ArticlePDF Available

Using non-systematic surveys to investigate effects of regional climate variability on Australasian gannets in the Hauraki Gulf, New Zealand

  • Instituto de Investigaciones Marinas y Costeras (IIMyC), CONICET Universidad Nacional de mar del Plata Argentina

Abstract and Figures

Few studies have investigated regional and natural climate variability on seabird populations using ocean reanalysis datasets (e.g. Simple Ocean Data Assimilation (SODA)) that integrate atmospheric information to supplement ocean observations and provide improved estimates of ocean conditions. Herein we use a non-systematic dataset on Australasian gannets (Morus serrator) from 2001–2009 to identify potential connections between Gannet Sightings Per Unit Effort (GSPUE) and climate and oceanographic variability in a region of known importance for breeding seabirds, the Hauraki Gulf (HG), New Zealand. While no statistically significant relationships between GSPUE and global climate indices were determined, there was significant correlation between GSPUE and regional SST anomaly for HG. Also, there appears to be strong link between global climate indices and regional climate in the HG. Further, based on cross-correlation function coefficients and lagged multiple regression models, we identified potential leading and lagging climate variables, and climate variables but with limited predictive capacity in forecasting future GSPUE. Despite significant inter-annual variability and marginally cooler SSTs since 2001, gannet sightings appear to be increasing. We hypothesize that at present underlying physical changes in the marine ecosystem may be insufficient to affect supply of preferred gannet main prey (pilchard Sardinops spp.), which tolerate a wide thermal range. Our study showcases the potential scientific value of lengthy non-systematic data streams and when designed properly (i.e., contain abundance, flock size, and spatial data), can yield useful information in climate impact studies on seabirds and other marine fauna. Such information can be invaluable for enhancing conservation measures for protected species in fiscally constrained research environments.
Content may be subject to copyright.
Using non-systematic surveys to investigate effects of regional climate
variability on Australasian gannets in the Hauraki Gulf, New Zealand
Mridula Srinivasan, Mariela Dassis, Emily Benn, Karen A. Stockin,
Emmanuelle Martinez, Gabriel E. Machovsky-Capuska
PII: S1385-1101(15)00018-0
DOI: doi: 10.1016/j.seares.2015.02.004
Reference: SEARES 1340
To appear in: Journal of Sea Research
Received date: 5 September 2014
Revised date: 16 January 2015
Accepted date: 9 February 2015
Please cite this article as: Srinivasan, Mridula, Dassis, Mariela, Benn, Emily,
Stockin, Karen A., Martinez, Emmanuelle, Machovsky-Capuska, Gabriel E., Using
non-systematic surveys to investigate effects of regional climate variability on Aus-
tralasian gannets in the Hauraki Gulf, New Zealand, Journal of Sea Research (2015),
doi: 10.1016/j.seares.2015.02.004
This is a PDF file of an unedited manuscript that has been accepted for publication.
As a service to our customers we are providing this early version of the manuscript.
The manuscript will undergo copyediting, typesetting, and review of the resulting proof
before it is published in its final form. Please note that during the production process
errors may be discovered which could affect the content, and all legal disclaimers that
apply to the journal pertain.
Using non-systematic surveys to investigate effects of regional climate
variability on Australasian gannets in the Hauraki Gulf, New Zealand
Mridula Srinivasan1,*, Mariela Dassis2, Emily Benn3, Karen A. Stockin4, Emmanuelle Martinez5,3, Gabriel E.
1 National Marine Fisheries Service, 1315 East-West Highway, Silver Spring, MD 20910, USA
2 Facultad de Ciencias Exactas y Naturales, Instituto de Investigaciones Marinas y Costeras, Universidad Nacional de
Mar del Plata-CONICET, Funes 3350 (7600), Mar del Plata, Argentina
3 School of Biological Sciences and The Charles Perkins Centre, University of Sydney, Sydney, Australia
4 Coastal-Marine Research Group, Institute of Natural and Mathematical Sciences, Massey University, Auckland,
New Zealand
5 Pacific Whale Foundation, Wailuku, Hawai‘i 96793, United States of America
6 The Charles Perkins Centre and Faculty of Veterinary Science, School of Biological Sciences, University of
Sydney, Sydney, Australia
Corresponding author email: * and **
Author contributions: KAS collected part of dataset, MS, MD, EM and GEM-C analysed the data. MS, MD, KAS,
EM, EB and GEM-C wrote and edited the manuscript.
Key Words: seabirds, climate variability, apex predators, Hauraki Gulf, New Zealand
Few studies have investigated regional and natural climate variability on seabird populations using ocean reanalysis
datasets (e.g. Simple Ocean Data Assimilation (SODA)) that integrate atmospheric information to supplement ocean
observations and provide improved estimates of ocean conditions. Herein we use a non-systematic dataset on
Australasian gannets (Morus serrator) from 2001-2009 to identify potential connections between Gannet Sightings
Per Unit Effort (GSPUE) and climate and oceanographic variability in a region of known importance for breeding
seabirds, the Hauraki Gulf (HG), New Zealand. While no statistically significant relationships between GSPUE and
global climate indices were determined, there was significant correlation between GSPUE and regional SST
anomaly for HG. Also, there appears to be strong link between global climate indices and regional climate in the
HG. Further, based on cross-correlation function coefficients and lagged multiple regression models, we identified
potential leading and lagging climate variables, and climate variables but with limited predictive capacity in
forecasting future GSPUE. Despite significant inter-annual variability and marginally cooler SSTs since 2001,
gannet sightings appear to be increasing. We hypothesize that at present underlying physical changes in the marine
ecosystem may be insufficient to affect supply of preferred gannet main prey (pilchard Sardinops spp.), which
tolerate a wide thermal range. Our study showcases the potential scientific value of lengthy non-systematic data
streams and when designed properly (i.e., contain abundance, flock size, and spatial data), can yield useful
information in climate impact studies on seabirds and other marine fauna. Such information can be invaluable for
enhancing conservation measures for protected species in fiscally constrained research environments.
Many studies have explored quantitative and qualitative relationships between ecosystem state and seabird
vital rates and life history parameters within the context of climate change impacts (Dann et al. 2003; Mills et al.
2008; Ainley and Blight 2009; Chambers et al. 2011), predominantly natural climatic fluctuations. Seabirds are
subject to the vagaries of both terrestrial and oceanic changes as they breed on land but spend the majority of their
lives at sea (Lack 1968). These long-lived marine apex predators are well known ―biomonitor species‖, offering
opportunities to detect and assess the biological effects of changes in physical parameters (sea surface temperature -
SST, salinity, depth of thermocline and environmental oscillations) of the marine ecosystem (Schreiber and
Schreiber 1984; Furness and Camphuysen 1997).
To date, research into climate impacts on marine ecosystems tend to focus on biogeochemical and lower
trophic effects (Ito et al. 2010; Doney et al. 2012). However, this is changing with recent studies now involving an
understanding climate variability effects on top marine predators, as reviewed in Hobday et al. (2013) and
ecosystem forecasting and downscaled modelling in fisheries ecology (Hollowed et al. 2013). There is also a wealth
of literature on climate impacts on seabird reproductive biology and population characteristics (reviewed in
Sydeman et al. 2012), although, studies in waters around Australia and New Zealand in the south-western Pacific are
limited (Chambers et al. 2011).
Previous studies on seabirds indicate that they adapt variably to climate change the effects are often
dictated by intrinsic life history factors and indirectly, via increases or decreases in SST and other climatological
factors (Chambers et al. 2012, 2013; Quillfeldt and Masello 2013). Although seabird responses to environmental
change are difficult to predict, there are certain consistent patterns (e.g. changes in distribution, phenology) that do
enhance our ability to understand and forecast potential population level consequences in different geographic
The need for inter-decadal time series data has created impetus to establish target species or ecosystem-
specific studies. However, such studies are not always possible with depreciating research capacity and budgets
worldwide. Thus, alternative data sources need to be considered while acknowledging the limitations associated
with these datasets.
