Climatic relationships of some New Zealand forest tree species

Abstract. A dataset of some 10 000 plots was used to describe the climatic relationships of 33 widespread New Zealand tree species. Estimates of mean annual temperature, temperature seasonality, mean annual solar radiation, and moisture balance were derived from mathematical surfaces fitted to climate station data. Plots were also categorized into five lithological classes and three drainage classes. Generalized additive models were used to examine species/environment relationships. Mean annual temperature and mean annual solar radiation are most strongly correlated with current tree distributions, followed by moisture balance, temperature seasonality, lithology, and drainage. Most broad-leaved tree species other than Nothofagus spp. reach their greatest levels of occurrence in warm, moist environments with high solar radiation. In contrast, Nothofagus spp. generally reach their greatest levels of occurrence in cooler and/or lower insolation environments, and all have lower levels of occurrence on rhyolitic substrates which have resulted from large-scale geomorphic disturbance, mostly over the past few thousand years. Although coniferous species have widely differing climatic optima, many are biased towards lithological classes characterized either by large-scale geomorphic disturbance or harsh edaphic conditions. The relevance of these results to particular synecological questions is briefly discussed. Continuing adjustments in the range of slow-dispersing Nothofagus spp. are strongly suggested, and the climatic suitability of extensive rhyolitic basins in the central North Island, from which these species are largely absent, is confirmed.     

Climatic niche of the Saker Falcon Falco cherrug: predicted new areas to direct population surveys in Central Asia

Accurate species distribution data across remote and extensive geographical areas are difficult to obtain. Here, we use bioclimatic envelope models to determine climatic constraints on the distribution of the migratory Saker Falcon Falco cherrug to identify areas in data-deficient regions that may contain unidentified populations. Sakers live at low densities across large ranges in remote regions, making distribution status difficult to assess. Using presence-background data and eight bioclimatic variables within a species distribution modelling framework, we applied MaxEnt to construct models for both breeding and wintering ranges. Occurrence data were spatially filtered and climatic variables tested for multicollinearity before selecting best fit models using the Akaike information criterion by tuning MaxEnt parameters. Model predictive performance tested using the continuous Boyce index (B) was high for both breeding (B_TEST = 0.921) and wintering models (B_TEST = 0.735), with low omission rates and minimal overfitting. The Saker climatic niche was defined by precipitation in the warmest quarter in the breeding range model, and mean temperature in the wettest quarter in the wintering range model. Our models accurately predicted areas of highest climate suitability and defined the climatic constraints on a wide-ranging rare species, suggesting that climate is a key determinant of Saker distribution across macro-scales. We recommend targeted population surveys for the Saker based on model predictions to areas of highest climatic suitability in key regions with distribution knowledge gaps, in particular the Qinghai-Tibet plateau in western China. Further applications of our models could identify protected areas and reintroduction sites, inform development conflicts, and assess the impact of climate change on distributions.     

Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France

Aim  To estimate the relative importance of climate and soil nutritional variables for predicting the distribution of Acer campestre (L.) in French forests.
Location  France.
Methods  We used presence/absence information for A. campestre in 3286 forest plots scattered all over France, coupled with climatic and edaphic data. More than 150 climatic variables (temperature, precipitation, solar radiation, evapotranspiration, water balance) were obtained using a digital elevation model (DEM) and a geographical information system (GIS). Six direct soil variables (pH, C/N ratio, base saturation rate, concentrations of calcium, magnesium and potassium) were available from EcoPlant, a phytoecological data base for French forests. Using a forward stepwise logistic regression technique, we derived two distinct predictive models for A. campestre ; the first with climatic variables alone and the second with both climatic and edaphic variables.
Results  The distribution of A. campestre was poorly modelled when including only climatic variables. The inclusion of edaphic variables significantly improved the quality of predictions for this species, allowing prediction of patches of presence/absence within the study region.
Main conclusion  Soil nutritional variables may improve the performance of fine-scale (grain) plant species distribution models.     

