The effectiveness of marine reserve systems constructed using different surrogates of biodiversity

Biological sampling in marine systems is often limited, and the cost of acquiring new data is high. We sought to assess whether systematic reserves designed using abiotic domains adequately conserve a comprehensive range of species in a tropical marine inter‐reef system. We based our assessment on data from the Great Barrier Reef, Australia. We designed reserve systems aiming to conserve 30% of each species based on 4 abiotic surrogate types (abiotic domains; weighted abiotic domains; pre‐defined bioregions; and random selection of areas). We evaluated each surrogate in scenarios with and without cost (cost to fishery) and clumping (size of conservation area) constraints. To measure the efficacy of each reserve system for conservation purposes, we evaluated how well 842 species collected at 1155 sites across the Great Barrier Reef seabed were represented in each reserve system. When reserve design included both cost and clumping constraints, the mean proportion of species reaching the conservation target was 20–27% higher for reserve systems that were biologically informed than reserves designed using unweighted environmental data. All domains performed substantially better than random, except when there were no spatial or economic constraints placed on the system design. Under the scenario with no constraints, the mean proportion of species reaching the conservation target ranged from 98.5% to 99.99% across all surrogate domains, whereas the range was 90–96% across all domains when both cost and clumping were considered. This proportion did not change considerably between scenarios where one constraint was imposed and scenarios where both cost and clumping constraints were considered. We conclude that representative reserve systems can be designed using abiotic domains; however, there are substantial benefits if some biological information is incorporated.     

The Effect of Incremental Reserve Design and Changing Reservation Goals on the Long-Term Efficiency of Reserve Systems

Abstract:  Selecting reserve areas based on percentages, such as 10% or 12% of a bioregion, is common in conservation planning despite widespread admission that such percentages are arbitrary and likely to be inadequate for the conservation of all biodiversity. Reserve systems based on these relatively low percentage targets are likely to require expansion in the future, resulting in the assembly of reserve systems over many years (incremental reserve design). How then will incremental reserve design, such as increasing percentage targets over time, affect the long-term efficiency of marine reserve systems? We used South Australia as a case study to investigate how changing percentage targets affects the contribution of individual planning units to efficient reserve design. Selection frequency counts provided a measure of a planning unit's conservation value. For the majority of planning units, changing targets led to a change in their conservation value indicating, for example, that planning units identified as high-value sites at a low-percentage conservation target may be of lesser importance when targets are increased. Despite the variability in the value of individual planning units at different targets, there was no loss in efficiency from incremental design of reserve systems based on systematic methods compared with purpose-built reserve systems (i.e., the system is assembled in a single iteration). The exception was when incrementally designed systems were based on South Australia's existing marine reserve system—a system developed in an ad hoc method. The result was reserve systems that were less efficient, less compact, and larger in size. This suggests that systematic approaches have an important role for efficient reserve design when there is uncertainty about the target level of reservation .     

Level of Geographical Subdivision and Its Effects on Assessments of Reserve Coverage: A Review of Regional Studies

Land classes such as vegetation types, ecoregions, or environmental domains can be defined in many ways and at many scales. We set out to quantify the influence of the level of subdivision of land classes on the extent to which the classes are represented in reserves. We examined data on the occurrence of land classes at two or more levels of subdivision in many regional reserve systems. Reserve coverage (the percentage of land classes represented in reserve systems) usually changed as the classes were defined more finely. The extent and general direction of change depended on the reservation threshold or percentage area of land classes needed in the reserve system before they were called "reserved." The results indicate the need to qualify assessments of reserve coverage as dependent on the level of subdivision. They also raise the question of the most appropriate levels of subdivision for such assessments. A definitive answer requires more research on the informativeness of land classes about the biota.     

Ad Hoc Reservations: Forward or Backward Steps in Developing Representative Reserve Systems?

A major reason for land reservation has been the relative lack of value of selected sites for major commercial land uses or for human habitation. Other important reasons include scenery, recreation, tourist potential, the influence of lobby groups, and historical protection for uses such as hunting or water supply. There are two main disadvantages of such ad hoc approaches to reserve planning. One is the bias in the content of regional reserve systems, leaving some species, communities, or ecosystems without protection, often the ones most in need of strict reservation. The second is that ad hoc reservations can make the goal of representing regional biodiversity more expensive, reducing the likelihood of protecting many elements of biodiversity. Ad hoc approaches to reservation persist despite clearly stated representation goals, improving data bases, and systematic techniques for reserve selection. The main causes need to be understood and addressed if the potential value of reservation for protecting biodiversity is to be realized.     