Information gleaned from examining historic and current climate trends and purported correlation with
species distribution or occurrence patterns, and other demographic parameters can help shape how future studies
involving systematic and non-systematic data collection are structured and what parameters are influential. This is
especially true for mobile species such as seabirds (Bunce et al. 2002) and marine mammals (Ballance et al. 2006)
that feed at the top of the food chain, but are part of a complex food network that generally preclude direct
correlations with physical and biological changes. However, they can respond to some systemic changes more
strongly than others.
We consider a survey to be systematic if data was collected from a randomized study design with an equal
probability of sampling all points in the study area, e.g., line-transect boat or aerial surveys (Buckland et al. 2012).
Whereas, we consider non-systematic surveys to be data collected opportunistically from a boat or aircraft providing
a reasonable coverage of the study area and similar methods of data collection.
The Hauraki Gulf (HG) North Island, New Zealand (Fig. 1) is recognized for its cultural, economic and
ecological significance as a Marine Park (Hauraki Gulf Marine Park Act (2000), Parliamentary Counsel Office,
Wellington, New Zealand). The HG encompass an area of ca. 4,000 sq km, is a shallow (maximum water depth ~60
m), semi-enclosed body of water riddled with islands and shallow reefs that extend into waters of the western Pacific
Ocean. Water circulation in the region is primarily driven by tides and wind (Heath 1985; Zeldis et al. 2004; Gaskin
and Rayner 2013). Most of the HG area is also recognized as an ‗Important Bird Area‘ (IBA) by New Zealand
Forest and Bird (, an affiliate of Birdlife International (Gaskin and Rayner 2013).
This region is a breeding spot for one of the most successful seabirds in New Zealand, the Australasian
gannet (Morus serrator; hereafter gannets). Gannets feed mainly on pelagic fish and squid (Robertson 1992;
Machovsky-Capuska et al. 2011a; Schuckard et al. 2012; Tait et al. 2014). These highly specialized marine
predators have been reported to travel for food as far as 388.5 km (Machovsky-Capuska et al. 2013a, 2014) with the
ability to assess prey density to increase foraging success (Machovsky-Capuska et al. 2013b). Their populations
have been increasing since the 1980s around New Zealand and the 1990s in Australia (Bunce et al. 2002). Currently,
there are 29 gannet colonies in New Zealand, three located on the east coast and 26 on the west coast, with an
estimated total of 48,509 pairs based on a census in 2000 (Nelson 2005), and an annual mean population growth rate
of 2.3 % (Robertson 1992).
The HG is home to four breeding colonies: Horuhoru Island, Mahuki Island, Motukaramarama, and
Motutakupu (Wingham 1985), with an estimated population of 12,726 pairs according to the 1980/81 census
(Wodzicki et al. 1984) no recent counts are available. It appears that gannet populations may be robust in the HG;
however, with increasing human impacts and changing oceanographic conditions, it is unknown how these changes
are permeating into the ecosystem and affecting gannet populations (Gaskin and Rayner 2013). For example, the HG
supports a highly profitable fishery for snapper (Pagrus spp.) as well marine farming. In fact, New Zealand‘s largest
marine farms are in Firth of Thames, located in the southern sector of the HG (Aquaculture New Zealand 2010).
Increases in gannet populations off New Zealand and Australia have been attributed to warming SST,
increased El Niño Southern Oscillation (ENSO) activity and associated with increased (preferred) prey availability,
i.e. pilchard (Sardinops sagax) (Bunce et al. 2002). The effect of expanding inshore commercial fishing activity in
New Zealand leading to a greater presence of surface-schooling fish, normally preyed on by commercial species,
may also impact gannet foraging behavior (Robertson 1992; Schuckard et al. 2012). However, such overlap with
commercial fisheries also raises the risk of gannet mortality via gear entanglements (Norman 2000).
In this study, we use a dataset collected during non-systematic surveys, to explore potential linkages
between regional and global climate variability and observed inter-annual fluctuations in gannet sightings in the HG.
Specifically, we examine how regional variability correlates with global climate processes (e.g. ENSO), and with
gannet sightings. In addition, we provide preliminary results about leading and lagging climate variables and climate
predictor variables that could potentially influence gannet populations in the HG. This study showcases the potential
scientific value that non-systematic long-term datasets can provide, if appropriately employed, to fill regional data
gaps in resource constrained settings.
To examine relationships between 12-year observations of gannets in the HG, New Zealand (36.3° S,
175.08° E) and regional oceanographic and climate variables, we used the Simple Ocean Data Assimilation (SODA)
reanalysis product (Version 2.0.2-4) (Carton et al. 2000a, b; Tillinger and Gordon 2010). We acquired total and
anomaly data (i.e. departure of observed conditions from average conditions in that region) for the following
variables from 1990-2012: monthly and annual SST, zonal (west-east) and meridional (south-north) wind stress
(horizontal force of the wind at the surface of the ocean) and velocity, and cube of wind speed (a measure of water
turbulence and mixing in surface waters).
The SODA analysis is derived from the global circulation model that uses the Geophysical Fluid Dynamics
Laboratory Modular Ocean Model (Version 2.b) (Carton et al. 2000a, b). Data is derived over a rectangular grid
covering our region of interest (i.e. HG). SODA data are stored on a 0.5 x 0.5 degree grid with a resolution at 36° S
to be approximately 44 km by 55 km. The chlorophyll data was obtained from NASA‘s MODIS mapped, 'monthly'
data on 9 km or 1/12 degree global grid (, available from 2003-2012 for the HG.
Gannet data were collected across all austral seasons between 2001 and 2009 on board Dolphin Explorer
(DE), a 20 m tour catamaran powered by twin 350 horse-power inboard diesel engines, with a 5 m elevated
observation platform. Due to permit conditions, tours conducted by DE in the Hauraki Gulf were restricted to waters
south of a line from Cape Rodney to Great Barrier Island and to Cape Coleville on the Coromandel Peninsula (Fig.
1); and in water depths > 10 m. Data presented here represent all months of each year with the exception of August-
September 2002 and January-May 2007, when the vessel was on dry dock. While surveys were non-systematic,
survey routes selected were based on prevailing weather and sea conditions, with an attempt made to cover regions
not previously surveyed within that month in on order to facilitate on-board research focusing on common dolphin
(Delphinus sp, Stockin et al. 2008b;2009) and Bryde‘s whales (Balaenoptera edeni, Wiseman et al. 2011).
Observations were undertaken by experienced observers using a continuous scan sampling methodology
(Hoffman et al. 1981) visually with or without binoculars (Bushnell 10 x 50 magnifications). Sighting cues used to
detect cetaceans included splashing and/or water disturbance due to activity of animals, including gannets. Once
within 400 m of a group of gannets and other seabirds, environmental variables were recorded (water depth, SST,
tidal and sea state, visibility, wind direction and speed). Time and location of gannet sightings were noted using a
Global Positioning System (GPS). Data included in the analysis were limited to good visibility (≥ 1 k m) and
Beaufort Sea State < 4.
Gannet sightings data were analysed for 2001-2009 (Fig. 2) and included data for 99 months. The number
of individual gannets observed per sighting or flock size was not recorded. To normalize sightings information
across months and years, a sighting per unit effort (SPUE) was calculated, where:
  
We used monthly GSPUE to correlate with mean monthly climate and oceanographic SODA variables
across years (2001-2009). Gannets are commonly found in multi-species foraging aggregations. These aggregations
can include common dolphins, Bryde‘s whales, shearwaters and terns, kahawai (Arripis spp.), jack mackerel
(Trachurus spp.), snapper (Pagrus spp.) and hammerhead sharks (Sphyrna spp.). The frequency of occurrence of
these multispecies associations is reflective of prey abundance (Stockin et al. 2008, 2009; Machovsky-Capuska et al.
