1.3 Summary of frugivore tracking movement studies
Since the early 1990s, researchers have used tracking technology to
study frugivore movement. Animal movement studies have increased
exponentially in the last two decades due to the continued advancement
of animal tracking and biologging technology (Kays et al, 2015; Williams
et al, 2020; Nathan et al, 2022). Recent GPS miniaturisation has
enabled tracking studies to focus on smaller animals, while previous
tracking was constrained to larger species to meet tag size requirements
(Wild et al, 2022). In addition, the development of solar powered tags
and remote downloading has enabled long-term studies and allowed
researchers to track more species in more remote habitats (Bridge et al,
2011; Flack et al, 2016). Such developments make understanding seed
dispersal through the lens of movement ecology more accessible and
plausible, and increasingly, studies have used tracking data to infer
seed dispersal effectiveness (Holbrook & Smith, 2000; Kays et al, 2011;
Hirsch et al, 2012; Rehm et al, 2019). Most commonly, studies infer the
movement of seeds using distances travelled during seed retention time
(the time the seed is retained by a frugivore, i.e. often the time taken
for seeds to move through the gut). Simulated GPS tracks are predicted
for the species-specific seed retention time using the fitted
distributions of actual animal movement, which can then be used to fit
seed dispersal kernels (Nathan & Muller-Landau, 2000).
Seed dispersal is defined by 1) frugivore diet, 2) seed retention time
and 3) movement behaviour (Morales et al, 2013; Morales & Lopez, 2022).
Frugivore diets can be described by targeted observations or faecal
analysis. Observational studies identify frugivore-plant interactions
directly and are a low-cost method, but they can be subject to observer
errors and bias, and require significant field effort (Matthews et al,
2020). Analysis of faecal samples can be a more efficient and accurate
method for describing diet. Novel DNA metabarcoding techniques recover a
short sequence of DNA that is characterized as a unique species
identifier (Kress et al, 2015). This method can be used to identify
plant species present in frugivore feces and functions with minimal
fragmented plant material, which is typical of faecal matter due to
degradation through digestion (Gonzalez-Varo et al, 2014). This method
requires a dedicated DNA barcoding sequence dataset of local plants for
reference, so that the sequences can be matched, which can be
prohibitive especially in highly diverse systems (Galimberti et al,
2016). Nonetheless, metabarcoding provides a highly effective new method
for describing frugivore-plant interactions for multiple species.
Describing seed retention time is complex and involves detailed
observation and identification of ingestion and deposition events. This
is challenging and typically requires knowledge of the foraging
behaviour of the species, which often comes from hours of observational
studies (Sorensen, 1981; Schleuning et al, 2011; Plein et al,2013). Traditionally, gut retention time has been measured by direct or
video observations of feeding and deposition events. However, recent
advances in tracking technology have enabled development of small tags
that can be ingested by larger frugivores (Beirne et al, 2019), and
high-resolution tracking tags that can identify certain behaviours
through small changes in body position and movements (Wild et al, 2022).
For example, accelerometers can measure small yet significant changes in
an animal’s posture to determine specific movements (Shepard et al,
2008). By pairing these with detailed observation, patterns in the
acceleration data can be matched with specific behaviours, such as
consumption or defecation events (Fehlmann et al, 2017).
Frugivores have highly detailed movement patterns that can be used to
predict where seeds are likely to be deposited following the calculated
seed retention time. This can be measured using structured observations
(Morales et al, 2103; Ramos et al. 2020), or by tracking animals with
GPS or radio tracking devices (Kays et al, 2011; Abedi-Lartey et al,
2016; Rehm et al, 2019; Martin-Velez et al, 2022). Movement paths from
tracking devices describe where an animal has travelled and, for
frugivorous animals, these can be used to predict where seeds are
deposited. These paths are constructed using movement models such as
random walks, correlated/biased random walks and Levy walks, which use
the probability distributions of movement lengths and turning angles
(Reynolds, 2010; Michelot & Blackwell, 2019). Once a movement path is
generated, seed shadows can be produced to determine the probability of
deposition at specific distances. Seed shadows are made up of 1)
Distance of seed from source, 2) Distribution and density of dispersed
seeds, 3) Number of overlapping, conspecific seed shadows (Cortes &
Uriarte, 2013). Many seed shadow models use a single lognormal
distribution to calculate dispersal kernels, which may not be sufficient
to correctly identify spatially aggregated seed deposition patterns that
are common for vertebrate seed dispersers (Russo et al, 2006). However,
these models are improved by considering an animal’s behavioural
response to different environmental stimuli and their ability to handle
potential biases within the movement data, such as spatial and temporal
autocorrelation (Morales & Lopez, 2022).