A Procedure for Making Optimal Selection of Input Variables for Multivariate Environmental Classifications

Abstract:  Multivariate classifications of environmental factors are used as frameworks for conservation management. Although classification performance is likely to be sensitive to choice of input variables, these choices have been subjective in most previous studies. We used the Mantel test on a limited set of sites for which biological data were available to iteratively seek a definition of environmental space (i.e., intersite distances calculated with a set of appropriately transformed and weighted environmental variables) that had maximal correlation with the same sites described in a biological space. The procedure was used to select input variables for a classification of New Zealand's rivers that discriminates variation in fish communities for biodiversity management. The classification performed (i.e., discriminated biological variation) better than classifications with subjectively chosen variables. The inherently linear measures of environmental distance that underlie multivariate environmental classifications mean that they will perform best if they are defined based on variables for which there is a linear variation in the biological community throughout the entire range of the variable. Classification performance will therefore be improved when variables that have nonlinear relationships with biological variation are transformed to make their relationship with biological turnover more linear and when the contributions of environmental factors that have particularly strong relationships with biological variation are increased by weighting. Our results indicate that attention to the manner in which environmental space is defined improves the efficacy of multivariate classification and other techniques in which the environment is used as a surrogate for biological variation.     

Designing the Masoala National Park in Madagascar Based on Biological and Socioeconomic Data

Abstract: Conservation biologists have developed powerful tools for reserve selection and design over the past two decades, yet seldom are protected areas actually designed on scientific grounds. Using fundamental biological and socioeconomic principles of conservation science, we designed a new protected area and its multiple-use zone on the Masoala Peninsula in the humid forest zone of Madagascar. The explicit design criteria determined the data gathered for the work, which included (1) spatial distribution and quality of habitat, (2) the areas and species at greatest risk, (3) the relationship between environmental gradients and species distributions, (4) current and predicted human settlement and land and resource use, and (5) the economic potential of natural forest management as an alternative to deforestation. We used a geographic information system to integrate these data layers and applied the design criteria to develop a park proposal that balanced human and wildlife needs. The proposal won the approval of local residents, and a national decree in 1997 designated 2100 km² of rainforest and three satellite marine reserves as the Masoala National Park, with a surrounding multiple-use zone of approximately 1000 km². The new park is Madagascar's largest protected area and protects more lowland (<400 m) humid forest habitat than the entire reserve system combined, a significant step forward in conserving a globally important ecoregion. Consideration of local needs and the national economy was a key element in gaining approval for the Masoala Park. Such an approach toward reserve design could be applied elsewhere to improve chances of establishing and maintaining protected areas over the long term.     

Habitat Suitability Models and the Shortfall in Conservation Planning for African Vertebrates

Abstract:  Ongoing loss of biodiversity requires identifying large-scale conservation priorities, but the detailed information on the distribution of species required for this purpose is often missing. We present a systematic reserve selection for 1223 African mammals and amphibians in which habitat suitability models are used as estimates of the area occupied by species. In the framework of the World Conservation Union (IUCN) Global Amphibian Assessment and IUCN Global Mammal Assessment, we collected the geographic range (extent of occurrence) and habitat preferences for each species. We used the latter to build species-specific habitat suitability models inside geographic ranges, and for 181 species we verified the models by comparing suitability levels to presence-absence data collected in the field. We then used the suitable areas as estimators of the area of occupancy and compared the results of systematic reserve selection based on geographic ranges to those based on estimated areas of occupancy. Our results showed that the reserve system would need a 30-100% expansion to achieve minimal conservation targets, concentrated in the tropics, where species richness reaches a maximum. Comparative analyses revealed that using geographic ranges, which overestimate the area occupied by species, underestimates the total amount of area that needs to be conserved. The area selected for conservation doubled when we used the estimated area of occupancy in place of the geographic ranges. This happened because the suitable areas potentially occupied by each species overlapped less than their geographic ranges. As a result, any given protected area contained fewer species than predicted by the analysis of ranges. Because species are more specialized than our estimates of distribution based on extent of occurrence suggest, we propose that this is a general effect in systematic conservation planning.     