2011a). As such, we calculated an annual Multi-species SPUE (MSPUE), which is the occurrence of multi-species
aggregations during gannet sightings and correlated the MSPUE with annual mean climate and oceanographic
SODA parameters for HG.
To explore the influence of global climate processes via teleconnections on regional climate dynamics, we
investigated ENSO and regional SST pattern correlations over a longer time series (1990-2012). We used Southern
Oscillation Index (SOI) total and anomaly data from the Bureau of Meteorology, Australia
(, and Niño 3.4 (equatorial Pacific 170W 120W, 5S 5N ) and Niño 4 (equatorial
and central Pacific 160E 150W, 5S 5N) region data, available through the Climate Prediction Centre, National
Centers for Environmental Prediction, USA (NCEP; These ―Niño boxes‖ are
typically used in the diagnosis and forecast of El Niño.
We also examined a potential association with the Southern Annular Mode (SAM) or Antarctic Oscillation,
which is the westerly wind belt around Antarctica with strong influence on large-scale variability in atmospheric
circulation in the Southern Hemisphere and describes large-scale alternations of atmospheric mass between the mid-
and high latitudes. Typically, negative SAM is associated with El Niño events (Wang and Cai 2013). On a shorter
time-scale (2001-2009), we also tested for correlations between GSPUE (2001-2009) data with the global climate
indices. We then conducted sample cross-correlations and ordinary linear lagged regressions of the climate and
gannet time series data in R (R Core Team 2014), to identify significant linear relationships between our time series
of interest, and identify potential climate variables that might be useful predictors of GSPUE. We used complete
case analysis to deal with GSPUE missing values (n=9). The time series were examined for significant evidence of
non-zero correlations for lags 1-20 months using the Ljung-Box test in R. Climate data were lagged by one month
and tested against GSPUE data (2001-2009). Maximum lags (k) were automatically limited to one less than the
number of observations in the series, but were also evaluated based on Cross-Correlation Function (CCF) lag plots.
Since we were primarily interested in identifying ―leading‖ climate variables to help predict future values of
GSPUE, we focused on the negative k spectrum.
We ran parametric tests as data were normally distributed with constant variance. The GSPUE was
significantly different across years (ANOVA, F = 7.580, n = 99, df = 8, P < 0.0001, but not across months within
each year (ANOVA, F = 0.651, n = 99, df = 11, P = 0.781, α = 0.05). In general, an increase in gannet observations
corresponded to an overall decrease in HG annual mean SST (total) from ca. 18.2 to 17.4 °C (Fig. 3a). Although the
mean annual SST has remained stable, ranging from 17.5 °C in 1990 to 17.7 °C in 2012, seasonal SST anomalies in
HG indicate an overall cooler period in the 1990s, with a slightly warmer period after 1998, followed by a decline
and plateau (Fig. 3b). This trend is also reflected in the overall variability in SST anomaly in the HG since 1990,
which is negatively correlated with SOI Anomaly (Fig. 3c).
Pearson‘s correlations of GSPUE and SODA climate and oceanographic variables resulted in a significant
correlation with only SST anomaly (Pearson‘s correlation r=-0.226, n=99, p<0.05). Annual correlations between
MSPUE and all annually averaged SODA variables were statistically non-significant . For wind velocities and
stress, values greater than zero indicate northerly winds in the meridional direction (S-N) and values greater than
zero indicate easterly winds in the zonal direction (W-E). Overall, during the period of interest, 3-year moving
averages suggest that winds tended to be more north and eastwards in 2004, south and eastwards between 2005 and
2007, and north and westwards since 2007 (Fig. 4). In general, wind cube and chlorophyll anomaly data, based on 3-
year moving averages, show a decrease after 2006-2007 (Fig. 4).
We found no significant correlations between GSPUE and the global climate indices. Over a longer time
frame (1990-2012), there are clear and significant relationships between regional SST in the HG and all global
climate indices tested. SSTHG (total and anomalies) were positively correlated with SAM and SOI and predictably,
negatively correlated with Niño 3.4 and 4.0 indices (Appendix).
Niño 3.4 and SOI variability suggests that in general 2009-2010, 2006-2007, 2002-2003 were associated
with weak to moderate El Niño periods and weak SOI with the strongest ENSO activity during 1997-1998 and
1994-1995. In contrast, La Niña was strong during 2010-2012 and generally moderate to weak historically for the
time period considered (Source: Bureau of Meteorology, Australia ―ENSO wrap up‖ Generally, sustained periods of negative (positive) SOI are associated with
warm (cold) ocean waters corresponding to El Niño (La Niña) episodes (Fig. 3c).
Since the time series satisfied the properties for a stationary series (autocorrelation for a specific lag is same
throughout the time series), we conducted sample CCF and lagged regressions. For a specific lagt+k (t = time, k =
number of lags), negative correlations tend to imply that the predictor variable ‗leads the dependent variable of
interest, and positive values could suggest that climate variables lag the outcome variable. For example, in Fig. 5,
the negative correlations for meridional wind velocity (total and anomaly) for negative k, imply that these variables
‗lead‘ GSPUE. Whereas, positive correlations of cube of wind speed (total and anomalies), SOI anomaly and SAM
suggest that these could lag‘ GSPUE (Fig. 5). Dominant correlations corresponded to coefficients of ±0.15 or
higher depending on the variable of interest. Lags with high correlation coefficients were then tested further with
lagged linear regressions (variables with significant model outputs are shown in Table 1).
Based on scatter plots of climate variable (xt) and their lags (xt-1) and Partial Autocorrelation Function
(PACF) residuals, we determined that an autoregressive model of order 1 or AR (1) would be applicable, which is a
linear association of the current value of the time series on the previous value (t-1). Among climate variables tested
meridional wind velocity model coefficients were significant for lags, 2, 8, and 14 and lag 2 and 14 based on
meridional wind velocity anomaly coefficients.
Cube of wind speed total and anomaly coefficients were significant for lags 3, 7, and 9 and lags 2, 3, 7, and
9, respectively. Similarly, lag 5 and 11 for SAM and lag 2 for SOI anomaly resulted in significant coefficients
(Table 1). However, R2 values were weak (ranging from 7 % to a maximum of 16 %, Table 1). Autocorrelation and
Partial Autocorrelation Functions (ACF and PACF) of the residuals indicate minor autocorrelation.
Changes in ecosystem condition manifest themselves through physical changes that directly and indirectly
affect trophic relationships and species abundance (Stenseth et al. 2002; Mills et al. 2008; Burthe et al. 2012;
Sydeman et al. 2012). Alteration of ocean characteristics due to anthropogenic climate change is now indisputable
(IPCC 2013), but how these fluctuations translate into impacts on marine organisms at different spatial and temporal
scales is less understood (Ballance et al. 2006).
Our analysis indicates that inter-annual variability in gannet sightings was significantly and negatively
correlated with SST anomaly in HG. Lack of direct correlation with other variables tested could be due to, a) our
inability to detect a relationship due to data limitations, b) as flexible foragers (Schuckard et al. 2012), gannets
have successfully adapted to variable climatic conditions, or c)there may be a delayed reaction to systemic changes
(Doney et al. 2012). Despite the slightly cooler SSTs, we suggest that oceanographic conditions offered ideal
foraging conditions for increased gannet observations during the period of study. This is supported in part by the
spatial distribution of gannets in the study area with observations dominant around 36.5 and 37 degrees S latitude
consistently since 2001 (Fig. 6).
