[Lisfauba] HOY SEMINARIO ESPECIAL IFEVA - SUM IFEVA 12:00 Hs
Facultad de Agronomía UBA
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Jue Nov 28 08:21:53 ART 2024
* Seminario IFEVA*
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*JUEVES28 DE NOVIEMBRE 202412:00 hs*
Presencial: SUM *IFEVA*
<https://www.youtube.com/channel/UCCC_QmqL9yuKBnZ6p4mnxBw>
Spatial aggregation, animal seed
dispersal and forest dynamics.
Autores: Thorsten Wiegand1,2, Xugao Wang3, and Andreas Huth1,2
Filiación: 1Dep. of Ecological Modelling, Helmholtz Centre for
Environmental Research –UFZ
2 German Centre for Integrative Biodiversity Research (iDiv)
3 Key Laboratory of Forest Ecology and Management, Institute of Applied
Ecology Chinese Academy of Sciences, Shenyang, China
*Resumen: *The search for simple principles underlying the spatial
structure and dynamics of plant communities is a long-standing challenge in
ecology. In particular, the relationship between species coexistence and
the spatial distribution of plants is challenging to resolve in
species-rich communities. Here we present a comprehensive analysis of the
spatial patterns of 720 tree species in 21 large forest plots and its
consequences for species coexistence. We find that species with low
abundances tend to be more spatially aggregated than more abundant species,
and a latitudinal gradient in the strength of this negative
aggregation-abundance relationship that increases from tropical to
temperate forests. We suggest, in line with recent work, that latitudinal
gradients in animal seed dispersal11 and mycorrhizal associations may
jointly generate this intriguing pattern. By integrating the observed
spatial patterns into population models we derive the conditions under
which species can invade from low abundances, in terms of spatial patterns,
demography, niche overlap, and immigration. Evaluation of the spatial
invasion condition for our 720 tree species suggests that temperate and
tropical forests meet the invasion criterion to a similar extend, but
through opposed strategies conditioned by their spatial patterns. Our
approach opens up new avenues for integrating observed spatial patterns
into ecological theory, and underscores the need to understand the
interaction among spatial patterns at the neighbourhood scale and multiple
ecological processes in greater detail.
*claves: *Coexistence, ForestGEO megaplots, latitudinal gradients, seed
dispersal, spatial pattern.
[image: ThorstenWiegand_b.jpg]
Thorsten Wiegand studied physics at the University Marburg where he
completed his graduate work in theoretical ecology. In 1992 he started as
Postdoc to the Department of Ecological Modelling at the UFZ in Leipzig,
and in 1999 obtained his habilitation in Theoretical Ecology at the LMU
Munich. Dr Wiegand is a theoretical ecologist with more than 25 years
research experience in question-driven research in biodiversity and
conservation. He is working in close collaboration with field ecologists to
conduct model-data integration and synthesis. His research centers broadly
on spatial ecology and the investigation of the role of species
interactions, spatial patterns and spatial processes for population and
community dynamics, community assembly, and biodiversity. His primary
research goals are to broaden the theory of population and community
ecology and to integrate them with landscape ecology to encompass an
explicit consideration of spatially distributed processes, and to develop
methods to adapt individual-based simulation models optimally for
ecological applications.
Certificados: los alumnos que necesiten certificar su asistencia, deberán
enviar su nombre y DNI al moderador (mtexeira en agro.uba.ar) durante el
transcurso del seminario o dentro de la hora posterior a la finalización
del mismo.
*Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la
Agricultura*
IFEVA - Facultad de Agronomía - Universidad de Buenos Aires
Av. San Martín 4453 - C1417DSE - Buenos Aires - Argentina
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Marcos Texeira
Departamento de Métodos Cuantitativos y Sistemas de Información //
LART - IFEVA - CONICET
(011) 52870829
Facultad de Agronomía
Universidad de Buenos Aires
Av. San Martín 4453 (C1417DSE)
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