Factors influencing incidental representation of previously unknown conservation features in marine protected areas

Spatially explicit information on species distributions for conservation planning is invariably incomplete; therefore, the use of surrogates is required to represent broad‐scale patterns of biodiversity. Despite significant interest in the effectiveness of surrogates for predicting spatial distributions of biodiversity, few researchers have explored questions involving the ability of surrogates to incidentally represent unknown features of conservation interest. We used the Great Barrier Reef marine reserve network to examine factors affecting incidental representation of conservation features that were unknown at the time the reserve network was established. We used spatially explicit information on the distribution of 39 seabed habitats and biological assemblages and the conservation planning software Marxan to examine how incidental representation was affected by the spatial characteristics of the features; the conservation objectives (the minimum proportion of each feature included in no‐take areas); the spatial configuration of no‐take areas; and the opportunity cost of conservation. Cost was closely and inversely correlated to incidental representation. However, incidental representation was achieved, even in a region with only coarse‐scale environmental data, by adopting a precautionary approach that explicitly considered the potential for unknown features. Our results indicate that incidental representation is enhanced by partitioning selection units along biophysical gradients to account for unknown within‐feature variability and ensuring that no‐take areas are well distributed throughout the region; by setting high conservation objectives that (in this case >33%) maximize the chances of capturing unknown features incidentally; and by carefully considering the designation of cost to planning units when using decision‐support tools for reserve design. The lessons learned from incidental representation in the Great Barrier Reef have implications for conservation planning in other regions, particularly those that lack detailed environmental and ecological data.     

Effects of connectivity and spatial resolution of analyses on conservation prioritization across large extents

The outcome of analyses that prioritize locations for conservation on the basis of distributions of species, land cover, or other elements is influenced by the spatial resolution of data used in the analyses. We explored the influence of data resolution on prioritization of Finnish forests with Zonation, a software program that ranks the priority of cells in a landscape for conservation. We used data on the distribution of different forest types that were aggregated to nine different resolutions ranging from 0.1 × 0.1 km to 25.6 × 25.6 km. We analyzed data at each resolution with two variants of Zonation that had different criteria for prioritization, with and without accounting for connectivity and with and without adjustment for the effect on the analysis of edges between areas at the project boundary and adjacent areas for which data do not exist. Spatial overlap of the 10% of cells ranked most highly when data were analyzed at different resolutions varied approximately from 15% to 60% and was greatest among analyses with similar resolutions. Inclusion of connectivity or edge adjustment changed the location of areas that were prioritized for conservation. Even though different locations received high priority for conservation in analyses with and without accounting for connectivity, accounting for connectivity did not reduce the representation of different forest types. Inclusion of connectivity influenced most the outcome of fine-resolution analyses because the connectivity extents that we based on dispersal distances of typical forest species were small. When we kept the area set aside for conservation constant, representation of the forest types increased as resolution increased. We do not think it is necessary to avoid use of high-resolution data in spatial conservation prioritization. Our results show that large extent, fine-resolution analyses are computationally feasible, and we suggest they can give more flexibility to implementation of well-connected reserve networks.     

Examining Fragmentation and Loss of Primary Forest in the Southern Bahian Atlantic Forest of Brazil with Radar Imagery

Abstract: The Atlantic rainforest of southern Bahia is one of the last remnants of the lowland forest of eastern Brazil that once covered the entire coastal area from Rio Grande do Norte to Rio Grande do Sul ( lat 8°–28° S) and has been deforested to a small fraction of its original cover (1–12%). All recent vegetation surveys have been based on optical satellite data, which is hampered by cloud cover and by southern Bahia's intricate mix of forest patches with other tree crops, especially cocoa. We describe the application of radar remote-sensing data to distinguish forest patches from cocoa planted in the shade of natural-forest trees. Radar, unlike optical sensors, is not obstructed by cloud cover and can acquire information about forest structure by penetrating into the vegetation canopy. The vegetation map generated from radar data clearly separates forest patches based on the degree of structural disturbance such as the density of shaded trees, the openness of the canopy, and the density of the monodominant Erythyrina shaded trees. The structural classification based on the radar data, and shown on the map, can help researchers assess the degree of fragmentation of the original Atlantic coastal forest and delineate areas of less disturbance with higher potential for conservation of biodiversity. This information can then be applied to conservation planning, especially the design and monitoring of nature reserves and the modeling of biological corridors.     

