (Teodosio, 2009 and Teodosio, 2014). The current EU LIFE+ project that is funding the management of the Azores Bullfinch will end in 2018 (EC Europa, 2016). There is a Species Action Plan in place that is due for review in 2019 (Teodosio, 2009).

In the first simulation the exponential growth was depressed due to a low intrinsic growth rate. This was most likely due to an over estimation of the age at first offspring for each sex, i.e. 5 years old. A third simulation with reduced age at first offspring, i.e. 2 years old for each sex, calculated a generation length of 4.08 years that is more compatible with that of Birdlife International, 2013 and an exponential growth curve that reached carrying capacity by 60 years. However the probability of the third simulation experiencing an extinction event was

41


very similar to the first simulation. Therefore, it appears that the accuracy of age at first offspring is not highly significant in predicting an extinction event for this population.

With continued habitat management for the species reflected by a habitat degradation severity multiplier of 0.75 on reproduction and survival rates the simulation experienced no extinction. Perhaps this level of severity best reflects the current habitat management where suitable areas have been recovered from invasive plants and some areas replanted with native species. Under that level of severity no extinctions were forecast in the 100 years and the population size increased by almost 123%. This of course is subject to renewed future funding and is not fully cognisant of the long term effects of genetic loss due to inbreeding. As genetic information on the species is currently unknown it could not be modelled except for the likelihood of inbreeding depression. This of course is most likely to occur in an isolated population like the Azores Bullfinch. Inbreeding depression was selected based on O’Grady et al.’s (2006) estimated lethal equivalents for vertebrate species. The results showed a highly significant decrease of 97.12% in the number of extant alleles by the end of the 100-year simulation. This correlates with a decrease in genetic diversity. Spielman et al.’s (2004) research on Drosophila demonstrated that reduced genetic diversity lowers resistance to disease. They advised wildlife managers to strive to minimise inbreeding in threatened populations and to try and prevent threatened inbred populations from being exposed to disease. In the case of this single remaining population a loss of genetic diversity could be a serious threat to the long term survival of the species regardless of habitat management efforts. The number of lethal alleles decreased from 3.14 to 2.84 over the simulation. This is most likely due to purging of the genetic load (Lacy and Pollack, 2015a and Lacy et al. 2015b) and a significantly reduced population size by year 100. To determine the extent to which inbreeding depression may influence the survival of the population a simulation was run with no environmental stochastic events. To speed up the simulation process a population based model was also selected. The outcome was no extinctions occurred in the 100 years and the exponential population growth reached carrying capacity in about 15 years. This demonstrated that the levels of inbreeding depression were not significant. However that statement should be taken with caution as there was not genetic input so the reality of inbreeding effects is ultimately unknown.

Predation was not modelled as a catastrophic event as the level of its threat is currently unknown. However according to Birdlife International (2013), recent studies are indicating that introduced mammals, i.e. rats and mustelids, to the Island may be having a negative effect on nesting success.

5 Recommendations for future management

Research into the genetics of this population is essential to determine the level of inbreeding and to produce a more accurate simulation of an extinction forecast.

42


Long term resources are required to maintain habitat management that is vital to sustain the Azores Bullfinch population.

Conclusive research is required to establish the level of threat of introduced mammals to the Azores Bullfinch population.

A captive breeding programme using individuals that are not inbred should be initiated as an insurance policy for the future survival of this species.

6 References

ADW (Animal Diversity Web), Accounts: Pyrrhula pyrrhula. Available at: http://animaldiversity.org/accounts/Pyrrhula_pyrrhula/. Accessed [29 April 2016].

Bibby, C.J., Charlton, T.D., Ramos, J. (1992) ‘Studies of west Palearctic birds. 191. Azores Bullfinch’, British Birds, 85: pp. 677-680, December 1992.

Birdlife International. 2013. Pyrrhula murina. The IUCN Red List of Threatened Species 2013: e.T22720676A50432049. Available at: http://dx.doi.org/10.2305/IUCN.UK.2013-2.RLTS.T22720676A50432049.en [Accessed 29 April 2016]

Caughley, G. (1994) ‘Directions in conservation biology’, Journal of Animal Ecology, 63 (2), pp. 215-244.

Ceia, R., Heleno, R. and Ramos, J.A. (2009) ‘Summer abundance and ecological distribution of passerines in native and exotic forests in São Miguel, Azores’, Ardeola, 56 (1), pp. 25-39.

Ceia, R.S., Sampaio, H.L., Paerjo, S.H., Heleno, R.H., Arosa, M.L., Ramos, J.A. and Hilton, G.M. (2010), ‘Throwing the baby out with the bath water: does laurel forest restoration remove a critical winter food supply for the critically endangered Azores Bullfinch?’, Biological Invasions, 13, pp. 93-104.

