Tracking Ocean Wanders (PDF, 5 MB) - BirdLife International

Tracking ocean wanderers: the global distribution of albatrosses and petrels
ANNEX 3 ALBATROSS TRACKING AND UTILISATION DISTRIBUTIONS FROM KERNELS
Introduction
The exploration of kernelling Royal Albatross data arose
because there were strong differences on methods of analysis
and the presentation of the results of satellite tracking. The
Workshop faces similar challenges. Our satellite telemetry
methodology differed between the various individuals
within the single species. The differences were intentional at
the time, but it requires careful analysis if we are to achieve
valid comparisons and summaries. These complications are
directly relevant to procedures combining datasets.
Definitions
The kernel is the shape placed over each observation. The
process of summing the kernels creates a measure of
abundance, either as a density, or the probability of
occurrence across the range.
Utilisation distribution is the grid or contour map of the
occurrence.
Home range is the area used by an animal in its normal
daily activities. Home range for an albatross that has
migrated to the other side of the world is arguably a
contradiction, so we used range.
Methods
The homogenous data set is of a single northern royal
albatross (abandoned breeding, migrated via the Pacific
Ocean to the Patagonian Shelf; bird was present from
March to 30 June, totalling 558 selected Argos locations;
transmission regime: on-period 25 hours, off-period 23
hours, i.e. exactly two days. The kernels, utilisations
distributions and maps were prepared in Animal
Movements Extension 2.0 in ESRI ArcView 3.2.).
Results
Smoothing produces different forms of the Utilisation
Distributions. The user must decide the form depending on
their hypothesis. There is no single choice, and no one other
than the user can decide. Different kinds of subsets of the
data do affect the range and Utilisation Distributions. These
differences may be deeply hidden in the data. We tested the
sample size and its effects on the area of the range. Small
samples underestimated the range, but indicated a measure
of by how much the range might be underestimated. It
cannot of course show the places where an underestimate
might be occurring.
Subsets
With subsets, such as day versus night, or, night, dawn, day,
dusk, accuracy of locations and speed, the area of the
ranges was close to the range area expected for the sample
size. However for transmission regime, or, for seasonal time
periods of the time spent on the Patagonian Shelf namely,
early, middle and late, the range areas emphatically did not
match the range for the complete data set.
Conclusions
Choosing the smoothing is subjective. The activity at hot
spots is speculative. Concentrations may only in a limited
sense indicate risk. Combining results and comparing maps
from different datasets, other than at the most superficial
levels, needs care but the exploration described here
provides methods to ensure valid use.
David Nicholls, Christopher Robertson
and Beat Naef-Daenzer
79