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Citation: Morimura, N.; Itahara, A.;
Brooks, J.; Mori, Y.; Piao, Y.;
Hashimoto, H.; Mizumoto, I. A
Drone Study of Sociality in the
Finless Porpoise Neophocaena
asiaeorientalis in the Ariake Sound,
Japan. Drones 2023,7, 422. https://
doi.org/10.3390/drones7070422
Academic Editors: Kate Brandis and
Roxane Francis
Received: 15 May 2023
Revised: 21 June 2023
Accepted: 23 June 2023
Published: 25 June 2023
Copyright: © 2023 by the authors.
Licensee MDPI, Basel, Switzerland.
This article is an open access article
distributed under the terms and
conditions of the Creative Commons
Attribution (CC BY) license (https://
creativecommons.org/licenses/by/
4.0/).
drones
Article
A Drone Study of Sociality in the Finless Porpoise
Neophocaena asiaeorientalis in the Ariake Sound, Japan
Naruki Morimura *, Akihiro Itahara, James Brooks, Yusuke Mori, Yige Piao, Hiroki Hashimoto and Itsuki Mizumoto
Wildlife Research Center, Kyoto University, 990 Ohtao, Misumi-machi, Uki 869-3201, Kumamoto, Japan;
itahara.akihiro.34n@st.kyoto-u.ac.jp (A.I.); jamesgerardbrooks@gmail.com (J.B.);
mori.yusuke.65r@st.kyoto-u.ac.jp (Y.M.); spoonasf@gmail.com (Y.P.); hirokihukuokaeco@icloud.com (H.H.);
itsukimizumoto@gmail.com (I.M.)
*Correspondence: morimura.naruki.5a@kyoto-u.ac.jp or naruki.morimura@gmail.com
Abstract:
The social structure of animal populations is a fundamental component of their biology, in-
fluencing gene flow, habitat use, competition and co-operation around resources, and communication.
However, ecological and social relationships can be challenging to describe in most marine mammals,
who spend the majority of their lives underwater. The finless porpoise (Neophocaena asiaeorientalis)
is one such cetacean species with a largely unknown social structure. Recent advances in drone
technology enable more systematic surveys, photogrammetry, and photo-identification for diverse
animal species. The present study aimed to validate new survey methods and provide a prelimi-
nary description of the spatiotemporal distribution of free-ranging finless porpoises in the coastal
open-sea area of Ariake Sound, Japan. A vertical take-off and landing (VTOL) drone equipped with
an action camera yielded GPS location datasets through line and area surveys, covering a total sea
area of 120 km
2
. The results suggest highly flexible and varied aggregation sizes in finless porpoises.
Distance analysis across individuals and aggregations revealed a cohesive tendency among groups,
compared to solitaries and in pairs. Therefore, the present VTOL drone surveys both elucidated
some social aspects of the study population and confirmed the efficacy of these standardized research
protocols involving automated, programmed, and repeatable flight missions.
Keywords: Neophocaena asiaeorientalis; UAVs; population distribution; sociality; group cohesion
1. Introduction
Knowledge of the distribution and abundance of both terrestrial and marine mammals
is crucial for planning and evaluating conservation strategies. This knowledge informs
our understanding of intrinsic and extrinsic factors influencing species’ ecology, behavior,
and reproduction [
1
,
2
]. Body size, age, sex, life history, prey availability, predation risk,
and intraspecific competition could all be major influential factors on the distribution
of species [
3
]. Moreover, some species, such as African elephants, some primates, and
bottlenose dolphins, form social structures with fission–fusion societies, which can flexibly
respond to the dynamic interaction of ecological variables, such as resource availability
and predation risk [
4
–
6
]. For example, one previous study [
4
] illuminated that the size
and presence of male alliances in a population of bottlenose dolphins (Tursiops aduncus
and Tursiops truncatus) were correlated with predation risk and population density factors.
Anthropogenic impacts, such as harvesting activity, fisheries by-catch, sound and other
forms of pollution, and disease, can also have significant impacts on the distribution of
marine mammals [
2
,
7
]. These studies illustrate that surveys of animal spatial distributions
are crucial for understanding species’ sociality, and, likewise, that understanding species’
sociality is necessary to make informed conservation and management decisions.
Unmanned aerial vehicles (UAVs), or drones, enable more systematic surveys, pho-
togrammetry, and photo-identification with unprecedented spatial and temporal resolu-
tions, alongside lower cost and greater operational flexibility than traditional methods
Drones 2023,7, 422. https://doi.org/10.3390/drones7070422 https://www.mdpi.com/journal/drones
Drones 2023,7, 422 2 of 12
for wildlife research [
8
–
12
]. Cetacean observation using UAVs, for example, has major
advantages compared to standard ship-based surveys through preventing the negative
impacts of ship presence and noise on cetacean behavior patterns, activity budgets, and
group size [
13
]. Fixed-wing Vertical Take-Off and Landing (VTOL) drones, in particular,
can both perform flight missions from vessels or land without the need for extended takeoff
or landing runs, as well as fly over target species groups with greater range/duration com-
pared to multirotor drones. Ref. [
14
] point out that the ability to examine and review UAV
video recordings of whale behavior post-flight and away from the water facilitates more
accurate and trustworthy analyses of whale behavioral states, especially social behavior
and nursing.
