11 research outputs found
Plant ecology meets animal cognition: impacts of animal memory on seed dispersal
We propose that an understanding of animal learning and memory is critical to predicting the impacts of animals on plant populations through
processes such as seed dispersal, pollination and herbivory. Focussing on endozoochory, we review the evidence that animal memory plays a role in seed
dispersal, and present a model which allows us to explore the fundamental consequences of memory for this process. We demonstrate that decision-making by animals based on their previous experiences has the potential to determine which plants are visited, which fruits are selected to be eaten from the plant and where seeds are subsequently deposited, as well as being an important determinant of animal survival. Collectively, these results suggest that the impact of animal learning and memory on seed dispersal is likely to be extremely important, although to date our understanding of these processes suffers from a conspicuous lack of empirical support. This is partly because of the difficulty of conducting appropriate experiments but is
also the result of limited interaction between plant ecologists and those who work on animal cognition
Geographic patterns in fruit colour diversity: do leaves constrain the colour of fleshy fruits?
7 pages, 2 figures.-- Supplementary material available: The list of fruit species, their colour as perceived by humans, their provenance and main disperser types. The dispersal category "mixed" refers to species consumed by birds and mammals (XLS, 43 kb).We tested for geographic patterns in fruit colour diversity. Fruit colours are thought to promote detection by seed dispersers. Because seed dispersers differ in their spectral sensitivities, we predicted that fruit colour diversity would be higher in regions with higher seed disperser diversity (i.e. the tropics). We collected reflectance data on 232 fruiting plant species and their natural backgrounds in seven localities in Europe, North and South America, and analysed fruit colour diversity according to the visual system of birds—the primary consumer types of these fruits. We found no evidence that fruit colours are either more conspicuous or more diverse in tropical areas characterised by higher seed disperser diversity. Instead, fruit colour diversity was lowest in central Brazil, suggesting that fruit colours may be more diverse in temperate regions. Although we found little evidence for geographic variation in fruit hues, the spectral properties of fruits were positively associated with the spectral properties of backgrounds. This result implies that fruit colours may be influenced by selection on the reflectance properties of leaves, thus constraining the evolution of fruit colour. Overall, the results suggest that fruit colours in the tropics are neither more diverse nor more conspicuous than temperate fruits, and that fruit colours may be influenced by correlated selection on leaf reflectance properties.H.M.S. was sponsored by a Deutsche Forschungsgemeinschaft (DFG) grant (Scha 1008/4-1). E.C. was sponsored by Fundaçao de Amparo à Pesquisa do Estado de Sao
Paulo (Fapesp) and a Deutscher Akademischer Austausch Dienst (DAAD) fellowship. M.G. was sponsored by Fapesp and receives a
research fellowship from Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), and E.C. a Fapesp fellowship. A.V.
was supported by the Marie Curie European programme (grant MERG-CT-2004-510260), I3P [Consejo Superior de Investigaciones
Científicas (CSIC)] and Acción Integrada (HA2006-0038; Ministerio de Educación y Ciencia).Peer reviewe
Evaluating sampling completeness in a desert plant-pollinator network
1. The study of plant-pollinator interactions in a network context is receiving increasing attention. This approach has helped to identify several emerging network patterns such as nestedness and modularity. However, most studies are based only on qualitative information, and some ecosystems, such as deserts and tropical forests, are underrepresented in these data sets. 2. We present an exhaustive analysis of the structure of a 4-year plant-pollinator network from the Monte desert in Argentina using qualitative and quantitative tools. We describe the structure of this network and evaluate sampling completeness using asymptotic species richness estimators. Our goal is to assess the extent to which the realized sampling effort allows for an accurate description of species interactions and to estimate the minimum number of additional censuses required to detect 90% of the interactions. We evaluated completeness of detection of the community-wide pollinator fauna, of the pollinator fauna associated with each plant species and of the plant-pollinator interactions. We also evaluated whether sampling completeness was influenced by plant characteristics, such as flower abundance, flower life span, number of interspecific links (degree) and selectiveness in the identity of their flower visitors, as well as sampling effort. 3. We found that this desert plant-pollinator network has a nested structure and that it exhibits modularity and high network-level generalization. 4. In spite of our high sampling effort, and although we sampled 80% of the pollinator fauna, we recorded only 55% of the interactions. Furthermore, although a 64% increase in sampling effort would suffice to detect 90% of the pollinator species, a fivefold increase in sampling effort would be necessary to detect 90% of the interactions. 5. Detection of interactions was incomplete for most plant species, particularly specialists with a long flowering season and high flower abundance, or generalists with short flowering span and scant flowers. Our results suggest that sampling of a network with the same effort for all plant species is inadequate to sample interactions. 6. Sampling the diversity of interactions is labour intensive, and most plant-pollinator networks published to date are likely to be undersampled. Our analysis allowed estimating the completeness of our sampling, the additional effort needed to detect most interactions and the plant traits that influence the detection of their interactions. © 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.Research was funded by grants from CONICET (PIP 6564), FONCYT (PICT 20805, PICT 1471) and BBVA Foundation (BIOCON03-162)Peer Reviewe