Although we did not see any significant relationship between GSPUE and global climate indices,
particularly the Southern Oscillation Index SOI as evidenced in previous works (Bunce et al. 2002; Stenseth et al.
2002), lagged regression models suggest that the cube of wind speed, meridional wind velocity, SAM, and SOI
could be influential factors governing gannet patterns in HG, but since they individually explain minimal variation
in gannet observations, their collective and individual predictive value requires validation. In spite of the minimum
variability explained by these variables, we know from other studies, that wind speed and direction can have an
effect on foraging efficiency and breeding success, e.g., wandering albatross, Diomedea exulans, in the Southern
Ocean (Weimerskirch et al. 2012). Weimerskirch et al. (2012) found that the meridional component was a major
driver for increase in flight speed during foraging trips for wandering albatross. Similarly, Amélineau et al. (2014)
noted that wind force and direction could affect foraging costs in northern gannets, M. bassanus. In New Zealand,
negative phases of the SAM are associated with increased westerlies and lighter winds during the positive phases of
SAM (Renwick and Thompson 2006). Thus, each of the predictor variables identified here could have potentially
important effects on foraging and breeding success for gannets, and merit further investigation.
Environmental variables can also operate in an additive fashion, constructing Generalized Additive Models
(GAMs) using various climate and other (e.g. year and month) parameter combinations may help explain gannet
variability. To avoid overstating results and to discount spurious correlations, we emphasize that such models should
be built using robust gannet datasets and population metrics such as flock size or abundance. Opportunistic surveys,
if designed to collect these additional metrics or used in combination with systematic survey data, will likely
strengthen preliminary conclusions and reduce uncertainty associated with such datasets.
The strong relationships between regional SST and global climate indices found here suggests that global
climate variability could affect the climate seascape of HG, but not necessarily translate into observable changes in
upper-trophic predators based on current evidence. Changes in SOI can alter wind strength and direction, nutrient
upwelling and SSTs (Trenberth and Shea 1987; Bunce et al. 2002). As such in the HG, there are seasonal shifts in
wind patterns which fluctuate during El Niño and La Niña episodes such that westerlies (winds from the west) are
typically associated with El Niño periods and upwelling (Broekhuizen et al. 2002). SST patterns have been steady
over a 20-year period, but cooler than average in the region during the time frame of the analysis. Marginal changes
in thermal regimes can have profound effects on seabird populations as evidenced in the northwest Atlantic
(Montevecchi and Myers 1997), however, it remains to be seen if gannets in HG will be affected if a cooler regime
continues. In HG, similar to trends observed nationally in Australia and New Zealand (Bunce et al. 2002), gannets
populations may be stable and increasing. Variable wind patterns and ENSO periods notwithstanding in HG, suggest
it is possible that food is readily available and plentiful for them to remain in the area. Nonetheless, independent and
current census counts are necessary to contextualize a likely increasing trend in gannet populations in HG.
In terms of the prey field, New Zealand gannet diet is composed of pelagic fish and squid species,
predominantly, pilchard (Sardina spp.), anchovy (Engraulis spp.), saury (Scomberesox spp.), jack mackerel, squid
(Nototodarus spp.) and garfish (Belone spp.) (Wingham 1985; Robertson 1992; Machovsky-Capuska et al. 2011a, b;
Schuckard 2012). Anchovies are abundant throughout the Hauraki Gulf during spring and migrate seaward in winter
(Paulin et al. 1989). Peak abundance occurs in winter with high productivity leading to large schools of anchovies
often closely associated with pilchards, which are abundant during warmer, less productive periods (Lecomte et al.
Pilchards are susceptible to viral disease and are sensitive to climatically driven oceanographic conditions
(Whittington et al. 1997; Paul et al. 2001). Nonetheless, pilchards accounted for more than 50 % of the diet of
gannets at Port Phillip Bay between 1995-1998 (Bunce et al. 2002), 90 % of the diet of gannets at Farewell Spit
between 1995-2001, excluding 1996 that switched to anchovy due to a mass pilchard mortality (Shuckard et al.
2012), and were the most abundant prey species found in the diet of gannets in the HG between 1979-1980
(Wingham 1985; Robertson 1992). The absence of pilchards as a primary food source is attributed to be a major
factor for the biggest crash in gannet populations ever recorded in New Zealand including at the Farewell Spit
colony where hundreds of birds were found dead in 1996 (Schuckard et al. 2012).
Pilchards (also known as sardines) have a preference for warm waters (Neumann 2001; Chavez et al.
2003), but remain tolerant to a wide range of temperatures, with spawning occurring between 13.5 and 25 ºC as
determined in Pacific sardines (Lluch-Belda et al. 1992). Thus, the marginally cooler SSTs recorded in the HG
region may still be optimum for pilchard spawning, although recruitment and productivity levels in these waters are
unknown. The East Auckland Current and shelf upwelling, along with tidal changes drive circulation patterns
interact to affect nutrient production in the Gulf, which is further influenced by ENSO patterns and Interdecadal
Pacific Oscillations (IPO) (Zeldis et al. 2004). So, lack of upwelling may have an impact on pilchard/anchovy
populations, with further investigations necessary to see how prey availability is linked with gannet population
The advantages of opportunistic datasets are that they are continuous both in terms of effort and temporal
scales particularly involving commercial operations. The standalone scientific value of these datasets cannot be
discounted. For example, Williams et al. (2006) demonstrated that it is possible to estimate marine mammal
abundance from non-randomized opportunistic surveys and be potentially used in management decision-making.
Fisheries observers on commercial fishing operations in the USA are one of the primary sources of marine mammal
by-catch information, which is utilized in marine mammal stock assessments by the US National Marine Fisheries
Service ( Conversely, exclusive reliance on opportunistic data can lead to
erroneous conclusions about abundance and distribution patterns due to incomplete coverage of study area and
selective or improper data gathering.
Nevertheless, in areas where research efforts are limited or where adequate funding is lacking, we propose
that long-term non-systematic survey results, if properly collected and analyzed, can be a valuable tool to address a
variety of marine conservation problems, including discerning probable effects of regional and global climate
variability on living marine resources.
In the present study, our interpretation and analysis would be significantly improved by including key
metrics such as abundance and presence/absence information. Synthesis studies involving analysis of multiple
species and their response to climate or oceanographic change would enhance our understanding of climate impacts
within ecosystems. We further need to understand the interactive effects of climate-ecosystem variables and human
impacts on seabird population dynamics to be able to forecast with increased certainty population responses to
climate change (Jenouvrier 2013). Also, since seabirds are significant ecological links between the land and the sea,
changes in breeding sites and gannet vital rates are important considerations. Future studies should use multiple data
streams from both systematic and non-systematic work to better understand and predict gannet responsiveness to
oceanographic and climate variability at regional scales.
We acknowledge the management and the crew of Dolphin Explorer, Auckland Whale and Dolphin Safaris
and the New Zealand Department of Conservation for providing an opportunistic observation platform and for
making accessible historical datasets on request. We thank E. Libby for helpful comments on early versions of the
manuscript and acknowledge R. Murtugudde (Earth System Science Interdisciplinary Centre, ESSIC, University of
Maryland) and Jim Beuchamp (ESSIC) for useful reviews that greatly improved the manuscript. Special thanks to J.
Beauchamp (ESSIC) for acquisition of SODA and MODIS datasets. Aspects of this research were funded by the
Massey University Research Fund (MURF). Special thanks to anonymous reviewers whose suggestions greatly
improved the manuscript.