The narrow-ridged finless porpoise (Neophocaena asiaeorientalis sunameri) is distributed
throughout the shallow (usually <50 m deep) coastal waters of Japan. It is small, endan-
gered, and has no dorsal fin, seriously reducing its visibility and, therefore, the feasibility
of detailed population monitoring from surface or vessel observations alone [
15
]. Their
behavioral repertoire and sociality in the wild are largely unknown. One study, which was
based on an aircraft survey, found that stable social bonds form at least between mothers
and calves [
16
]. Drone observations also revealed coincident diving of aggregated groups
of finless porpoises near boat traffic [
17
]. These studies suggest potentially substantial
undescribed sociality in the species.
Therefore, the present study surveyed the presence and distribution of finless por-
poises in the open-sea area of Ariake Sound. A VTOL drone with a camera and GPS device
collected location data, and we quantified distances between individuals and aggregations.
If stable social relationships are rare, individuals and aggregations of a few individuals
are expected to be sparsely distributed, with large inter-aggregation distances [
18
]. Con-
sidering feeding resources, such as prey-fish schools, occasionally attract many porpoises,
the distribution of aggregation sizes and inter-aggregation distances would, therefore, be
expected to be bimodally skewed [
19
]. In contrast, if stable social relationships are more
common, aggregation variables would be expected to vary more gradually from single
individuals to larger social groups. Therefore, the present study aimed to confirm the
efficacy of VTOL drone monitoring for this species and describe social aggregation patterns,
comparing the distributions of free-ranging individuals across a series of aerial surveys
with an automated protocol.
2. Materials and Methods
2.1. Study Area
Surveys were conducted in an area of 120 km
2
off the Japanese coast in the marine
waters of Ariake Sound (Figure 1) between June 2022 and January 2023. The launch location
for the VTOL drone was set at an off-limit area of 30 m
×
30 m at Ohtao Port (32
◦
38
0
23.4
00
N,
130◦28039.900 E).
2.2. Drone Use and Flight Routes
The presence/absence of finless porpoises at the sea surface was recorded using a
fixed-wing VTOL drone (makeflyeasy Co., Ltd., Fighter VTOL, Mianyang, China). The
aircraft was automatically controlled with the QGroundControl (ver. 4.2.0) for Android
OS (Dronecode Project, Inc.). Photographic data with GPS location were collected at 1-s
intervals throughout the flights, using the time-lapse function of GoPro Hero 5 (GoPro,
Inc.). The flight height of the drone was set at 149 m above sea level (ASL) throughout
all flights. A 90
◦
angle of view had an approximate area of 99 m by 74 m under these
conditions. All flights were conducted from 9 a.m. until 2 p.m. The presence and noise of
the aircraft had a limited impact on the animal’s surface behavior [
20
]. The observation
was repeated on a schedule but canceled in unsuitable weather conditions.
Drones 2023,7, 422 3 of 12
Drones 2023, 7, x FOR PEER REVIEW 3 of 13
Figure 1. The study area in Ariake Sound, Japan. Solid lines indicate the North, Yushima, and Area
ight routes on the Digital Map (Basic Geospatial Information) published by the Geospatial Infor-
mation Authority of Japan.
2.2. Drone Use and Flight Routes
The presence/absence of nless porpoises at the sea surface was recorded using a
xed-wing VTOL drone (makeyeasy Co., Ltd., Fighter VTOL, Mianyang, China). The
aircraft was automatically controlled with the QGroundControl (ver. 4.2.0) for Android
OS (Dronecode Project, Inc.). Photographic data with GPS location were collected at 1-
second intervals throughout the ights, using the time-lapse function of GoPro Hero 5
(GoPro, Inc.). The ight height of the drone was set at 149 m above sea level (ASL) through-
out all ights. A 90° angle of view had an approximate area of 99 m by 74 m under these
conditions. All ights were conducted from 9 a.m. until 2 p.m. The presence and noise of
the aircraft had a limited impact on the animal’s surface behavior [20]. The observation
was repeated on a schedule but canceled in unsuitable weather conditions.
The ight routes for the survey consisted of two line routes, namely the North and
Yushima routes, and a single area route (Figure 1). The North route was a straight ight
of 12 km from Ohtao Port to a turning point (32°43′53.4″ N, 130°33′04.8″ E) near the Ku-
mamoto Ferry Terminal. The Yushima route was another straight ight of 15 km from
Ohtao Port to a turning point (32°36′39.8″ N, 130°19′15.7″ E) near Yushima Island. The
area route covered coastal water of 6 km by 11 km surrounded by the coordinates of
32°37′28.4″ N 130°24′55.0″ E, 32°39′49.2″ N 130°22′24.5″ E, 32°43′23.4″ N 130°28′04.7″ E,
and 32°41′02.1″ N 130°30′35.6″ E. The aircraft repeated a 6-kilometer straight ight 12
times with a 1-kilometer-long interval from between the southern and northern ends. The
total ight length of the area route was 95 km. The turning point on the North route was
reduced to an 8-kilometer distance from the launch location, while maintaining the same
direction as the original route, because of the local shery activity and radio wave inter-
ference when approaching a high-density human population. The other two routes re-
mained constant throughout the surveys. All ights were monitored for surveillance by
authors based on land and boat.