Ceia, R.S., Ramos, J.A., Heleno, R.H., Hilton, G.M and Marques, T.A. (2011) ‘Status assessment of the critically endangered Azores Bullfinch Pyrrhula murina’, Bird Conservation International, 21, pp. 477-489.

EC Europa (2016/Last updated 02/05/2016) European Commission: Environment: LIFE programme. Available at: http://ec.europa.eu/environment/life/project/Projects/index.cfm?fuseaction=home.search&cfid=2227154&cftoken=24178732. [Accessed 02 May 2016]

Gil, A., Ceia, R., Coelho, R., Teodosio, J., Sampaio, H., Verissimo, C., Heleno, R., Ramos J. and Timoteo, S. (2015) ‘The Priolo Atlas: A citizen science based census initiative for supporting Pyrrhula murina habitat conservation and restoration policies in São Miguel Island (Azores, Portugal)’, Ecological Engineering, 86 (2016), pp. 45-52.

43


HAGR (Human Aging Genomic Resources), An Age: The animal aging and longevity database: Pyrrhula pyrrhula. Available at: http://genomics.senescence.info/species/entry.php?species=Pyrrhula_pyrrhula. [Accessed 28 April 2016].

Heleno, R., Lacerda, I., Ramos, J.A. and Memmott, J. (2010) ‘Evaluation of restoration effectiveness: community response to the removal of alien plants’, Ecological Applications, 20 (5), pp. 1191-1203.

Lacy, R.C., and Pollak, J.P. (2015a) Vortex: A Stochastic Simulation of the Extinction Process. Version 10.1. Chicago Zoological Society, Brookfield, Illinois, USA.

Lacy, R.C., Miller, P.S. and Traylor-Holzer, K. (2015b) Vortex 10 User’s Manual. 15 April 2015 update. IUCN SSC Conservation Breeding Specialist Group, and Chicago Zoological Society, Apple Valley, Minnesota, USA.

Martins, I., Arosa, M.L., Ceia, R.S., Parejo, S., Ramos, J.A. and Damgaard, C. (2012) ‘The winter energetics of the Azores Bullfinch and the implications for the restoration of its native laurel forest habitat’, Ecological Modelling, 231, pp. 80-86.

Monticelli, D., Ceia, R., Heleno, R., Laborda, H., Timóteo, S., Jareño, D., Hilton, G. M. and Ramos, J. A. (2010) ‘High survival rate of a critically endangered species, the Azores Bullfinch Pyrrhula murina as a contribution to population recovery’, Journal of Ornithology, 151, pp. 627–636.

O’Grady, J.J., Brook, B.W., Reed, D.H., Ballou, J.D., Tonkyn, D.W. and Frankham, R. (2006) ‘Realistic levels of inbreeding depression strongly affect extinction risk in wild populations’, Biological Conservation, 133, pp. 42-51

Ramos, J.A. (1993) Status and ecology of the Priolo or Azores Bullfinch, Pyrrhula murina. PhD thesis. Wolfson College, Oxford.

Ramos, J.A. (1994a) ‘Fern frond feeding by the Azores Bullfinch’, Journal of Avian Biology, 25 (4), pp. 344-347.

Ramos, J.A. (1994b) ‘The diet of the Azores Bullfinch Pyrrhula murina and floristic variation within its range’, Biological Conservation, 71, pp. 237-249.

Ramos, J. A. (1996) ‘Introduction of exotic tree species as a threat to the Azores bullfinch population’, Journal of Applied Ecology, 33, pp. 710-722.

Ramos, J. A. (1998) ‘Biometrics, weights, breeding and moulting seasons of passerines in Azores cloud forest’, Ringing and Migration, 19 (1), pp. 17-22.

Reed, D.H., O’Grady, J.J., Ballou, J.D. and Frankham, R. (2003) ‘The frequency and severity of catastrophic die-offs in vertebrates’, Animal Conservation, 6, pp. 109-114.

44


RSPB. 21 facts about Bullfinches. Available at: http://www.rspb.org.uk/community/wildlife/f/13609/t/9147.aspx. [Accessed 29 April 2016]

Spielman, D., Brook, D.W., Briscoe, D.A. and Frankham, R. (2004) ‘Does inbreeding and loss of genetic diversity decrease disease resistance?’, Conservation Genetics, 5, pp. 439-448.

Teodosio, J., Ceia, R. and Costa, L. (2009). ‘Species action plan for the Azores Bullfinch Pyrrhula murina in the European Union’, 19 pp.

Teodosio, J. (2014). Relatorio Inicial do projeto LIFE+ Terras do Priolo (LIFE12 NAT/PT/000527). Sociedade Portuguesa para o Estudo das Aves, Lisboa (relatorio nã publicado).

45

envb 40320-assignment 3-tkelly

Documents