Modelling the distribution of a threatened habitat: the California sage scrub

Aim Using predictive species distribution and ecological niche modelling our objectives are: (1) to identify important climatic drivers of distribution at regional scales of a locally complex and dynamic system – California sage scrub; (2) to map suitable sage scrub habitat in California; and (3) to distinguish between bioclimatic niches of floristic groups within sage scrub to assess the conservation significance of analysing such species groups. Location Coastal mediterranean‐type shrublands of southern and central California. Methods Using point localities from georeferenced herbarium records, we modelled the potential distribution and bioclimatic envelopes of 14 characteristic sage scrub species and three floristic groups (south‐coastal, coastal–interior disjunct and broadly distributed species) based upon current climate conditions. Maxent was used to map climatically suitable habitat, while principal components analysis followed by canonical discriminant analysis were used to distinguish between floristic groups and visualize species and group distributions in multivariate ecological space. Results Geographical distribution patterns of individual species were mirrored in the habitat suitability maps of floristic groups, notably the disjunct distribution of the coastal–interior species. Overlap in the distributions of floristic groups was evident in both geographical and multivariate niche space; however, discriminant analysis confirmed the separability of floristic groups based on bioclimatic variables. Higher performance of floristic group models compared with sage scrub as a whole suggests that groups have differing climate requirements for habitat suitability at regional scales and that breaking sage scrub into floristic groups improves the discrimination between climatically suitable and unsuitable habitat. Main conclusions The finding that presence‐only data and climatic variables can produce useful information on habitat suitability of California sage scrub species and floristic groups at a regional scale has important implications for ongoing efforts of habitat restoration for sage scrub. In addition, modelling at a group level provides important information about the differences in climatic niches within California sage scrub. Finally, the high performance of our floristic group models highlights the potential a community‐level modelling approach holds for investigating plant distribution patterns.     

The role of land cover in bioclimatic models depends on spatial resolution

Aim We explored the importance of climate and land cover in bird species distribution models on multiple spatial scales. In particular, we tested whether the integration of land cover data improves the performance of pure bioclimatic models. Location Finland, northern Europe. Methods The data of the bird atlas survey carried out in 1986–89 using a 10 × 10 km uniform grid system in Finland were employed in the analyses. Land cover and climatic variables were compiled using the same grid system. The dependent and explanatory variables were resampled to 20‐km, 40‐km and 80‐km resolutions. Generalized additive models (GAM) were constructed for each of the 88 land bird species studied in order to estimate the probability of occurrence as a function of (1) climate and (2) climate and land cover variables. Model accuracy was measured by a cross‐validation approach using the area under the curve (AUC) of a receiver operating characteristic (ROC) plot. Results In general, the accuracies of the 88 bird–climate models were good at all studied resolutions. However, the inclusion of land cover increased the performance of 79 and 78 of the 88 bioclimatic models at 10‐km and 20‐km resolutions, respectively. There was no significant improvement at the 40‐km resolution. In contrast to the finer resolutions, the inclusion of land cover variables decreased the modelling accuracy at 80km resolution. Main conclusions Our results suggest that the determinants of bird species distributions are hierarchically structured: climatic variables are large‐scale determinants, followed by land cover at finer resolutions. The majority of the land bird species in Finland are rather clearly correlated with climate, and bioclimate envelope models can provide useful tools for identifying the relationships between these species and the environment at resolutions ranging from 10 km to 80 km. However, the notable contribution of land cover to the accuracy of bioclimatic models at 10–20‐km resolutions indicates that the integration of climate and land cover information can improve our understanding and model predictions of biogeographical patterns under global change.     