2.3. Data Analysis
2.3.1. The Size of the Animal Aggregations
Aggregations were dened based on photo sequences and collected at 1-second in-
tervals. The ight speed was planned at 15 m/s throughout the survey (though the actual
speed varied according to wind conditions), which indicates that the sea area in the angle
of view had no overlap between photographs taken at a delay of ˃7 s. We, therefore, set a
threshold for characterizing individuals/aggregations as distinct when there was no ani-
mal detected over seven consecutive images. Individuals that appeared in multiple pho-
tographs were counted only once, and the number of individuals in each aggregation was
Figure 1.
The study area in Ariake Sound, Japan. Solid lines indicate the North, Yushima, and
Area flight routes on the Digital Map (Basic Geospatial Information) published by the Geospatial
Information Authority of Japan.
The flight routes for the survey consisted of two line routes, namely the North and
Yushima routes, and a single area route (Figure 1). The North route was a straight flight
of 12 km from Ohtao Port to a turning point (32
◦
43
0
53.4
00
N, 130
◦
33
0
04.8
00
E) near the
Kumamoto Ferry Terminal. The Yushima route was another straight flight of 15 km from
Ohtao Port to a turning point (32
◦
36
0
39.8
00
N, 130
◦
19
0
15.7
00
E) near Yushima Island. The
area route covered coastal water of 6 km by 11 km surrounded by the coordinates of
32
◦
37
0
28.4
00
N 130
◦
24
0
55.0
00
E, 32
◦
39
0
49.2
00
N 130
◦
22
0
24.5
00
E, 32
◦
43
0
23.4
00
N 130
◦
28
0
04.7
00
E,
and 32
◦
41
0
02.1
00
N 130
◦
30
0
35.6
00
E. The aircraft repeated a 6-km straight flight 12 times with
a 1-km-long interval from between the southern and northern ends. The total flight length
of the area route was 95 km. The turning point on the North route was reduced to an 8-km
distance from the launch location, while maintaining the same direction as the original
route, because of the local fishery activity and radio wave interference when approaching a
high-density human population. The other two routes remained constant throughout the
surveys. All flights were monitored for surveillance by authors based on land and boat.
2.3. Data Analysis
2.3.1. The Size of the Animal Aggregations
Aggregations were defined based on photo sequences and collected at 1-s intervals.
The flight speed was planned at 15 m/s throughout the survey (though the actual speed
varied according to wind conditions), which indicates that the sea area in the angle of view
had no overlap between photographs taken at a delay of >7 s. We, therefore, set a threshold
for characterizing individuals/aggregations as distinct when there was no animal detected
over seven consecutive images. Individuals that appeared in multiple photographs were
counted only once, and the number of individuals in each aggregation was also counted to
estimate the total number of individuals. Individual recognition was not feasible with this
survey method, and, therefore, some individuals might have been counted twice (especially
in the area survey). Water visibility during the study period was usually less than 2 m, but
varied depending on the weather and tide conditions.
2.3.2. Distances across Solitaries and Aggregations
The GPS location data for each individual and aggregation were collected from a
single photograph. When individuals or small aggregations were in captured in multiple
photographs, the location of the photograph with the individual or aggregation closest
to the center of the image was used. In the case of large aggregations spread out over
more than one image, the location was chosen as the photograph with the largest number
Drones 2023,7, 422 4 of 12
of individuals in a single image. Based on the location datasets, we quantified distances
between the single individuals, dyads, and aggregations observed in each flight.
2.4. Statistical Analysis
The numbers of finless porpoises and aggregation sizes were compared between the
line and area surveys to evaluate the performances along different flight routes using
a Welch two-sample t-test. The detection effort was operationally defined as the flight
distance per single individual detected, and the line and area surveys were compared using
Welch two-sample t-tests. To analyze seasonal differences throughout repeated sessions in
both surveys, the number of observed individuals was analyzed using Pearson’s product-
moment correlation. Moreover, the distances between distinct individuals and aggregations
were compared to explore a possible cohesive tendency using one-way analysis of variance
(ANOVA), followed by Bonferroni’s post hoc tests. Statistical tests were performed using R
statistical software, version 3.5.0 [
21
]. We considered values of p< 0.05 to be statistically
significant. The null hypothesis was that there would be no tendency for social cohesion.
3. Results
The presence/absence survey of finless porpoises was conducted for seven sessions
during the study period (Figure 2and Table 1). The numbers of finless porpoises in the
line (North and Yushima routes) and area surveys, on average (
±
standard error of the
mean [SEM]), were 9.6
±
2.5 individuals and 46.7
±
16.1 individuals (t=
−
2.28, df = 6.29,
p-value = 0.06
), respectively. The mean aggregation size, including solitaries, in the line
surveys was 1.3
±
0.1 individuals, whereas that of area surveys was 1.6
±
0.3 individuals
(
t=−0.62
,df = 7.93, p-value = 0.55). In both survey types, the distribution of the observed
individuals varied drastically between the seven sessions, indicating substantial variation
in finless porpoise distributions over time in the survey area. Moreover, the values of
detection effort, when defined operationally, were 12.8
±
5.7 km and 9.6
±
7.0 km in the
line and area surveys, respectively (t=
−
0.34, df = 9.68, p-value = 0.74). Thus, the line and
area surveys generally yielded quite similar detection and grouping patterns (Figure 3).
