中国蔷薇科植物多样性格局及其资源植物保护现状

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中国蔷薇科植物多样性格局及其资源植物保护现状

2023-04-21 06:48| 来源: 网络整理| 查看: 265

Aims We present an analysis of grid-based species-richness data for European plants, mammals, birds, amphibians and reptiles, designed to test the proposition of Hawkins et al. (2003a ) that the single best factor describing richness variation switches from the water regime to the energy regime in the mid-latitudes and that the 'breakpoint' is related to the physiological character of the taxa. We go on to develop subregional models showing the extent to which regional model fits vary as a function of the extent of the study system, and compare the relative performance of 'water', 'energy' and 'water–energy' models of richness for southern, northern and pan-European models. Location Western Europe. Methods We use atlas data comprising species range data for 187 species of mammals, 445 species of breeding birds, 58 amphibians, 91 reptiles and 2362 plant species, inserted into a c. 50 × 50 km grid cell system. We used 11 modelled climate variables, averaged for the period 1961–90. Statistical analyses were carried out using generalized additive models (GAMs), with splines simplified to a maximum of four degrees of freedom, and we tested for spatial autocorrelation using Moran's I values obtained at 10 different distance intervals. We selected favoured models on the grounds of deviance explained combined with a simple parsimony criterion, such that we selected either: (1) the best two-variable energy, water or water–energy model, or (2) a four-variable water–energy model, where the latter improved on the best two-variable model by a minimum of 5% deviance explained. Results Threshold energy values, at which richness shows a transition from an increasing to a decreasing function of annual solar radiation, were identified for all taxa apart from reptiles. We found conditional support for the switch from dominance of water variables (southern models) to energy variables (northern models). Our favoured models switched between 'water' and 'energy' for mammals, and between 'energy' and 'water–energy' for birds, depending on whether we used data of pan-European extent, southern or northern subsets. Deviance explained in our favoured models varied from 15% (birds, southern Europe) to 72% (amphibians, northern Europe), i.e. ranging from very poor to good fits with the data. Comparison with previous work indicates that our models are generally consistent with (if sometimes weaker than) previous findings. Main conclusions Our models are incomplete representations of factors influencing macro-scale richness patterns across Europe, taking no explicit account of, for example, topographic variation, human influences or long-term climatic variation. However, with the exception of birds, for which only the northern model attains over one-third deviance explained, the models show that climate can account for meaningful proportions of the deviance. We find general support for considering water and energy regimes together in modelling species richness, and for the proposition that water is more limiting in southern Europe and energy in the north. Our analyses demonstrate the sensitivity of model outcomes to the geographical location and extent of the study system, illustrating that simple curve-fitting exercises like these, particularly if based on regions with the complex history and geography characteristic of Europe, are unlikely to provide the basis for global, predictive models. However, such exercises may be of value in detecting which aspects of water and energy regimes may be of most importance in refining independently generated global models for regional application.



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