Amélineau, F, Péron C., Lescroël A, Authier M, Provost P Grémillet D (2014) Windscape and tortuosity shape the
flight costs of northern gannets. J Exp Biol 217, 876-885
Ainley DG, Blight LK (2009) Ecological repercussions of historical fish extraction from the Southern Ocean. Fish
Fish 10:13-38
Aquaculture New Zealand Levy Production (2010) Major aquaculture areas in New Zealand. Aquaculture New
Zealand. Accessed from
Ballance L, Pitman RL, Hewitt RP, Siniff DB, Trivelpiece WZ, Clapham PJ, Brownell RL Jr (2006) The removal of
large whales from the Southern Ocean: evidence for long-term ecosystem effects? Whales, Whaling and
Ocean Ecosystems, University of California Press, Berkeley
Broekhuizen N, Zeldis J, Stephens SA, Oldman JW, Ross AH, Ren J, James MR (2002) Factors related to the
sustainability of shellfish aquaculture operations in the Firth of Thames: a preliminary analysis. Auckland
Regional Council, Auckland N.Z
Bunce A, Norman F, Brothers N, Gales, R (2002) Long-term trends in the Australasian gannet (Morus serrator)
population in Australia: the effect of climate change and commercial fisheries. Mar Biol 141:263-269
Burthe S, Daunt F, Butler A, Elston DA, Frederiksen M, Johns D, Wanless S (2012) Phenological trends and trophic
mismatch across multiple levels of a North Sea pelagic food web. Mar Ecol Prog Ser 454:119-133
Carton JA, Chepurin GA, Cao X, Giese BS (2000a) A Simple Ocean Data Assimilation analysis of the global upper
ocean 1950-95. Part I: Methodology. JPO 30:294-309
Carton JA, Chepurin GA, Cao X, Giese BS (2000b) A Simple Ocean Data Assimilation analysis of the global upper
ocean 1950-95. Part II: Results. JPO 30:311-326
Chambers LE, Devney CA, Congdon BC, Dunlop N, Woehler EJ, Dann P (2011) Observed and predicted effects of
climate on Australian seabirds. Emu 111:235-251
Chambers L, Hobday A, Arnould J, Patterson T, Tuck G, Wilcox C (2012) Seabird and marine mammal
management options in the face of climate change. In NCCARF/CSIRO 2012: Sharing knowledge to adapt:
Proceedings of Climate Adaptation in Action 2012 (pp. 85-85). National Climate Change Adaptation
Research Facility (NCCARF)
Chambers LE, Beaumont LJ, Hudson IL (2013) Continental scale analysis of bird migration timing: influences of
climate and life history traitsa generalized mixture model clustering and discriminant approach. Int J
biometeorol. doi:10.1007/s00484-013-0707-2
Chavez FP, Ryan J, Lluch-Cota SE, Ñiquen M (2003) From anchovies to sardines and back: multidecadal change in
the Pacific Ocean. Science 299:217-221
Dann P, Arnould JPY, Jessop R, Healy M (2003) Distribution and abundance of seabirds in Western Port, Victoria.
Emu 103:307-313
Doney SC, Ruckelshaus M, Duffy JE, Barry JP, Chan F, English CA, Galindo HM (2012) Climate change impacts
on marine ecosystems. Annu Rev Mar Sci 4:11-37
Furness RW, Camphuysen KC (1997) Seabirds as monitors of the marine environment. ICES J Mar Sci 54:726-737
Gaskin CP, Rayner MJ (2013) Seabirds of the HG: Natural History, Research and Conservation. Hauraki Gulf
Forum. Strategic Plan.
Heath RA (1985) A review of the physical oceanography of the seas around New Zealand1982. New Zeal J Mar
Fresh 9:79-124
Hobday, AJ, Young JW., Abe O, Costa DP, Cowen RK., Evans K., Gasalla MA., Kloser R, Maury O, Weng, KC
(2013) Climate Impacts and Oceanic Top Predators: Moving from impacts to adaptation in oceanic
systems. Reviews in Fis Biol and Fish
Hoffman W, Heinemann D, Wiens JA (1981) The ecology of seabird feeding flocks in Alaska. Auk 98:437-456
Hollowed AB, Barange M, Beamish RJ, Brander K, Cochrane K, Drinkwater K, Foreman MGG (2013) Projected
impacts of climate change on marine fish and fisheries. ICES J Mar Sci 5:1023-1037
IPCC (2013) Fifth assessment report. Stockholm: Inter-governmental Panel on Climate Change, Cambridge:
Cambridge University Press; Available from:
Ito A, Ichii K, Kato T (2010) Spatial and temporal patterns of soil respiration over the Japanese Archipelago: a
model intercomparison study. Ecol Res 25:1033-1044
Jenouvrier S (2013) Impacts of climate change on avian populations. Global Change Biol 19:2036-2057
Kendrick TH, Francis MP (2002) Fish assemblages in the HG, New Zealand. New Zeal J Mar Fresh 36:699-717
Lack D (1968) Ecological adaptations for breeding in birds. London: Methuen
Lecomte F, Grant WS, Dodson JJ, Rodriguez-Sanchez R, Bowen BW (2004) Living with uncertainty: genetic
imprints of climate shifts in East Pacific anchovy (Engraulis mordax) and sardine (Sardinops sagax). Mol
Ecol 13:2169-2182
Lluch-Belda D, Lluch-Cota DB, Hernández-Vázquez S, Salinas-Zavala CA (1992) Sardine population expansion in
eastern boundary systems of the Pacific Ocean as related to sea surface temperature. S Afr J Marine Sci
Machovsky-Capuska GE, Vaughn RL, Würsig B, Katzir G, Raubenheimer D (2011a) Dive strategies and foraging
effort in the Australasian gannet Morus serrator revealed by underwater videography. Mar Ecol Prog Ser,
Machovsky-Capuska GE, Dwyer SL, Alley MR, Stockin KA, Raubenheimer D (2011b) Evidence for fatal
collisions and kleptoparasitism while plunge-diving in Gannets. IBIS 153:631-635
Machovsky-Capuska GE, Hauber ME, Dassis M, Libby E, Wikelski MC, Schuckard R, Melville D, Cook W,
Houston M, Raubenheimer D (2013a) Foraging behaviour and habitat use of chick-rearing Australasian
Gannets in New Zealand. J Ornithol, 155: 379-387
Machovsky-Capuska GE, Vaughn-Hirshorn RL, Würsig B, Raubenheimer D (2013b) Can gannets define their
diving profile prior to submergence? Notornis 60:255-257
Machovsky-Capuska GE, Hauber ME, Libby E, Amiot C, Raubenheimer D (2014) The contribution of private and
public information in foraging by Australasian gannets. Anim Cogn 17:849-858
Mills JA, Yarrall JW, BradfordGrieve JM, Uddstrom MJ, Renwick JA, Merilä J (2008) The impact of climate
fluctuation on food availability and reproductive performance of the planktivorous redbilled gull Larus
novaehollandiae scopulinus. J Anim Ecol, 77:1129-1142
Montevecchi WA, Myers RA (1997). Centurial and decadal oceanographic influences on changes in Northern
Gannet populations and diets in the Northwest Atlantic: Implications for climatic change. ICES J. of Mar.
Sc. 54: 608-614.