However, the observed number of individuals increased as the area surveys were repeated
from session #1 to #7 (r= 0.82, t
5
= 3.23, p-value = 0.02), although those figures in the line
surveys did not show such tendency (r= 0.57, t5= 1.62, p-value = 0.16).
Drones 2023, 7, x FOR PEER REVIEW 5 of 13
Figure 2. Enlarged sample picture of nless porpoises in the present study (taken during session
#6). Arrows indicate nless porpoises.
Table 1. Observation of conditions and performances for each session in the area and line surveys.
Start times in the line surveys indicate the North and Yushima routes, respectively.
A
B
Frequency of Aggregation Sizes (#Individuals)
Survey Type
-Session#
Start Time-Date
Route
Length
(km)
#Individuals
Detection
Eort
(A/B; km)
Mean
Aggregation
Size
#1
#2
#3
#4
#5
#6
#7
#8
#9
#16
#33
Area #01
10:56, 27 June 2022
95.0
29
3.3
1.9
6
6
1
2
Area #02
10:56, 4 August 2022
95.0
0
n/a
n/a
Area #03
10:40, 30 August 2022
95.0
27
3.5
1.4
14
5
1
Area #04
10:57, 22 September
2022
95.0
2
47.5
1.0
2
Area #05
10:17, 27 December
2022
95.0
74
1.3
1.9
18
12
3
4
1
Area #06
10:23, 6 January 2023
95.0
91
1.0
2.8
20
11
1
1
Area #07
10:20, 11 January
2023
95.0
104
0.9
2.1
25
12
6
1
2
1
1
1
Line #01
9:39 and 12:56, 27
June 2022
56.7
5
11.3
1.0
5
Line #02
9:41 and 12:56, 4 Au-
gust 2022
56.7
3
18.9
1.0
3
Line #03
9:43 and 12:36, 30
August 2022
56.7
11
5.2
1.4
6
1
1
Line #04
9:50 and 12:54, 22
September 2022
56.7
14
4.1
1.6
5
3
1
Line #05
9:35 and 12:21, 27 De-
cember 2022
44.4
1
44.4
1.0
1
Line #06
9:38 and 12:15, 6 Jan-
uary 2023
44.4
18
2.5
1.6
7
2
1
1
Line #07
9:34 and 12:28, 11 Jan-
uary 2023
44.4
15
3.0
1.9
3
3
2
Figure 2.
Enlarged sample picture of finless porpoises in the present study (taken during session #6).
Arrows indicate finless porpoises.
Drones 2023,7, 422 5 of 12
Table 1.
Observation of conditions and performances for each session in the area and line surveys. Start times in the line surveys indicate the North and Yushima
routes, respectively.
A B Frequency of Aggregation Sizes (#Individuals)
Survey Type
-Session# Start Time-Date
Route
Length
(km)
#Individuals
Detection
Effort
(A/B; km)
Mean
Aggregation
Size
#1 #2 #3 #4 #5 #6 #7 #8 #9 #16 #33
Area #01 10:56, 27 June 2022 95.0 29 3.3 1.9 6 6 1 2
Area #02 10:56, 4 August 2022 95.0 0 n/a n/a
Area #03 10:40, 30 August 2022 95.0 27 3.5 1.4 14 5 1
Area #04 10:57, 22 September 2022 95.0 2 47.5 1.0 2
Area #05 10:17, 27 December 2022 95.0 74 1.3 1.9 18 12 3 4 1
Area #06 10:23, 6 January 2023 95.0 91 1.0 2.8 20 11 1 1
Area #07 10:20, 11 January 2023 95.0 104 0.9 2.1 25 12 6 1 2 1 1 1
Line #01 9:39 and 12:56, 27 June 2022 56.7 5 11.3 1.0 5
Line #02 9:41 and 12:56, 4 August 2022 56.7 3 18.9 1.0 3
Line #03 9:43 and 12:36, 30 August 2022 56.7 11 5.2 1.4 6 1 1
Line #04 9:50 and 12:54, 22 September 2022 56.7 14 4.1 1.6 5 3 1
Line #05 9:35 and 12:21, 27 December 2022 44.4 1 44.4 1.0 1
Line #06 9:38 and 12:15, 6 January 2023 44.4 18 2.5 1.6 7 2 1 1
Line #07 9:34 and 12:28, 11 January 2023 44.4 15 3.0 1.9 3 3 2
Drones 2023,7, 422 6 of 12
Drones 2023, 7, x FOR PEER REVIEW 6 of 13
Figure 3. Comparisons of the average number of individuals (bar chart) and detection eorts (line
chart; mean ± SEM) between the area and line surveys.
