Landscape structure shapes carnivore-mediated seed dispersal kernels

Context Seed dispersal is recognized as having profound effects on the distribution, dynamics and structure of plant populations and communities. However, knowledge of how landscape structure shapes carnivore-mediated seed dispersal patterns is still scarce, thereby limiting our understanding of large-scale plant population processes. Objectives We aim to determine how the amount and spatial configuration of forest cover impacted the relative abundance of carnivorous mammals, and how these effects cascaded through the seed dispersal kernels they generated. Methods Camera traps activated by animal movement were used for carnivore sampling. Colour-coded seed mimics embedded in common figs were used to know the exact origin of the dispersed seed mimics later found in carnivore scats. We applied this procedure in two sites differing in landscape structure. Results We did not find between-site differences in the relative abundance of the principal carnivore species contributing to seed dispersal patterns, Martes foina. Mean dispersal distance and the probability of long dispersal events were higher in the site with spatially continuous and abundant forest cover, compared to the site with spatially aggregated and scarcer forest cover. Seed deposition closely matched the spatial patterning of forest cover in both study sites, suggesting behaviour-based mechanisms underpinning seed dispersal patterns generated by individual frugivore species. Conclusions Our results provide the first empirical evidence of the impact of landscape structure on carnivore-mediated seed dispersal kernels. They also indicate that seed dispersal kernels generated strongly depend on the effect that landscape structure exerts on carnivore populations, particularly on habitat-use preferences.

Occurrence and abundance models of threatened plant species: Applications to mitigate the impact of hydroelectric power dams

Species occurrence and abundance models are important tools that can be used in biodiversity conservation, and can be applied to predict or plan actions needed to mitigate the environmental impacts of hydropower dams. In this study our objectives were: (i) to model the occurrence and abundance of threatened plant species, (ii) to verify the relationship between predicted occurrence and true abundance, and (iii) to assess whether models based on abundance are more effective in predicting species occurrence than those based on presence–absence data. Individual representatives of nine species were counted within 388 randomly georeferenced plots (10 m × 50 m) around the Barra Grande hydropower dam reservoir in southern Brazil. We modelled their relationship with 15 environmental variables using both occurrence (Generalised Linear Models) and abundance data (Hurdle and Zero-Inflated models). Overall, occurrence models were more accurate than abundance models. For all species, observed abundance was significantly, although not strongly, correlated with the probability of occurrence. This correlation lost significance when zero-abundance (absence) sites were excluded from analysis, but only when this entailed a substantial drop in sample size. The same occurred when analysing relationships between abundance and probability of occurrence from previously published studies on a range of different species, suggesting that future studies could potentially use probability of occurrence as an approximate indicator of abundance when the latter is not possible to obtain. This possibility might, however, depend on life history traits of the species in question, with some traits favouring a relationship between occurrence and abundance. Reconstructing species abundance patterns from occurrence could be an important tool for conservation planning and the management of threatened species, allowing scientists to indicate the best areas for collection and reintroduction of plant germplasm or choose conservation areas most likely to maintain viable populations.