Nelson JB (2005) Pelicans, cormorants and their relatives. Oxford University Press, Oxford
Neumann DR (2001) Activity budget of free-ranging common dolphins (Delphinus delphis) in the northwestern Bay
of Plenty, New Zealand. Aquat Mamm 27:121-136
Norman FI (2000) Preliminary investigation of the bycatch of marine birds and mammals in inshore commercial
fisheries, Victoria, Australia. Biol Conserv 92:217-226
Paul LJ, Taylor PR, Parkinson DM (2001) Pilchard (Sardinops neopilchardus) biology and fisheries in New
Zealand, and a review of pilchard (Sardinops, Sardina) biology, fisheries, and research in the main world
fisheries. New Zealand Fisheries Assessment Report 200U37
Paulin C, Stewart A, Roberts C. McMillan P (1989) New Zealand Fish. A complete guide. National Museum of
New Zealand Miscellaneous Series No.19
Quillfeldt P, Masello JF (2013) Impacts of climate variation and potential effects of climate change on South
American seabirdsa review. Mar Biol Res 9:337-357
R Core Team (2014) R: A language and environment for statistical computing. R Foundation for Statistical
Computing, Vienna, Austria. URL
Renwick J, Thompson D (2006) The Southern Annular Mode and the New Zealand climate. Wat and Atm14(2) 24-
Robertson D (1992) Diet of the Australasian gannet Morus serrator (G.R. Gray) around New Zealand. New Zeal J
Ecol 16: 77-81
Schreiber RW, Schreiber EA (1984) Central Pacific seabirds and the El Nino Southern Oscillation: 1982 to 1983
perspectives. Science 225:713716
Schuckard R, Melville D, Cook W, Machovsky-Capuska GE (2012) Diet of the Australasian gannet (Morus
serrator) at Farewell Spit, New Zealand. Notornis 59:6670
Stockin KA, Lusseau D, Binedell V, Wiseman N, Orams MB (2008a) Tourism affects the behavioural budget of the
common dolphin (Delphinus sp.) in the HG, New Zealand. Mar Ecol Prog Ser 355:287-295
Stockin KA, Pierce GJ, Binedell V, Wiseman N, Orams MB (2008b) Factors affecting the occurrence and
demographics of common dolphins (Delphinus sp.) in the HG, New Zealand. Aquat Mamm 34:200-211
Stockin KA, Orams MB (2009) The status of common dolphins (Delphinus delphis) within New Zealand waters. J
Cetacean Res Manage SC/61/SM20
Stockin KA, Binedell V, Wiseman N, Brunton DH, Orams MB (2009) Behavior of freeranging common dolphins
(Delphinus sp.) in the HG, New Zealand. Mar Mammal Sci 25:283-301
Stenseth NC, Mysterud A, Ottersen G, Hurrell JW, Chan KS, Lima M (2002) Ecological effects of climate
fluctuations. Science 297:1292-1296
Sydeman WJ, Thompson SA, Kitaysky A (2012) Seabirds and climate change: roadmap for the future. Mar Ecol
Prog Ser 454:107-117
Tait A, Raubenheimer D, Stockin KA, Merriman M, Machovsky-Capuska GE (2014) Nutritional geometry of
gannets and the challenges in field studies. Mar Biol 12: 2791-2801
Tillinger D, Gordon AL (2010) Transport weighted temperature and internal energy transport of Indonesian
throughflow. Dynam Atmos Oceans 50:224:232
Trenberth KE, Shea DJ (1987) On the evolution of the Southern Oscillation. Mon Weather Rev 115:3078-3096
Wang G, Cai W (2013) Climate-change impact on the 20th-century relationship between the Southern Annular
Mode and global mean temperature. Sci Rep 3:2039
Weimerskirch, H., Louzao M, de Grissac S, Delord K. (2012). Changes in wind pattern alter albatross distribution
and life-history traits. Sci335: 211-214.
Whittington RJ, Jones JB, Hine PM, Hyatt AD (1997) Epizootic mortality in the pilchard Sardinops sagax
neopilchardus in Australia and New Zealand in 1995. 1. Pathology and epizootiology. Dis Aquat Organ 28:
Wingham EJ (1985) Food and feeding range of the Australasian Gannet Morus serrator (Gray). Emu 85:1-239
Wingham EJ (1989) Energy Requirements of Australasian Gannets Morus serrator (Gray) at a Breeding Colony.
Emu 89:65-89
Wiseman N, Parsons S, Stockin KA, Baker CS (2011) Seasonal occurrence and distribution of Bryde's whales in the
HG, New Zealand. Mar Mammal Sci 27:E253-E267
Williams, R, Hedley, SL Hammond PS (2006). Modeling distribution and abundance of Antarctic baleen whales
using ships of opportunity. Ecol. and Soc. 11(1):1
Wodzicki KA, Robertson CJR, Thompson HR, Alderton CJT (1984) The distribution and number of gannets (Sula
serrator) in New Zealand. Notornis 31:232-261
Zeldis JR, Walters RA, Greig MJN, Image K (2004) Circulation over the northeastern New Zealand continental
slope, shelf and adjacent HG, from spring to summer. Cont Shelf Res 24:543-561
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Table 1. Lagged multiple regression model outputs wherein GSPUE is assumed to be linear function of historic lags
(in months) for the following climate variables with significant coefficients: Wcube = cube of wind speed,
WcubeAno = cube of wind speed anomaly, Mvel = meridional wind velocity, SOIAno = Southern Oscillation Index
anomaly, and SAM =Southern Annular Mode
Model = GSPUE ~ SOIAnolag1 + SOIAnolag2 + SOIAnolag3 + SOIAnolag5
Coeffici ents: Coeffi ci ents:
Estimate Std. Error t value Pr(>|t|) Estimate Std. Error t value Pr(>|t|)
Wcubelag3 0.0005 0.0002 2.223 0.02 9 * SOIAnol ag1 0.019 0.02 70 0.71 0 0.480
Wcubelag7 0.0005 0.0003 2.064 0.04 21 * SOI Anola g2 0.057 0.0280 2.086 0.040 *
Wcubelag9 0.0008 0.0003 2.766 0.00 7 ** SOIAnol ag3 0.028 0.02 93 0.96 3 0.339
*** 0.001 ** 0.01 * 0.05 SOIAnol ag5 0.001 0.02 8 0.038 0.970
Multi pl e R-squa red=0.15 Adjusted R-squared=0.12 *** 0.001 * 0.05
F = 5.197 on 3 and 86 df, p = 0.002 Multi pl e R-squa red=0.12, Adjus ted R-squa red=0.08
F= 3.108 on 4 and 89 df, p = 0.019
Model = GSPUE ~ SAMlag5 + SAMlag7
Coeffici ents: Coeffi ci ents:
Estimate Std. Error t value Pr(>|t|) Estimate Std. Error t value Pr(>|t|)
WcubeAnola g2 0.0004 0.0003 1.263 0.210 SAMla g5 0.071 0.035 2.048 0.044 *
WcubeAnola g3 0.0006 0.0003 1.979 0.051 SAMlag7 0.060 0.036 1.669 0.099
WcubeAnolag7 0 .0007 0.0003 2.255 0.027 * *** 0.001 * 0.05
WcubeAnolag9 0 .0008 0.0003 2.483 0.015 * Multi pl e R-squa red= 0.09, Adjus ted R-squa red=.07
*** 0.001 * 0.05 F = 4.172 on 2 and 89 df, p = 0.019
Multi pl e R-squa red=0.19, Adjus ted R-squa red=0.15
F= 4.999 on 4 and 85 df, p = 0.001
Model = GSPUE ~ MvelAnolag2 + MvelAnolag14
Coeffici ents: Coeffi ci ents:
Estimate Std. Error t value Pr(>|t|) Estimate Std. Error t value Pr(>|t|)
Mvellag2 -0.07 0 0.027 -2.583 0 .0116 * MvelAnol ag2 -0.092 0.02 9 -3.258 0.002**
Mvellag8 -0.04 3 0.026 -1.687 0 .096 MvelAnola g14 -0.097 0.028 -3.527 0.001 ***
Mvellag14 -0 .075 0.02 7 -2.834 0.006 ** *** 0.001 ** 0.01
*** 0.001 ** 0.01 * 0.05
Multi pl e R-squa red= 0.15, Adjus ted R-squa red=0.12 Multi pl e R-squa red= 0.17, Adjus ted R-squa red=0.16
F= 4.885 on 3 and 81 df, p = 0.004 F= 8.835 on 2 and 82 df,p=0.000 3
Model: GSPUE ~ Wcubelag3 + Wcubelag7 + Wcubelag9
Model: GSPUE ~ Mvellag2 + Mvellag8 + Mvellag14
Model = GSPUE ~ WcubeAnolag2 + WcubeAnolag3 +
WcubeAnolag7 + WcubeAnolag9
We identified links between Gannet Sightings Per Unit Effort (GSPUE) and climate variability.