The area survey claried the spatiotemporal distribution characteristics of nless
porpoises on the sea surface in the study area (Figure 4). Solitaries and various sizes of
aggregations widely appeared across the survey area. In sessions #1, #3, #5, and #7, the
aggregation sizes varied gradually between one and nine individuals (Table 1). In contrast,
in session #6, we observed over 50 individuals in relatively close proximity, segregating
some as single individuals and some as aggregations (of 2, 16, and 33 individuals). Nota-
bly, no prey-sh school was observed on this occasion. Only solitary individuals and pairs
were observed on the rest of the survey route in that session, suggesting that the distribu-
tion of aggregation sizes was bimodally skewed to extremely large and small values on
this day. Thus, both possible distribution paerns described in the introduction were ob-
served, on dierent days, over the course of the seven area survey sessions (Table 1 and
Figure 4). In sessions #2 and #4, few individuals were observed, i.e., zero and two, respec-
tively.
For the size frequency of aggregations in the area surveys (N = 157), solitaries were
the most common (54.1%), followed by pairs (29.3%) and three individuals (7.0%), with
decreasing proportions (Figure 5a). Solitary individuals and pairs were, therefore, the
most common group size observed. Contrastingly, by focusing on the number of individ-
uals (N = 327), the proportion of solitary individuals reduced to 26.0%, indicating that the
majority of observed nless porpoises (N = 242) belonged to some type of aggregation
(Figure 5b). We focused on the area surveys for these aggregation size analyses, as only
six aggregations with more than three individuals were observed in the line surveys. Vis-
ual comparison of the aggregation distribution between the line and area surveys revealed
a similar overall tendency, where the observed aggregation sizes varied with decreasing
frequency from single individuals to larger social groups. In both survey types, the most
common grouping size was solitary, though the majority of individual porpoises were
observed in aggregations (Figure 6).
0.0
10.0
20.0
30.0
0
10
20
30
40
50
Area Line
Detection effort (km)
#Individual
Type of survey
Figure 3.
Comparisons of the average number of individuals (bar chart) and detection efforts (line
chart; mean ±SEM) between the area and line surveys.
The area survey clarified the spatiotemporal distribution characteristics of finless
porpoises on the sea surface in the study area (Figure 4). Solitaries and various sizes of
aggregations widely appeared across the survey area. In sessions #1, #3, #5, and #7, the
aggregation sizes varied gradually between one and nine individuals (Table 1). In contrast,
in session #6, we observed over 50 individuals in relatively close proximity, segregating
some as single individuals and some as aggregations (of 2, 16, and 33 individuals). Notably,
no prey-fish school was observed on this occasion. Only solitary individuals and pairs were
observed on the rest of the survey route in that session, suggesting that the distribution of
aggregation sizes was bimodally skewed to extremely large and small values on this day.
Thus, both possible distribution patterns described in the introduction were observed, on
different days, over the course of the seven area survey sessions (Table 1and Figure 4). In
sessions #2 and #4, few individuals were observed, i.e., zero and two, respectively.
For the size frequency of aggregations in the area surveys (N = 157), solitaries were
the most common (54.1%), followed by pairs (29.3%) and three individuals (7.0%), with
decreasing proportions (Figure 5a). Solitary individuals and pairs were, therefore, the most
common group size observed. Contrastingly, by focusing on the number of individuals
(N = 327), the proportion of solitary individuals reduced to 26.0%, indicating that the
majority of observed finless porpoises (N = 242) belonged to some type of aggregation
(Figure 5b). We focused on the area surveys for these aggregation size analyses, as only six
aggregations with more than three individuals were observed in the line surveys. Visual
comparison of the aggregation distribution between the line and area surveys revealed
a similar overall tendency, where the observed aggregation sizes varied with decreasing
frequency from single individuals to larger social groups. In both survey types, the most
common grouping size was solitary, though the majority of individual porpoises were
observed in aggregations (Figure 6).
Drones 2023,7, 422 7 of 12
Drones 2023, 7, x FOR PEER REVIEW 7 of 13
Figure 4. The distributions of solitaries and aggregations for each session in the area survey.
Heatmaps corresponding to the aggregation sizes and the numbers across sessions are drawn on
the satellite images of © OpenStreetMap. No individual was observed in session #2.
Figure 5. Proportions (%) of aggregation size frequency (a) and individual numbers (b) belonging
to solitaries and aggregations of 2, 3, 4, 5, and ≥6 individuals in the area surveys.
Solitary
Pair
3
4
5
6−33
a)
Solitary
Pair
3
4
5
6−33
b)
Figure 4.
The distributions of solitaries and aggregations for each session in the area survey.
Heatmaps corresponding to the aggregation sizes and the numbers across sessions are drawn on the
satellite images of © OpenStreetMap. No individual was observed in session #2.
Drones 2023, 7, x FOR PEER REVIEW 7 of 13
Figure 4. The distributions of solitaries and aggregations for each session in the area survey.
Heatmaps corresponding to the aggregation sizes and the numbers across sessions are drawn on
the satellite images of © OpenStreetMap. No individual was observed in session #2.
Figure 5. Proportions (%) of aggregation size frequency (a) and individual numbers (b) belonging
to solitaries and aggregations of 2, 3, 4, 5, and ≥6 individuals in the area surveys.
Solitary
Pair
3
4
5
6−33
a)
Solitary
Pair
3
4
5
6−33
b)
Figure 5.