The movement patterns of frugivorous animals are determined by species
traits, landscape context and fruit resources. Species morphological
traits define a species’ functional role within an ecosystem and can
impact the provisioning of ecological services. For example,
large-bodied avian frugivores are recognised as important dispersers due
to the large number of seeds they disperse and their ability to disperse
a diverse range of seed sizes, including large seeded species (Wotton &
Kelly, 2012; Galetti et al, 2013; Naniwadekar et al, 2019). Bird species
gape width determines diet breadth and species with larger gape widths
tend to have a more heterogeneous diet and interact with more fruiting
plants (Wheelwright, 1985; Kitamura, 2011; Naniwadekar et al, 2019).
Flying species are also key seed dispersers as they typically disperse
seeds over longer distances and can functionally connect habitat patches
in fragmented landscapes and exploit resources unavailable to
terrestrial vertebrates (Lundberg & Moberg, 2003; Sekercioglu, 2006;
Borah & Beckman, 2022). The relative importance of different frugivore
guilds in seed dispersal networks varies with biogeographic region and
habitat (Dent & Estrada-Villegas, 2021; Garcia-Rodriguez et al, 2022;
Tsunamoto et al, 2020). Birds tend to be generalist and opportunistic
feeders, whilst mammals, especially larger bodied species, can have more
specialised roles and are highly important for the dispersal of larger
seeds (Ong et al, 2022). Understanding how morphological traits of
frugivores are linked to seed dispersal potential is a critical step in
understanding the link between animal and plant communities and can help
to disentangle how changes in landscape structure affect colonisation,
persistence, and recovery of animal and plant communities.
Habitat loss and fragmentation have reduced continuous tracts of natural
habitat to complex human-modified landscapes (Mitchell et al, 2013;
Chazdon, 2014). In these contexts, natural habitat is often embedded in
a matrix of agriculture, pastureland or other heavily modified
landscapes. Shifts in the spatial structure and composition of habitats
at the landscape scale drives changes in plant and animal communities
and their interactions (Durães et al, 2013). For example, the diversity
of forest-dependant frugivores decreases with deforestation, resulting
in loss of habitat, simplification of vegetation complexity and loss of
fruit biomass (Sekercioglu, 2012; Rey & Alcantara, 2014; Morante-Filho
et al, 2018). The composition and configuration of fragmented landscapes
also affects the ability of animals to disperse among habitat fragments
(Schick et al, 2008; Nield et al, 2020). Many species do not cross gaps
between fragments due to increased predation risk or physiological
constraints (Sekercioglu et al, 2015; Ramos et al, 2020). This affects
the assemblages of organisms found at specific sites; and the ecosystem
services they provide (Terborgh et al, 2008; Lehouck et al, 2009;
Brockerhoff et al, 2017). If seed dispersers are unable or unwilling to
move among fragments, then gene flow and plant diversity may decrease in
isolated fragments due to reductions in seed rain (Knörr & Gottsberger,
2012; Martin-Queller et al, 2017; Hooper & Ashton, 2020).
Fruit-resource distributions and availability also influence animal and
seed dispersal across heterogenous landscapes. Fruiting seasons tend to
be sporadic and the size of fruit crops varies, leading to
spatiotemporal variations in fruit availability, which underpin many
frugivore movement decisions. For example. Herrera et al, (2011)
demonstrated that mean seed dispersal and probability of long-distance
dispersal decreased with increasing abundance of fleshy fruits. Animals
are likely to congregate in areas of high fruit abundance, then move
long distances searching for other patches when fruit resources are low
(Gopal et al, 2020). Additionally, forest composition and fruit
resources can also interact to affect how frugivores track fruit
resources, with areas of high fragmentation experiencing lower seed
removal rates than intact forests due to the shifts in frugivore
assemblages (Lehouck et al, 2009).