RESUMEN
Occurrence patterns of many sessile species in dynamic landscapes are not in equilibrium due to their slow rates of metapopulation colonization and extinction. Colonization-extinction data enable the estimation of colonization rates for such species, but collecting the necessary data may require long waiting times between sampling years. Methods for estimating colonization rates of nonequilibrium metapopulations from single occurrence-pattern data have so far relied on additional data on patch ages and on past patch connectivities. We present an approach where metapopulation colonization rates are estimated from occurrence-pattern data and from disturbance history data that inform of past patch dynamics and that can be collected together with occurrence-pattern data. We estimated parameter values regulating patch and metapopulation dynamics by simulating patch network and metapopulation histories that result in present-like patch network configurations and metapopulation occurrence patterns. We tested our approach using occurrence-pattern data of the epiphytic lichen Lobaria pulmonaria in Fennoscandian forests, and fire-scar data that inform of the 400-yr history of fires and host tree dynamics in the same landscapes. The estimated model parameters were similar to estimates obtained using colonization-extinction data. The projected L. pulmonaria occupancy into the future also agreed with the respective projections that were made using the model estimated from colonization-extinction data. Our approach accelerates the estimation of metapopulation colonization rates for sessile species that are not in metapopulation equilibrium with the current landscape structure.
Asunto(s)
Ecosistema , Líquenes , Modelos Biológicos , Dinámica Poblacional , ÁrbolesRESUMEN
We present a Bayesian hierarchical model for the joint spatial dynamics of a host-parasite system. The model was fitted to long-term data on regional plague dynamics and metapopulation dynamics of the black-tailed prairie dog, a declining keystone species of North American prairies. The rate of plague transmission between colonies increases with increasing precipitation, while the rate of infection from unknown sources decreases in response to hot weather. The mean annual dispersal distance of plague is about 10 km, and topographic relief reduces the transmission rate. Larger colonies are more likely to become infected, but colony area does not affect the infectiousness of colonies. The results suggest that prairie dog movements do not drive the spread of plague through the landscape. Instead, prairie dogs are useful sentinels of plague epizootics. Simulations suggest that this model can be used for predicting long-term colony and plague dynamics as well as for identifying which colonies are most likely to become infected in a specific year.
Asunto(s)
Clima , Modelos Biológicos , Peste/veterinaria , Sciuridae/parasitología , Yersinia pestis/fisiología , Animales , Teorema de Bayes , Simulación por Computador , Interacciones Huésped-Parásitos , Peste/parasitología , Peste/transmisión , Densidad de Población , Dinámica Poblacional , Lluvia , TemperaturaRESUMEN
Three different approaches were used to assess the kinship structure of two epiphytic bryophytes, Orthotrichum speciosum and O. obtusifolium, that have different dispersal strategies. The two species were sampled in a 200 ha landscape where species occurrence and host trees had been mapped previously. Local environmental conditions at sampled trees were recorded and kinship between individuals was calculated based on amplified fragment length polymorphism (AFLP)-marker data. We did not detect any association between AFLP-markers and investigated environmental conditions. In both species, significant kinship coefficients were found between individuals up to 300-350 m apart which shows that both species have a restricted dispersal range. The spatial kinship structure was detected with both autocorrelation analysis and generalized additive models (GAMs), but linear regression failed to detect any structure in O. speciosum. Although the dioecious O. obtusifolium is currently the more common species it may, none the less, due to its restricted dispersal range and reproduction mode, become threatened in the future by current silvicultural practices which enhance the distance between host trees and decrease their life span. Finally, GAMs seem most appropriate for analysing spatial genetic structure because the effects of local environmental conditions and spatial structure can be analysed simultaneously, no assumption of a parametric form between kinship coefficient and distance is required, and spatial data resolution is not lost in the arbitrary choice of distance classes characterizing autocorrelation analysis.