Proportions (%) of aggregation size frequency (
a
) and individual numbers (
b
) belonging to
solitaries and aggregations of 2, 3, 4, 5, and ≥6 individuals in the area surveys.
Drones 2023,7, 422 8 of 12
Drones 2023, 7, x FOR PEER REVIEW 8 of 13
Figure 6. Comparison of size frequency of aggregations between area (a) and line (b) surveys.
Inter-individual/aggregation distances can provide a basis for exploring characteris-
tics of sociality, such as social behavior, group structure, and cohesion [22,23]. The dis-
tances across all inter-individual/aggregation combinations in the area surveys were cal-
culated and compared. Observations were split into two types for comparison: singles and
pairs (the sprinkling type) and aggregations with more than three individuals (the group
type). Again, these analyses focused on the area surveys. The comparison revealed that
the group types were more closely distributed (Figure 7), whereas the sprinkling types
were relatively more dispersed throughout the survey area (one-way ANOVA; F2, 5403 =
52.90, p-value < 0.01). The mean distance across sprinkling-to-sprinkling types was 3581 ±
36.5 m, ranging from 18–10,857 m. The distance across sprinkling-to-group types was 3042
± 50.0 m, on average, ranging from 33–10,519 m, although that of group-to-group types
was the closest, being 2527 ± 104.0 m, on average, ranging from 31–5810 m. Thus, the
group types showed more cohesion than the sprinkling types (post hoc tests: the distances
of sprinkling-to-sprinkling vs. group-to-group, p < 0.01), indicating potentially distinct re-
lationships between the group types compared to sprinkling types.
0
5
10
15
20
25
30
12345678910 11 12 13
#Frequency
Aggregation size
S#01
S#02
S#03
S#04
S#05
S#06
S#07
Average
a)
16 33
0
1
2
3
4
5
6
7
8
1 2 3 4
#Frequency
Aggregation size
S#01
S#02
S#03
S#04
S#05
S#06
S#07
Average
b)
Figure 6. Comparison of size frequency of aggregations between area (a) and line (b) surveys.
Inter-individual/aggregation distances can provide a basis for exploring character-
istics of sociality, such as social behavior, group structure, and cohesion [
22
,
23
]. The
distances across all inter-individual/aggregation combinations in the area surveys were
calculated and compared. Observations were split into two types for comparison: sin-
gles and pairs (the sprinkling type) and aggregations with more than three individuals
(the group type). Again, these analyses focused on the area surveys. The comparison
revealed that the group types were more closely distributed (Figure 7), whereas the sprin-
kling types were relatively more dispersed throughout the survey area (one-way ANOVA;
F2, 5403 = 52.90
,
p-value < 0.01)
. The mean distance across sprinkling-to-sprinkling types
was
3581 ±36.5 m,
ranging from 18–10,857 m. The distance across sprinkling-to-group
types was
3042 ±50.0 m
, on average, ranging from 33–10,519 m, although that of group-to-
group types was the closest, being 2527
±
104.0 m, on average, ranging from 31–5810 m.
Thus, the group types showed more cohesion than the sprinkling types (post hoc tests: the
distances of sprinkling-to-sprinkling vs. group-to-group, p< 0.01), indicating potentially
distinct relationships between the group types compared to sprinkling types.
Drones 2023, 7, x FOR PEER REVIEW 9 of 13
Figure 7. Comparisons of distance-class distributions of group-to-group, group-to-sprinkling, and
sprinkling-to-sprinkling aggregations. The distance class was set at a 100-meter interval, with D000
representing the distance range from 0–99 m.
4. Discussion
The ndings of the present study highlight dynamic spatiotemporal variation in nar-
row-ridged nless porpoises’ distribution and provide novel data on both the total num-
ber of individuals and the frequencies of their aggregation in this area. Using a xed-wing
VTOL drone, comparison of distribution paerns in dierent time periods could be con-
ducted with automated and programmed ights over a total sea area of 120 km2. Those
methods claried that nless porpoises did form aggregations of a variety of sizes and,
thus, were not living strictly solitarily or in pairs (Figure 4). Aggregations typically ranged
in size from 1 to 9, but could occasionally reach sizes of more than 30 individuals. Fur-
thermore, the majority of individual porpoises were observed in some type of aggrega-
tion. This observation suggests a potentially rich diversity of social interactions. The pres-
ence/absence surveys, therefore, hint at the possibility of highly exible social relation-
ships and grouping structures in the nless porpoise.