GSPUE was linked with regional Sea Surface Temperature anomaly and regional climate indices.
We identified potential climate variables with capacity to forecast future GSPUE.
Despite inter-annual variability on SSTs gannet sightings appeared to be increasing.
We demonstrate the scientific value of non-systematic data in climate impact studies on seabirds.
... Surrounded by the Auckland region, the Hauraki Plains, the Coromandel Peninsula, and Great Barrier Island, this semi-enclosed body of water is riddled with islands and shallow reefs that extend into waters of the western Pacific Ocean. Water circulation in the gulf is primarily driven by tides and wind (Heath, 1985;Gaskin and Rayner, 2013) and, accordingly, has historically been an area of high primary productivity (Zeldis et al., 2004), subject to large environmental fluctuations (Srinivasan et al., 2015). ...
... Interactions between marine apex predators may have a significant role on the structuring and functioning of their communities (Ritchie and Johnson, 2009;Baum and Worm, 2009). Given that both dolphins and gannets play a key role in driving ecological interactions Machovsky-Capuska et al., 2016b) and serve as bio-monitor species (Srinivasan et al., 2015;Stockin et al., 2021a, b), an understanding of the extent of these relations and their ecological role, is important to preserve healthy marine ecosystems. Our study provides nutritional and ethological perspectives, that reveal how foraging strategies of dolphins shape these multispecies interactions while feeding on patchily distributed marine prey. ...
... The use of a commercial tourism catamaran as a platform of opportunity to collect such behavioural data further adds to the challenge. Nonetheless, historical studies from this same platform have a well-established value to address scientific questions on free-ranging marine predators related to their behavioural ecology (de la Brosse, 2010;Meissner et al., 2015;Purvin, 2015;Gostischa et al., 2021) and the influence of climate change in their habitat use (Srinivasan et al., 2015), among others. While the use of an opportunistic platform can present several trade-offs (Hupman et al., 2014) we are confident that our sampling regime had sufficient resolution to support the mutualistic nature of the foraging interactions between free ranging dolphin and gannets. ...
Full-text available
Prey detection and subsequent capture is considered a major hypothesis to explain feeding associations between common dolphins and Australasian gannets. However, a current lack of insight on nutritional strategies with respect to foraging behaviours of both species has until now, prevented any detailed understanding of this conspecific relationship. Here we combine stomach content analysis (SCA), nutritional composition of prey, a multidimensional nutritional niche framework (MNNF) and videography to provide a holistic dietary, nutritional, and behavioural assessment of the feeding association between dolphins and gannets in the Hauraki Gulf, New Zealand. Dolphins consumed ten prey species, including grey mullet (Mugil cephalus) as the most representative by wet mass (33.4%). Gannets preyed upon six species, with pilchards (Sardinops pilchardus) contributing most of the diet by wet mass (32.4%) to their diet. Both predators jointly preyed upon pilchard, jack mackerel (Trachurus spp.), arrow squid (genus Nototodarus), and anchovy (Engraulis australis). Accordingly, the MNNF revealed a moderate overlap in the prey composition niche (0.42) and realized nutritional niche (0.52) between dolphins and gannets. This suggests that both predators coexist in a similar nutritional space, while simultaneously reducing interspecific competition and maximizing the success of both encountering and exploiting patchily distributed prey. Behavioural analysis further indicated that dolphin and gannets feeding associations are likely to be mutually beneficial, with a carouselling foraging strategy and larger pod sizes of dolphins, influencing the diving altitude of gannets. Our approach provides a new, more holistic understanding of this iconic foraging relationship, which until now has been poorly understood.
... The Australasian gannet (Morus serrator) is an important marine predator in southeastern Australia and New Zealand [38,39], with an estimated annual consumption of 228.2 tons of schooling pelagic fish (e.g. Australian sardine Sardinops sagax, barracouta Thyrsites atun and blue mackerel Scomber australasicus) in Australian waters alone [40]. ...
Full-text available
Foraging is a behaviour that can be influenced by multiple factors and is highly plastic. Recent studies have shown consistency in individual foraging behaviour has serious ecological and evolutionary implications within species and populations. Such information is crucial to understand how species select habitats, and how such selection might allow them to adapt to the environmental changes they face. Five foraging metrics (maximum distance from the colony, bearing from the colony to the most distal point, tortuosity index, total number of dives and mean vectorial dynamic body acceleration were obtained using GPS tracking and accelerometry data in adult Australasian gannets (Morus serrator) from two colonies in southeastern Australia. Individuals were instrumented over two breeding seasons to obtain data to assess factors influencing foraging behaviour and behavioural consistency over multiple timescales (consecutive trips, breeding stages and years) and habitats (pelagic, mixed pelagic and inshore, and inshore). Colony, breeding stage and year were the factors which had the greatest influence on foraging behaviour, followed by sex. Behavioural consistency, measured as the contribution of the individual to the observed variance, was low to moderate for all foraging metrics (0.0-27.05%), with the higher values occurring over shorter timescales. In addition, behavioural consistency was driven by spatio-temporal factors rather than intrinsic characteristics. Behavioural consistency was higher in individuals foraging in inshore than pelagic habitats or mixed pelagic/inshore strategy, supporting suggestions that consistency is favoured in stable environments.
... The challenges faced by foragers in marine environments are particularity complex. Within these habitats, foods may be especially sparse and patchily distributed and are subject to oceanic and climatic fluctuations, as well as additional human pressures (Norman 2000;Hobday et al. 2013;Srinivasan et al. 2015). Drastic shifts in climate-related regimes are believed to be responsible for the decrease in availability of high-quality prey species (in terms of energy and lipid contents) and an increase in lowquality foods, which has negatively influenced marine predator populations around the world (Österblom et al. 2008). ...
Full-text available
The foraging challenge for predators is to find and capture food with adequate levels of energy and nutrients. Marine predators require particularly sophisticated foraging strategies that enable them to balance self- and offspring-feeding, and also in many circumstances simultaneously consider the nutritional constraints of their partners. Here we combined the use of dietary analysis, proximate composition and nutritional geometry (right-angled mixture triangle nutritional models) to examine the macronutrient preferences of Australasian gannets (Morus serrator) at Farewell Spit gannetry in New Zealand. Our results showed intra- and inter-specific variation in the protein, lipid and water composition of prey captured by our sample of 111 Australasian gannets. In addition, we observed significant differences in the Australasian gannets’ nutritional niche between seasons. We provide evidence of sex-specific macronutrient foraging strategies in a successful marine predator in the wild. We have shown that in spite of fluctuations in the nutritional composition of foods available to Australasian gannets, males consistently capture prey with higher protein-to-lipid ratios and lower lipid-to-water ratios than females. These results aid to better understand the evolutionary relationship between macronutrient selection and sex-specific traits in wild animals. They also suggest an incentive for these predators to combine individually imbalanced but nutritionally complementary foods to achieve dietary balance, further highlighting the likelihood that prey selection is guided by the balance of macronutrients, rather than energy alone.
... Based on observational studies, for example, gannet sightings per unit effort were weakly correlated to regional sea surface temperature (SST). SST, however, was predicted to have a limited impact prey abundance, particularly as a major prey item, pilchards (Sardinops spp.), were tolerant to a wide range of temperatures (Srinivasan et al. 2015). The timing and productivity of penguins is correlated with SST (Cullen et al. 2009). ...