Bioclimatic constraints to Andean cat distribution: a modelling application for rare species

Aim To identify the bioclimatic niche of the endangered Andean cat (Leopardus jacobita), one of the rarest and least known felids in the world, by developing a species distribution model. Location South America, High Andes and Patagonian steppe. Peru, Bolivia, Chile, Argentina. Methods We used 108 Andean cat records to build the models, and 27 to test them, applying the Maxent algorithm to sets of uncorrelated bioclimatic variables from global databases, including elevation. We based our biogeographical interpretations on the examination of the predicted geographic range, the modelled response curves and latitudinal variations in climatic variables associated with the locality data. Results Simple bioclimatic models for Andean cats were highly predictive with only 3–4 explanatory variables. The climatic niche of the species was defined by extreme diurnal variations in temperature, cold minimum and moderate maximum temperatures, and aridity, characteristic not only of the Andean highlands but also of the Patagonian steppe. Argentina had the highest representation of suitable climates, and Chile the lowest. The most favourable conditions were centrally located and spanned across international boundaries. Discontinuities in suitable climatic conditions coincided with three biogeographical barriers associated with climatic or topographic transitions. Main conclusions Simple bioclimatic models can produce useful predictions of suitable climatic conditions for rare species, including major biogeographical constraints. In our study case, these constraints are also known to affect the distribution of other Andean species and the genetic structure of Andean cat populations. We recommend surveys of areas with suitable climates and no Andean cat records, including the corridor connecting two core populations. The inclusion of landscape variables at finer scales, crucially the distribution of Andean cat prey, would contribute to refine our predictions for conservation applications.     

小五台亚高山草甸与生境关系分析

该文结合野外植被调查,在获取更为详细的景观尺度生境数据基础上,探讨了小五台亚高山草甸植物群落与直接环境因子之间的定量关系。典范对应分析(CCA)的结果表明:1) 在小五台的亚高山草甸分布地段,热量、养分和水分条件构成了其生境特征差异的基本格局;2) 用效应温度和太阳直接辐射量所表征的热量因子,指示出研究区植物群落最基本的分化,说明热量条件是制约研究区草甸群落分布的最重要的因子;3) 养分状况的差异,除了说明生境条件本身的差异外,也在一定程度上指示了放牧干扰对群落分布的影响;4) 由地形等因素控制的土壤表层水分状况,则反映了草甸植物群落分布所受到的水分条件影响。     

Inselbergs in a changing world — global trends

Abstract. Based on a review of recent literature, this paper puts forward hypotheses for global trends of inselbergs (isolated mountains) with regard to: (a) their bioclimatic position in relation to the surroundings; (b) their potential for providing habitat niches; and (c) human impacts that may influence ecological processes. This review takes a landscape-level perspective and highlights the challenges ahead in view of changing environmental conditions. Recognizing that inselbergs per se are composed of different microhabitats relative to their surroundings, inselbergs are hypothesized to be bioclimatic 'islands' of xeric conditions in a humid matrix in tropical and temperate regions, and 'islands' of mesic conditions in arid regions. The bioclimatic status of intermediate positions along this global axis (e.g. semiarid and subtropical savanna regions) is less clear. Here, other environmental variables may be of greater importance (microhabitat composition, size of inselberg, distance to other mountain habitats and biogeographical influences). Whether or not biotic communities match these hypothesized physical and bioclimatic trends warrants investigation and could contribute to explaining global species diversity patterns. Invasion of alien species in tropical and Mediterranean-climate regions, and altered fire regimes and resource use pose threats to inselberg communities. Their role as sources of native species to recolonize disturbed surroundings is important in degraded semiarid and arid regions. A generalized model is proposed hypothesizing possible processes between inselberg habitats and disturbed areas in their surroundings in different climatic regions. This model may help to direct further research towards substantiating these perceived trends.     