The average aggregation sizes of both line and area surveys in the present study (1.3
and 1.6 individuals, respectively) were similar to those of previous studies, such as 1.97
individuals recorded in a previous study of nless porpoises [16] and 2.32 individuals
recorded in a study of harbor porpoises (Phocoena phocoena) [24]. Solitaries were the most
frequent, followed by pairs, seemingly supporting the characterization of nless porpoise
grouping structures as mostly individualistic (with some very small group sizes). How-
ever, when focusing on the number of individuals, a striking 76.0% of the observed indi-
viduals in the area surveys were observed in some kind of aggregation. Aggregation sizes
were calculated based on an operational denition of the number of individuals photo-
graphed in a single image or a stream of sequential photographs with conspecic individ-
uals. These aggregation size distributions can be interpreted in at least two ways. Firstly,
porpoise aggregations could be assumed to typically represent small, stable groups with
xed membership. In this case, aggregation sizes ranging gradually from one to nine in-
dividuals would seem to indicate that some porpoises have the behavioral competence to
form long-lasting social bonds among many individuals. The sharp discontinuity in ag-
gregation size frequencies beyond nine individuals suggests against these aggregations
representing mere resource-based groupings. This interpretation would, therefore, sug-
gest a complex paern of intra-group relations and the presence of unknown factors in
determining group size. Alternatively, and possibly more parsimoniously given the pre-
sent ndings, porpoise aggregations could instead be more representative of exible and
transient association paerns without stable membership. Under this interpretation, n-
less porpoises may then develop more varied and dynamic inter-individual relationships
0
10
20
30
Mean of frequency
Distance classes from 0-10 km
Group-to-Group
Group-to-Sprinkling
Sprinkling-to-Sprinkling
Figure 7.
Comparisons of distance-class distributions of group-to-group, group-to-sprinkling, and
sprinkling-to-sprinkling aggregations. The distance class was set at a 100-m interval, with D000
representing the distance range from 0–99 m.
Drones 2023,7, 422 9 of 12
4. Discussion
The findings of the present study highlight dynamic spatiotemporal variation in
narrow-ridged finless porpoises’ distribution and provide novel data on both the total
number of individuals and the frequencies of their aggregation in this area. Using a fixed-
wing VTOL drone, comparison of distribution patterns in different time periods could
be conducted with automated and programmed flights over a total sea area of 120 km
2
.
Those methods clarified that finless porpoises did form aggregations of a variety of sizes
and, thus, were not living strictly solitarily or in pairs (Figure 4). Aggregations typically
ranged in size from 1 to 9, but could occasionally reach sizes of more than 30 individu-
als. Furthermore, the majority of individual porpoises were observed in some type of
aggregation. This observation suggests a potentially rich diversity of social interactions.
The presence/absence surveys, therefore, hint at the possibility of highly flexible social
relationships and grouping structures in the finless porpoise.
The average aggregation sizes of both line and area surveys in the present study
(1.3 and 1.6 individuals, respectively) were similar to those of previous studies, such as
1.97 individuals recorded in a previous study of finless porpoises [
16
] and 2.32 individuals
recorded in a study of harbor porpoises (Phocoena phocoena) [
24
]. Solitaries were the most
frequent, followed by pairs, seemingly supporting the characterization of finless porpoise
grouping structures as mostly individualistic (with some very small group sizes). However,
when focusing on the number of individuals, a striking 76.0% of the observed individuals
in the area surveys were observed in some kind of aggregation. Aggregation sizes were
calculated based on an operational definition of the number of individuals photographed
in a single image or a stream of sequential photographs with conspecific individuals. These
aggregation size distributions can be interpreted in at least two ways. Firstly, porpoise
aggregations could be assumed to typically represent small, stable groups with fixed
membership. In this case, aggregation sizes ranging gradually from one to nine individuals
would seem to indicate that some porpoises have the behavioral competence to form
long-lasting social bonds among many individuals. The sharp discontinuity in aggregation
size frequencies beyond nine individuals suggests against these aggregations representing
mere resource-based groupings. This interpretation would, therefore, suggest a complex
pattern of intra-group relations and the presence of unknown factors in determining group
size. Alternatively, and possibly more parsimoniously given the present findings, porpoise
aggregations could instead be more representative of flexible and transient association
patterns without stable membership. Under this interpretation, finless porpoises may then
develop more varied and dynamic inter-individual relationships that change across time.
Future work will be necessary to verify these possibilities, but in either case, the current
results suggest a higher degree of social complexity than has typically been assumed in
this species.
The mean group-to-group distance (
≥
3 individuals) was smaller than the sprinkling-
to-sprinkling distance in the open sea area (Figure 7), potentially suggesting a cohesive
tendency across groups. In contrast, the sprinkling types (including solitaries and pairs)
were widely dispersed throughout the survey area. The mechanism of this effect remains
unclear. A recent acoustic study revealed pulsed signals in the communication of captive
finless porpoises [
25
], but long-distance communication remains undetermined. The fact
that the medium-sized groups (three to nine individuals) disappeared entirely in session #6
of the area survey (when the largest aggregation was detected) also indirectly supports the
possibility of social communication (regardless of intentionality) in catalyzing the formation
of large aggregations. Additional studies, especially those focusing on a structural analysis
of groups and their ranges (using a VTOL drone at a relatively large scale), as well as
cognitive experiments targeting captive groups, will be necessary to better understand
the behavioral flexibility and variation underlying group formations, social structure, and
communication in finless porpoises.
While the social system and social intelligence of dolphins and some other cetacean
species have been more extensively discussed [
26
–
28
], finless porpoises have been thought
Drones 2023,7, 422 10 of 12
to develop only rare and transient social relationships in a simpler social structure [16,29].
