Deterministic modelling of seed dispersal based on observed behaviours of an endemic primate in Brazil

Abstract

Plant species models are among the available tools to predict the future of ecosystems threatened by climate change, habitat loss, and degradation. However, they suffer from low to no inclusion of plant dispersal, which is necessary to predict ecosystem evolution. A variety of seed dispersal models have been conceived for anemochorous and zoochorous plant species, but the coupling between vegetation models and seed dispersal processes remains rare. The main challenge in modelling zoochoric dispersal is simulating animal movements in their complex habitat. Recent developments allow straightforward applications of hidden Markov modelling (HMM) to animal movements, which could ease generalizations when modelling zoochoric seed dispersal. We tested the use of HMM to model seed dispersal by an endangered primate in the Brazilian Atlantic forest, to demonstrate its potential simplicity to simulate seed dispersal processes. We also discuss how to adapt it to other species. We collected information on movement, fruit consumption, deposition, and habitat use of Leontopithecus chrysomelas. We analysed daily trajectories using HMM and built a deterministic Model Of Seed Transfer (MOST), which replicated, with good approximation, the primate’s movement and seed deposition patterns as observed in the field. Our results suggest that the dispersal behaviour and short daily-trajectories of L. chrysomelas restrict the species’ role in large-scale forest regeneration, but contribute to the prevalence of resource tree species locally, and potentially maintaining tree diversity by preventing local extinction. However, it may be possible to accurately simulate dispersal in an area, without necessarily quantifying variables that influence movement, if the movement can be broken down to step-length and turning angles, and parametrised along with the distribution of gut-transit times. For future objectives, coupling MOST with a DVM could be used to test hypotheses on tree species survival in various scenarios, simulating regeneration and growth at regional scales by including data on main dispersal agents over the area of interest, distribution of tree species, and land use data. The principal advantage of the MOST model is its functionality with data available from the literature as the variables are easy to parametrise. We suggest using the coupled model to perform experiments using only available information, but varying the numbers and species of seed dispersers, or modifying land cover or configuration to test for possible thresholds preventing the extinction of selected tree species.

CoFee-L: A model of animal displacement in large groups combining Cohesion maintenance, Feeding area search and transient Leadership.

“…Then, departure and/or arrival generation points could be set up, as some species have particular sleeping sites (e.g. [32,48,49]). In the current context, given the degradation of the environment and low fruit 3 High-cost (resp.…”

“…In this framework, mechanistic modelling, including animal movements, their interactions with the fruiting trees and their physiological requirements becomes easier to consider and this kind of methodology looks able to exploit the available datasets. For instance, the model MOST was built and validated for the seed deposition of the genus Pourouma produced by a small group of 4 Golden-headed lion tamarins (Leontopithecus chrysomelas) [48]. The animal trajectories in their seasonal home range were analysed with hidden Markov modelling which further allows generating state transitions related to local environmental characteristics and accordingly, random steps and turning angles.…”

CoFee-L: A Model of Animal Displacement in Large Groups Combining Cohesion Maintenance, Feeding Area Search and Transient Leadership

“…In the case of macaques and other species that form large groups, individuals split into several subgroups for feeding (and thus use several FAs at the same time) and join each other during large movements [ 48 , 49 ]. Departure and/or arrival generation points could then be set up, as some species have particular sleeping sites (e.g., [ 32 , 50 , 51 ]). In the current context, given the degradation of the environment and low fruit availability, the group was simulated and ended its days around FAs; this was observed in the field to presumably maximize energy intake [ 31 ] and also in other species such as the bonobo ( Pan paniscus ) [ 52 ].…”

“…In this framework, mechanistic modeling, including animal movements, their interactions with the fruiting trees and their physiological requirements, becomes easier to consider, and this type of methodology appears to be able to exploit the available datasets. For instance, the model MOST was built and validated for the seed deposition of the genus Pourouma produced by a small group of four golden-headed lion tamarins ( Leontopithecus chrysomelas ) [ 50 ]. The animal trajectories in their seasonal home range were analyzed with hidden Markov modeling, which further allows for the generation of state transitions related to local environmental characteristics and accordingly, random steps and turning angles.…”