Bioclimatic Modeling of Southern African Bioregions and Biomes Using Bayesian Networks

This study uses Bayesian networks (BNs) to simulate the spatial distribution of southern African biomes and bioregions using bioclimatic variables. Two Tree-Augmented Naïve (TAN) BN models were parameterized from 23 bioclimatic variables using the expectation-maximization (EM) algorithm. Using sensitivity analyses, the relative influence of each variable was determined using the mutual information from which six bioclimatic variables were selected for the final models. Precipitation of the warmest quarter and extra-terrestrial solar radiation was found to be the most influential variables on both bioregion and biome distributions. Isothermality was the least influential bioclimatic variable at both bioregion and biome levels. Overall correspondence was very high at 93.8 and 87.1% for biomes and bioregions, respectively, whereas classification errors were obtained in transition areas indicating the uncertainties associated with vegetation mapping around margins. The findings indicate that southern African bioregions and biomes can be classified and mapped according to key bioclimatic variables. Spatio-temporal, in particular, monthly and quarterly variations in both precipitation and temperature are found to be ecologically significant in determining the spatial distribution of biomes and bioregions. The findings also reflect the hierarchical relationship of biomes and bioregions as a function of local bioclimatic gradients and interactions. The results indicate the ecological significance of bioclimatic conditions in ecosystem science and offer the opportunity to utilize the models for predicting future responses and sensitivities to climatic changes.     

Bioclimatic analysis of disjunct populations of the giant burrowing frog, Heleioporus australiacus

Aim A bioclimatic analysis of the giant burrowing frog was conducted to determine if the northern and southern populations have distinct climatic profiles and to determine if the disjunction in the species records is a result of a climatically unsuitable area. Location The study utilized records throughout the species range in south‐eastern Australia. Methods The bioclim package was used to examine the climatic envelope of the species, as well as envelopes for the southern and northern populations. Principal components analysis (PCA) was used in an attempt to refine the model. Results The package predicted the observed gap between the populations as climatically suitable in all of the models. The northern populations were found in warmer and wetter sites than the southern populations. River valleys and coastal lowlands were generally unsuitable climatically for the species. Main conclusions The area of the observed disjunction is climatically suitable for both the northern and southern populations. Large river valleys appear to have played a significant role in determining the distribution of the species. PCA was used successfully to alter the model, however further research is needed to determine which is the most accurate approach.     

Modeling a solar radiation topoclimatology for the Rio Grande River Basin

Abstract. Key components in the climatology of the Earth are incoming and net solar radiation. Next to clouds, the major modulator of solar radiation at the surface is topography. Variability in elevation, slope, aspect, and shadowing can lead to large gradients in incoming and net solar radiation fields. The response of vegetation to these gradients can often be dramatic, as in the distribution of vegetation on south- and north-facing slopes. Recently much progress has been made in modeling the effects of topography on incoming and net solar radiation. Such models produce fields of radiation that have been adjusted for topography derived from digital elevation data. This paper presents a topographic solar radiation model that combines digital elevation data with surface and satellite measurements. Specifically, a monthly topoclimatology for the Rio Grande River Basin in Colorado is constructed for the hydrological years 1987 - 1990. Using digital elevation models with 30 m x 30 m grid spacing, representing a mosaic of 39 U.S. Geological Survey 1:24 000 Quadrangles, a digital representation of the watershed is created. Hourly pyranometer measurements taken nearby the basin are then used with satellite reflectances to drive the solar radiation model. The results are monthly maps at 30 m x 30 m grid spacing covering the entire basin that show considerable variability by location and season. Such maps may be useful for vegetation modeling, especially for pattern analysis and ecosystem process modeling.     

