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).