Marin-Gomez, O. H. | Search bioRxiv

bioRxiv2018

Abundance drives generalisation in hummingbird-plant pollination networks

Abundant pollinators are often more generalised than rare pollinators. This could be because abundance drives generalisation: neutral effects suggest that more abundant species will be more generalised simply because they have more chance encounters with potential interaction partners. On the other hand, generalisation could drive abundance, as generalised species could have a competitive advantage over specialists, being able to exploit a wider range of resources and gain a more balanced nutrient intake. Determining the direction of the abundance-generalisation relationship is therefore a chicken-and-egg dilemma. Here we determine the direction of the relationship between abundance and generalisation in plant-hummingbird pollination networks sampled from a variety of locations across the Americas. For the first time we resolve the direction of the abundance-generalisation relationship using independent data on animal abundance. We find evidence that hummingbird pollinators are generalised because they are abundant, and little evidence that hummingbirds are abundant because they are generalised. Additionally, a null model analysis suggests this pattern is due to neutral processes: most patterns of species-level abundance and generalisation were well explained by a null model that assumed interaction neutrality. These results suggest that neutral processes play a key role in driving broad patterns of generalisation in animal pollinators across large spatial scales.\n\nDeclarationsFunding - BIS is supported by the Natural Environment Research Council as part of the Cambridge Earth System Science NERC DTP [NE/L002507/1]. JVB was funded by CERL - Engineer Research and Development Center. PKM was funded by the Sao Paulo Research Foundation (FAPESP grant #2015/21457-4). PAC was funded by the David Lack studentship from the British Ornithologists Union and Wolfson College, University of Oxford. CL was funded by the ESDEPED-UAT grant. MAM acknowledges the Consejo Nacional para Investigaciones Cientificas y Tecnologicas (Costa Rica), German Academic Exchange Service and the research funding program LOEWE-Landes-Offensive zur Entwicklung Wissenschaftlicho konomischer Exzellenz of Hesses Ministry of Higher Education, Research, and the Arts (Germany). ROP was funded by CONACyT (project 258364). MAR was supported by the State of Sao Paulo Research Foundation (FAPESP) within the BIOTA/FAPESP, The Biodiversity Institute Program (www.biota.org.br) and the Parcelas Permanentes project, as well as by Coordenacao de Pessoal de Nivel Superior (CAPES), Fundo de Apoio ao Ensino e a Pesquisa (FAEP)/Funcamp/Unicamp and The Nature Conservancy (TNC) of Brazil. LCR was supported by CNPq and Capes. MS was funded by CNPq (grant #302781/2016-1). AMMG is supported through a Marie Skodowska-Curie Individual Fellowship (H2020-MSCA-IF-2016-704409). LVD was supported by the Natural Environment Research Council (grants NE/K015419/1 and NE/N014472/1). AMMG, JS, CR and BD thank the Danish National Research Foundation for its support of the Center for Macroecology, Evolution and Climate (grant no. DNRF96). WJS is funded by Arcadia.

ecology↗

bioRxiv2018

Multinomial-Poisson mixture models reveal unexpected higher density estimates of an Andean threatened bird

Multinomial-Poisson mixture models reveal unexpected higher density estimates of an Andean threatened bird.Distance sampling and repeated counts are important tools to estimate population density of birds with low detectability. Here we use model based approach to assess the population density of a threatened bird, the Multicolored Tanager (Chlorochrysa nitidissima). We conducted 144 fixed point counts samplings to record all the individuals of the Multicolored Tanager detected by visual and aural observations from different habitats (forest edge, mature, secondary, and riparian forest), during four months in an Important Bird Area of Central Andes of Colombia. We used spatially replicated counts, distance sampling, and multinomial- Poisson mixture models to estimate the population density of the Multicolored Tanager. Accumulated sampling effort was of 576 repetitions in 144 point counts with 96 h of observation. The Multinomial-Poisson mixture model showed the best fit due low variance of density estimations in comparison to the conventional distance sampling and the spatially replicated counts. Results of this model evidenced a remarkable higher density estimates (1.3 - 2.05 individuals/ha) of the Multicolored Tanager, particularly in mature and secondary forest, as a result of detection correction, instead of sampling effort, by our model based analysis in contrast to index density used in previous studies. We discuss the advantages of model based methods over density indexes in designs monitoring programs of endangered species as the Multicolored Tanager, in order to obtain better and comparable assessment of density estimations along multiple localities.\n\nResumenLa combinacion de modelos multi-nominales y Poisson revelan estimaciones de densidad altas inesperadas en un ave amenazada Andina. Los muestreos por distancias y los conteos repetidos son herramientas importantes para estimar la densidad de poblacion de aves con baja deteccion. Aqui utilizamos un enfoque basado en modelos para evaluar la densidad de poblacion de un ave amenazada, la tangara multicolor (Chlorochrysa nitidissima). Realizamos 144 muestreos de conteos de puntos fijos para registrar todos los individuos de la tangara multicolor detectados por observaciones visuales y auditivas en diferentes habitats (borde del bosque, bosque maduro, bosque secundario y bosque ribereno), durante cuatro meses en un Area Importante para la Conservacion de las Aves en los Andes centrales de Colombia. Utilizamos conteos replicados espacialmente, muestreos de distancia y la combinacion de modelos multi-nominales y Poisson para estimar la densidad de poblacion de la tangara multicolor. El esfuerzo de muestreo acumulado fue de 576 repeticiones en 144 puntos de conteo con 96 h de observacion. La combinacion de modelos multi-nominales y Poisson mostro el mejor ajuste debido a la baja varianza de las estimaciones de densidad en comparacion con el muestreo de distancias y los conteos replicados espacialmente. Los resultados de este modelo evidenciaron una notable estimacion de mayor densidad (1.3 - 2.05 individuos / ha) de la tangara multicolor, principalmente en bosques maduros y secundarios, como resultado de la correccion de la deteccion por nuestro analisis basado en modelos, en lugar del esfuerzo de muestreo, en contraste con los indices de densidad utilizados en estudios previos. Discutimos las ventajas de los metodos basados en modelos sobre los indices de densidad en los disenos de programas de monitoreo de especies en peligro como la tangara multicolor, con el fin de obtener una evaluacion mejor y comparable de las estimaciones de densidad a lo largo de multiples localidades.

zoology↗