Niche-based modelling as a tool for predicting the risk of alien plant invasions at a global scale

Predicting the probability of successful establishment of plant species by matching climatic variables has considerable potential for incorporation in early warning systems for the management of biological invasions. We select South Africa as a model source area of invasions worldwide because it is an important exporter of plant species to other parts of the world because of the huge international demand for indigenous flora from this biodiversity hotspot. We first mapped the five ecoregions that occur both in South Africa and other parts of the world, but the very coarse definition of the ecoregions led to unreliable results in terms of predicting invasible areas. We then determined the bioclimatic features of South Africa's major terrestrial biomes and projected the potential distribution of analogous areas throughout the world. This approach is much more powerful, but depends strongly on how particular biomes are defined in donor countries. Finally, we developed bioclimatic niche models for 96 plant taxa (species and subspecies) endemic to South Africa and invasive elsewhere, and projected these globally after successfully evaluating model projections specifically for three well‐known invasive species (Carpobrotus edulis, Senecio glastifolius, Vellereophyton dealbatum) in different target areas. Cumulative probabilities of climatic suitability show that high‐risk regions are spatially limited globally but that these closely match hotspots of plant biodiversity. These probabilities are significantly correlated with the number of recorded invasive species from South Africa in natural areas, emphasizing the pivotal role of climate in defining invasion potential. Accounting for potential transfer vectors (trade and tourism) significantly adds to the explanatory power of climate suitability as an index of invasibility. The close match that we found between the climatic component of the ecological habitat suitability and the current pattern of occurrence of South Africa alien species in other parts of the world is encouraging. If species' distribution data in the donor country are available, climatic niche modelling offers a powerful tool for efficient and unbiased first‐step screening. Given that eradication of an established invasive species is extremely difficult and expensive, areas identified as potential new sites should be monitored and quarantine measures should be adopted.     

Bioclimatic model of tree radial growth: application to the French Mediterranean Aleppo pine forests

The potential effects of global changes on forests are of increasing concern. Dendrochronology, which deals with long-term records of tree growth under natural environmental conditions, can be used to evaluate the impact of climatic change on forest productivity. However, assessment of climatic change impacts must be supported by accurate and reliable models of the relationships between climate and tree growth. In this study, a bioclimatic model is used to explore the relationships between tree radial growth and bioclimatic variables closely related to the biological functioning of a tree. This model is at an intermediate level of complexity between purely empirical and process-based models. The method is illustrated with data for 21 Aleppo pine (Pinus halepensis Mill.) stands grown under a Mediterranean climate in south-east France. The results show that Aleppo pine growth is mainly controlled by soil water availability during the growing season. The bioclimatic variable which best expresses the observed inter-annual tree growth variations is the actual evapotranspiration (AET). Four parameters were adjusted to simulate dendrochronological data: the soil water capacity, the wilting point, the minimum temperature for photosynthesis, and the end of the growing season. The bioclimatic model gives better results than the standard response function and provides better insight into the functional processes involved in tree growth. The convincing results obtained by the bioclimatic model as well as the limited numbers of parameters it requires demonstrate the feasibility of using it to explore future climatic change impacts on Aleppo pine forests.     

Application of Predictive Distribution Modelling to Invertebrates: Odonata in South Africa

The application of distributional modelling techniques to invertebrates has seldom been explored, primarily due to a lack in adequate distributional data for these taxa. Here, we have selected a simple modelling approach for the generation of distribution maps from a limited dataset, as a first step to the atlassing of Odonata in South Africa. The BIOCLIM-type approach was selected for this purpose, as it requires minimal data for model building and validation procedures. BIOCLIM partitions an area climatically prior to survey, and predicts species distributions on a bioclimatic basis. Conservative deterministic models were developed using point presence/absence data for each of the regions' 160 described species. These models were validated by cross-validation, and the Jaccard coefficient of similarity was used as an index of model performance. A sensitivity analysis investigated the influence of extreme values and errors in the data on predictive ability. Models identified disjunct distribution patterns and accurately predicted the restricted ranges of habitat-specialist species. However, models overstated the distribution of habitat generalists and species with distinct outlier records. For accurate predictions of broad-ranging species, it is suggested that a probabilistic approach be adopted. Nevertheless, basic distribution patterns generated through this conservative approach can be further applied to the investigation of species richness and issues relating to conservation, such as reserve design. The BIOCLIM-type approach provided a means of predicting species distributions, allowing for broad-scale atlassing and thereby providing the first step towards Odonata conservation in South Africa.     

