Research Highlights: Frugivores able to disperse large seeds over large distances are indispensable for seedling recruitment, colonization and regeneration of tropical forests. Understanding their effectiveness as seed dispersal agents in degraded habitat is becoming a pressing issue because of escalating anthropogenic disturbance. Although of paramount importance in the matter, animal behaviour’s influence on seed shadows (i.e., seed deposition pattern of a plant population) is difficult to evaluate by direct observations. Background and Objectives: We illustrated a modeling approach of seed shadows incorporating field-collected data on a troop of northern pigtailed macaques (Macaca leonina) inhabiting a degraded forest fragment in Thailand, by implementing a mechanistic model of seed deposition with random components. Materials and Methods: We parameterized the mechanistic model of seed deposition with macaque feeding behavior (i.e., consumed fruit species, seed treatments), gut and cheek pouch retention time, location of feeding and sleeping sites, monthly photoperiod and movement patterns based on monthly native fruit availability using Hidden Markov models (HMM). Results: We found that northern pigtailed macaques dispersed at least 5.5% of the seeds into plantation forests, with a majority of medium- to large-seeded species across large distances (mean > 500 m, maximum range of 2300 m), promoting genetic mixing and colonization of plantation forests. Additionally, the macaques produced complementary seed shadows, with a sparse distribution of seeds spat out locally (mean >50 m, maximum range of 870 m) that probably ensures seedling recruitment of the immediate plant populations. Conclusions: Macaques’ large dispersal distance reliability is often underestimated and overlooked; however, their behavioral flexibility places them among the last remaining dispersers of large seeds in disturbed habitats. Our study shows that this taxon is likely to maintain significant seed dispersal services and promote forest regeneration in degraded forest fragments.

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.

<p>Dynamic vegetation modelling is intensively used with plant functional types which limits the range of interest of obtained outputs for other fields of knowledge like conservation science. An alternative approach is to simulate plant species. This however requires additional data, i.e. morphological and physiological traits values characterizing the species and determining their functional properties. However, not only many traits vary among the species belonging to the same plant functional type but also the traits vary broadly according to climate factors.</p><p>Since most of the traits are functional, their values may be critical for dynamic vegetation model outputs. We measured several traits (specific leaf area, leaf and sapwood C:N) of Cedrus atlantica in its native range, the Rif and Middle Atlas Mountains of Morocco, as well as in some plantations in western Europe. Trait values exhibit significant variations between the sampled sites. It is possible to predict these trait values using multiple regression with climate factors as explanatory variables. Using regression equations, we produced spatial- and time-varying traits over the study area. We implemented these equations in the CARAIB dynamic vegetation model and tested whether they improve the simulation of C. atlantica in the Rif and Middle Atlas Mountains, by comparing the net primary productivities and biomasses computed with and without trait variation, with those retrieved from measurements on the sampled sites. We then performed simulations of the future using climate projections of the regional climate model RCA4 nested in HadGEM2 general circulation model under the RCP8.5 scenario, in order to test the influence of trait acclimation on the predicted future changes in the range and productivity of the species.</p>

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