Full-text available
The distribution, status and trends of grey-faced petrel (Pterodroma macroptera gouldi) populations are summarised from historical records from as early as the 1800’s, but predominantly over a 40 year period from the 1970’s and 1980’s to the present day. We tallied the most recent of 104 island population estimates to give a total range of 72,398-286,268 burrows over a minimum area of 37,967 ha. On predator-free islands (n = 9) during winter, the mean burrow occupancy rate was 60% (± 18 % SD). Fewer than 1000 burrows were detected from 20 mainland sites over an unspecified area. Implications for the conservation of this species are discussed.
While global climate change is impacting biota across the world, New Zealand’s maritime climate is highly variable and relatively mild, so climate change is sometimes seen as a minimal threat to species and ecosystems especially in comparison to the more immediate threat of invasive species. However, climate change will alter rainfall patterns, increase the incidence and severity of extreme events, and gradually increase temperatures which will all modify terrestrial, freshwater, and marine systems. Our comprehensive review of reported climate change impacts in New Zealand indicates that most measured impacts to date are due to indirect impacts (such as exacerbation of invasive species impacts) and most are in the marine realm. Ocean acidification and marine heatwaves are particularly problematic for calcareous organisms and algae respectively. Other notable impacts include thermal squeeze in the alpine zone and impacts of drought on freshwater fish. Very small populations of rare and threatened species can be very vulnerable to extreme events (e.g. fire, floods). While the evidence for climate change impacts is sparse in some regions and for some ecosystems, we encourage ongoing monitoring to identify processes of decline that may need to be mitigated. We identify five key research needs to improve our understanding of the threat of climate change to the biodiversity of Aotearoa New Zealand.
Full-text available
Information on animal abundance and distribution is at the cornerstone of many wildlife and conservation strategies. However, these data can be difficult and costly to obtain for cetacean species. The expense of sufficient ship time to conduct design-unbiased line transect surveys may be simply out of reach for researchers in many countries, which nonetheless grapple with problems of conservation of endangered species, by-catch of small cetaceans in commercial fisheries, and progression toward ecosystem-based fisheries management. Recently developed spatial modeling techniques show promise for estimating wildlife abundance using non-randomized surveys, but have yet to receive much field-testing in areas where designed surveys have also been conducted. Effort and sightings data were collected along 9 650 km of transects aboard ships of opportunity in the Southern Ocean during the austral summers of 2000-2001 and 2001-2002. Generalized additive models with generalized cross-validation were used to express heterogeneity of cetacean sightings as functions of spatial covariates. Models were used to map predicted densities and to estimate abundance of humpback, minke, and fin whales in the Drake Passage and along the Antarctic Peninsula. All species' distribution maps showed strong density gradients, which were robust to jackknife resampling when each of 14 trips was removed sequentially with replacement. Looped animations of model predictions of whale density illustrate uncertainty in distribution estimates in a way that is informative to non-scientists. The best abundance estimate for humpback whales was 1 829 (95% CI: 978-3 422). Abundance of fin whales was 4 487 (95% CI: 1 326-15 179) and minke whales was 1,544 (95% CI: 1,221-1,953). These estimates agreed roughly with those reported from a designed survey conducted in the region during the previous austral summer. These estimates assumed that all animals on the trackline were detected, but preliminary results suggest that any negative bias due to violation of this assumption was likely small. Similarly, current methodological limitations prohibit inclusion of all known sources of uncertainty in the favored variance estimator. Meanwhile, our approach can be seen generally as an inexpensive pilot study to identify areas of predicted high density that could be targeted to: inform stratified designs for future line transect surveys, making them less expensive and more precise; increase efficiency of future photo-identification or biopsy studies; identify candidate time-area fisheries closures to minimize by-catch; or direct ecotourism activities. The techniques are likely to apply to areas where funding is limiting, where cetacean studies or wilderness-based tourism are just beginning, or in regions where even a very rough estimate of animal abundance is needed for conservation or management purposes.
Full-text available
The diet of the Australasian gannet (Morus serrator) at Farewell Spit, New Zealand, was studied by the analysis of 70 regurgitations collected from the 1995 to 2001 breeding seasons. Surface schooling pilchard (Sardinops neopilchardus) was the main prey, followed by anchovy (Engraulis australis). The composition of the diet was similar in most seasons examined except in 1996 in which anchovy was the main prey item. Such a change in diet could be linked with a pilchard mass mortality in New Zealand in August 1995. The estimated annual prey consumption by birds at the Farewell Spit gannetry was 852 tonnes. Although annual catches of pilchard and anchovy by commercial fsheries in the area are still relatively small, an increase may interfere with prey availability, and in turn, increase competition between marine predators and infuence the breeding success. Our analyses of diet are consistent with previous studies showing that Australasian gannets as fexible foragers and they highlight their importance as bioindicators of fsh stocks in New Zealand.
Full-text available
Many studies have shown that seabirds are sensitive to changes in food supply, and therefore have potential as monitors of fish stocks. For most seabird species breeding parameters suitable for biomonitoring have yet to be measured over a wide range of prey densities. However, it is clear that responses vary among species and care must be taken when interpreting seabird data as a proxy for fish abundance. For many years seabirds have also been used as monitors of pollution, especially oil pollution. Beached bird surveys provide important evidence of geographical and temporal patterns, and, for example, show consistent declines in oil release into the southern North Sea over the last 15 years. Analysis of oil on birds can now permit fingerprinting of sources, allowing prosecution of polluters. As predators high in marine food webs, seabirds also have potential as monitors of pollutants that accumulate at trophic levels. Recent work on mercury in seabirds has permitted an analysis of spatial patterns and of the rates of increase in mercury contamination of ecosystems over the last 150 years, since mercury concentrations in feathers of museum specimens can be used to assess contamination in the birds when they were alive. Surprisingly, pelagic seabirds show higher increases than most coastal ones, and increases have been greatest in seabirds feeding on mesopelagic prey. This seems to relate to patterns of methylation of mercury in low-oxygen, deeper water. Accurate measurement of long-term trends in mercury contamination depend on the assumption that seabird diet composition has not changed. This can be assessed by analysis of stable isotopes of N and C from the same feathers used for mercury measurement, a technique that also permits the monitoring of trophic status over time or between regions. While high mercury contamination of seabirds in the southern North Sea is unsurprising, we cannot yet explain certain unexpected results, such as high levels in seabirds from north Iceland compared with those from south Iceland or Scotland.
The Australasian gannet (Morus serrator) population has increased considerably over the past century, both in New Zealand and Australia. Since 1980, the population in Australian waters has increased threefold, from 6,600 breeding pairs to approximately 20,000 pairs in 1999-2000, a rate of 6% per year. Reasons for the increase in the Australasian gannet population are poorly understood; here we consider the possible effects of recent fluctuations in climatic and oceanographic conditions, and changes in major local commercial fisheries. A significant trend towards more frequent, and stronger, El Niño Southern Oscillation events, warmer summer sea surface temperatures in Bass Strait, increased annual catches and catch per unit effort in the Victorian pilchard (Sardinops sagax) fishery and potential increased discarding of fisheries bycatch may account for at least some of the observed increase in the Australasian gannet population. The potential interactive effects of these factors on prey distribution and abundance and consequently on gannet numbers are discussed.
A brief history of the 26 breeding colonies and 23 roosts is given. Over 99% of gannets nested in the 23 colonies round the northern half of the North Island in 1980-81. Gannet roosts are mostly near the breeding colonies. The 1946-47 population was assessed at 21 115 pairs; 37 774 pairs were counted in 1969-70 and 46 004 in 1980-81. The mean annual rate of increase for the whole population between 1946-47 and 1980-81 was 2.3%. In comparison with gannets in Australia, South Africa, and the North Atlantic, the gannet in New Zealand seems to be the only one steadily increasing and free from human interference.-from Authors