However, the present study found population distributions that suggested unexpected
complexity, highlighting the need for both increased attention to finless porpoise sociality
and re-evaluation of the social complexity of other marine mammals that may have been
overlooked through traditional observation methods [
30
,
31
]. Nonetheless, there are several
important limitations to this study in characterizing finless porpoise sociality. The drastic
change in finless porpoise distributions between two types of group structure (skewed vs.
gradual) in a relatively short period raises the question of how each individual contributes
to the formation of large aggregations, as well as how these patterns are impacted by
extremely localized valuable resources, such as a large prey-fish school, which we could
not assess here. More generally, inability to identify individuals involves a risk of double
counting individuals. This issue may be especially serious in the area surveys, where
individuals and pairs may swim across the survey area over the course of a drone flight.
Nonetheless, we do not have reason to suspect double counting may be more likely to occur
for larger aggregations. On the other hand, some porpoises may have been associated with
others who were too deep in the water for the drone to detect and, thus, counted as solitary
(or as a smaller aggregation size). Actual aggregation sizes, as well as the proportion of
individuals found in aggregations, may, thus, have been underestimated. In either case,
our main findings are unlikely to be explained by these limitations alone. However, limited
knowledge of the size and structure of home ranges, prey-fish resource distributions, and
how other unmeasured variables may affect habitat use seriously limits the generalizability
of our results, and this issue will require explicit research attention.
Furthermore, the drone flight techniques employed in the present study were primitive
and will need refinement and improvement in future studies. The seasonal angle of sunlight
on the water surface is one possible influential factor on visual detection [
11
]. Notably, the
number of individuals observed in the last three sessions was four times larger than that
observed in the first three sessions (303 vs. 75 individuals). This increasing tendency may,
therefore, be related, in part, to the angle of sunlight on the water surface influencing the
visibility of finless porpoises (due to the seasonal change in sun elevation, which is higher
from ASL in summer than in winter in Japan). It is also possible this result is driven by
ecological factors across seasons. Drone research protocols have the potential for further
improvement by increasing flight range and duration, as well as decreasing intervals
between flights. More frequent aerial surveys can also provide novel opportunities for
evaluating and adjusting methods towards more sophisticated flight protocols. Comparing
a variety of flight routes, sizes of survey areas, speeds, altitudes, and times of day can
suggest more optimal techniques for efficient detection of finless porpoises, other animal
species, and even other objects at the sea surface [
32
–
34
]. In any case, our observation
techniques, which were facilitated by the use of a VTOL drone, enabled us to precisely
quantify and visualize the spatiotemporal dynamics of overlapping activity between finless
porpoises and humans at unprecedented resolution in a broad sea area. We hope future
work can extend this approach and improve population monitoring efforts for endangered
and understudied species.
In sum, the current study validated the efficacy of fixed-wing VTOL drone flights for
population monitoring of narrow-ridged finless porpoises and, in so doing, discovered
highly complex and undescribed social aggregation patterns. This outcome reinforces the
feasibility of advanced drone technology as a tool for monitoring large coastal areas and
probing the sociality of understudied species, all through entirely automated, programmed,
and repeatable flight routes. Conservation and management programs crucially depend
on our understanding of species’ distribution and social structures, and with high ocean
biodiversity [
35
–
37
], coastal areas are prime targets for intensive monitoring. These efforts
will undoubtedly be essential for protecting narrow-ridged finless porpoises and other
endangered species, as well as for understanding the diversity and evolution of animal
sociality [38,39].
Drones 2023,7, 422 11 of 12
Author Contributions:
Conceptualization, funding acquisition, methodology, N.M.; investiga-
tion N.M., A.I., J.B., Y.M., Y.P., H.H. and I.M.; formal analysis, N.M.; Writing—original draft,
Writing—review
and editing, N.M., A.I., J.B. and Y.P. All authors have read and agreed to the
published version of the manuscript.
Funding:
This research was funded by the Mitsui and Co. Environment Fund, Grant/Award (K18-
0098) to Naruki Morimura, and the Collaboration Research Program of IDEAS, Chubu University
(IDE-AS201714/IDEAS201818/IDEAS201918/IDEAS202119/IDEAS202216).
Institutional Review Board Statement:
The study protocol was approved by the Institutional Com-
mittee of the Wildlife Research Center of Kyoto University (permit no. WRC-2022-004). The registra-
tion ID of the aircraft was JU42269C1562. Drone flights were approved by the Osaka Regional Civil
Aviation Bureau (permit no. 31326). Kumamoto Coast Guard supported the security of boat traffic
control and related human activity.
Data Availability Statement:
The dataset generated during the current study is not publicly available,
but is available from the corresponding author on reasonable request.
Acknowledgments:
We thank Yujiro Kamimura and Wataru Hamasaki from the Kumamoto Drone
Technology and Development Foundation; Makoto Kitano and Kyouko Myose from CLIMAX Co.,
Ltd.; and Tatsuya Sato from Mirai Legal Service Office Co., Ltd. for supporting the aircraft develop-
ment, flight practices, and administrative proceedings required for the research. We thank Daisuke
Fukushima and the local fishers from the Japan Fisheries Cooperative, Misumimachi, for carrying
out drone surveillance by boat. We also thank Hiromichi Fukui, Satoru Sugita, and Hiroshi Inoue
for providing technical drone expertise at the early stage of development, as well as all staff of the
Kumamoto Sanctuary of Kyoto University for their support during daily observations.
Conflicts of Interest: The authors declare no conflict of interest.
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