Forest pattern,climate and vulcanism in central North Island,New Zealand

Abstract. A quantitative study of relationships between forest pattern and environment in the central North Island, New Zealand, is based on forest composition data from ca. 2000 existing plots distributed throughout the forests of the region. Estimates of mean annual temperature, rainfall, and solar radiation are derived for each plot from mathematical surfaces fitted to climate station data. Estimates of the depth of the last major rhyolitic eruption, (Taupo Pumice, ca. 130 AD) are derived from isopach maps. A classification procedure is used to identify broad compositional groups. Generalised linear models are used to examine relationships between major species and climatic and other physical factors. Significant relationships are identified between the distributions of both plot groups and species, and climate, vulcanism, topography and drainage. Among these factors, temperature and/or solar radiation are indicated as major determinants of the regional forest pattern, with rainfall, topography, and drainage acting at a secondary level. The role of the Taupo Pumice eruption is more difficult to interpret, and its effects seem to have been greatly influenced by topography. Deep extensive deposits of tephra on flat-to-rolling sites close to the eruption centre have probably favoured the current dominance of these sites by more rapidly dispersing conifers. In contrast, on adjacent steep sites where forest destruction was likely to be less severe, slow-dispersing Nothofagus species are largely dominant. Further work is needed to understand the factors favouring conifer dominance of the central basins and the degree to which Nothofagus species might expand their range in the future.     

Step‐less models for regional environmental variation in Norway

Aim To assess the scale of variation for major environmental gradients in Norway. To obtain a step‐less model for this variation and to use this model to evaluate the extent to which the consensus expert classification of Norway into vegetation regions can be predicted from environmental variables. To discuss the potential of step‐less models for understanding natural variation at regional scales, for stratification and for predictive modelling of species distributions and land‐cover types. Location The mainland of Norway. Methods Fifty‐four climatic, topographical, hydrological and geological variables were recorded for grid cells with spatial resolution (grain size) of 1 × 1, 5 × 5 and 10 × 10 km, spanning the entire mainland of Norway. Principal components analyses (PCA) were used to summarize variation in three primary data matrices and three random subsets of these. Results The first four principal components explained between 75% and 85% of the variation in the data sets. All PCAs revealed four consistent environmental gradients, in order of decreasing importance: (1) regional variation (gradient) from coast to inland and from oceanic/humid to continental areas; (2) regional variation from north to south and from high to low altitudes; (3) regional variation from north to south and from inland to coast, related to solar radiation; and (4) topographic (terrain relief) variation on finer scales than (1–3). The first two PCA axes corresponded to the two bioclimatic gradients used in expert classifications of Norway into biogeographical regions: vegetation sections (from highly oceanic to slightly continental) and vegetation zones (from nemoral to alpine). Main conclusions Our PCA analyses substantiate the current view of bioclimatic regional vegetation variation in Norway, provide an explicit characterization of this variation in terms of climatic variables, and show that environmental variability can be reproduced as GIS layers in step‐less models. These models have the potential to become important tools for future predictive modelling within resource management, conservation planning and biogeographical (and other ecological) research.     

Geographical gradients in seed mass in relation to climate

Aim To determine whether latitudinal and longitudinal gradients in seed mass are related to variation in climatic features including temperature, solar radiation and rainfall. Location Australia. Methods Seed mass was estimated from over 1600 provenances covering the latitudinal and longitudinal extents of 34 perennial Glycine taxa in Australia. Climatic data were obtained from ANUCLIM 5.1 for collection locations based on long‐term meteorological records across Australia. These climatic data were subject to principal components analysis to extract three components as climatic indices. Generalized linear models were used in three separate sets of analyses to evaluate whether seed mass–latitude and seed mass–longitude relationships persisted after taking climatic variation into account. First, relationships were examined across species in analyses that did not explicitly consider phylogenetic relationships. Secondly, phylogenetic regressions were performed to examine patterns of correlated evolutionary change throughout the Glycine phylogeny. Within‐species analysis was also performed to examine consistency across different taxonomic levels. Results Geographical variation in seed mass among species was related primarily to temperature and solar radiation, while rainfall was much less influential upon seed mass. Partialing out the influence of temperature and solar radiation in models resulted in the disappearance of significant seed mass–latitude and seed mass–longitude relationships. Patterns within species were generally consistent with patterns among species. However, in several species, factors additional to these climatic variables may contribute to the origin and maintenance of geographical gradients in seed mass, as significant seed mass–latitude and seed mass–longitude relationships remained after controlling for the influence of climatic variables. Main conclusions Our empirical results support the hypotheses that (1) seed mass is larger at low latitudes and in the interior of the Australian continent due to increased metabolic costs at high temperatures, and that (2) higher levels of solar radiation result in an increase in the availability of photosynthate, which in turn leads to an increase in biomass for the production of large seeds. In effect, our findings show that greater energy is available precisely where needed, that is, where high temperatures require large seed mass on the basis of metabolic requirements.     

Biological invasion on an oceanic island mountain: Do alien plant species have wider ecological ranges than native species?

Abstract. Spatial distribution patterns of alien plant species were compared with those of native species on a windward slope of Mt. Haleakala (3055 m). Oceanic islands are considered susceptible to biological invasion, and this study numerically tested this circumstantial evidence with the following questions: Are all habitats equally susceptible; and, do successful invaders have wider realized niches than natives? The mountain slope consists of three distinct altitudinal bioclimatic zones (hot moist lowland, wet montane cloud, and cool arid high-altitude zones). Ordination indicated that alien species' ranges and population expansions were clustered in the lowland and high-altitude zones. The lowland zone had been subjected to natural canopy dieback, and the high-altitude zone to grazing by domestic and feral ungulates. By contrast, the montane cloud forest was relatively intact in terms of number and cover of native species. Thus, susceptibility to alien invasion clearly differed among zones, and the primary causes seemed to be the obvious disturbance factors. The mean ecological range along the altitude-rainfall gradient was significantly (P < 0.05) greater for native than for alien species in most life-form groups. The reasons for the greater number of climate generalists among the natives vs. the range-restricted aliens appear to be related to: (1) the pre-alien condition with a depauperate flora which allowed for ‘ecological release’ of successful native colonizers, and (2) the climatic pre-adaptation of alien invaders which restricts them from penetrating over a broader spectrum of climatic zones in a floristic matrix subjected to increasing interspecific competition.     

Predicting the distribution of shrub species in southern California from climate and terrain-derived variables

Abstract. Generalized additive, generalized linear, and classification tree models were developed to predict the distribution of 20 species of chaparral and coastal sage shrubs within the southwest ecoregion of California. Mapped explanatory variables included bioclimatic attributes related to primary environmental regimes: averages of annual precipitation, minimum temperature of the coldest month, maximum temperature of the warmest month, and topographically-distributed potential solar insolation of the wettest quarter (winter) and of the growing season (spring). Also tested for significance were slope angle (related to soil depth) and the geographic coordinates of each observation. Models were parameterized and evaluated based on species presence/absence data from 906 plots surveyed on National Forest lands. Although all variables were significant in at least one of the species’ models, those models based only on the bioclimatic variables predicted species presence with 3–26% error. While error would undoubtedly be greater if the models were evaluated using independent data, results indicate that these models are useful for predictive mapping – for interpolating species distribution data within the ecoregion. All three methods produced models with similar accuracy for a given species; GAMs were useful for exploring the shape of the response functions, GLMs allowed those response functions to be parameterized and their significance tested, and classification trees, while some-times difficult to interpret, yielded the lowest prediction errors (lower by 3–5%).