Managing Biodiversity in a Forestry Environment

In forest management and other land-use planning, ecological, social, and economical demands often conflict. Forest planning in particular has been biased towards maximizing economic output while disregarding the ecological effects of forestry practices. In this paper we present an approach for taking biological diversity into account in strategic forest management planning. We used the Analytic Hierarchy Process (AHP) method for resource allocation and priority setting. We carried out a case study, whereby a set of management strategies was evaluated in order to identify the strategy which best fulfills the requirement of maintaining biological diversity while at the same time yielding a reasonable income from timber production. We discuss applicability of the approach in solving different forest management and conservation planning problems, as well as in assessment of ecological impacts.     

Surrogates for Macrofungi and Mosses in Reservation Planning

Abstract: Our knowledge of cryptogam taxonomy and species distributions is currently too poor to directly plan for their conservation. We used inventory data from four distinct vegetation types, near Hobart Tasmania, to address the proposition that vegetation type, vascular plant taxon composition, and environmental variables can act as surrogates for mosses and macrofungi in reservation planning. The four vegetation types proved distinct in their taxon composition for all macrofungi, mosses, and vascular plants. We tested the strength of the relationships between the composition of cryptogam taxonomic groups and vascular plant composition and between the environmental variables and canopy cover. Taxon composition of woody vascular plants and vascular plants was the best predictor of the taxon composition of mosses and macrofungi. Combinations of environmental variables and canopy cover were also strong predictors of the taxon composition of mosses and macrofungi. We used an optimization routine for vascular plant taxa and woody plant species and determined the representation of cryptogam taxa in these selections. We identified sites with approximately 10% and 30% of the greatest proportions of vascular plants and woody vascular plants and calculated representation of mosses and macrofungi at these sites. We compared the results of these site selections with random site selections and random selections stratified by vegetation type. Random selection of sites by vegetation type generally captured more cryptogams than site selection by vascular plants at the 10% level. Vascular plant and woody plant taxon composition, vegetation type, and environmental and structural characteristics, all showed promise as surrogates for capturing common cryptogams in reserve systems.     

Habitat classification modeling with incomplete data: pushing the habitat envelope.

Habitat classification models (HCMs) are invaluable tools for species conservation, land-use planning, reserve design, and metapopulation assessments, particularly at broad spatial scales. However, species occurrence data are often lacking and typically limited to presence points at broad scales. This lack of absence data precludes the use of many statistical techniques for HCMs. One option is to generate pseudo-absence points so that the many available statistical modeling tools can bb used. Traditional techniques generate pseudo-absence points at random across broadly defined species ranges, often failing to include biological knowledge concerning the species-habitat relationship. We incorporated biological knowledge of the species-habitat relationship into pseudo-absence points by creating habitat envelopes that constrain the region from which points were randomly selected. We define a habitat envelope as an ecological representation of a species, or species feature's (e.g., nest) observed distribution (i.e., realized niche) based on a single attribute, or the spatial intersection of multiple attributes. We created HCMs for Northern Goshawk (Accipiter gentilis atricapillus) nest habitat during the breeding season across Utah forests with extant nest presence points and ecologically based pseudo-absence points using logistic regression. Predictor variables were derived from 30-m USDA Landfire and 250-m Forest Inventory and Analysis (FIA) map products. These habitat-envelope-based models were then compared to null envelope models which use traditional practices for generating pseudo-absences. Models were assessed for fit and predictive capability using metrics such as kappa, threshold-independent receiver operating characteristic (ROC) plots, adjusted deviance (D(adj)2), and cross-validation, and were also assessed for ecological relevance. For all cases, habitat envelope-based models outperformed null envelope models and were more ecologically relevant, suggesting that incorporating biological knowledge into pseudo-absence point generation is a powerful tool for species habitat assessments. Furthermore, given some a priori knowledge of the species-habitat relationship, ecologically based pseudo-absence points can be applied to any species, ecosystem, data resolution, and spatial extent.     

Pastoralism,nature conservation and ecological sustainability in Western Australia's southern shrubland rangelands

Two major issues are discussed in this paper. The first is the commitment of Federal and State Governments to the maintenance of biodiversity and nature conservation through their endorsement of conservation strategies. Based on a rangeland biophysical resource inventory survey (Pringle et al., 1994) it is contended that existing nature conservation reserves are not representative of the biological diversity in the region. In 1990, less than 1% of the survey area was under nature reservation. Whilst 13 of 17 land types are present in reserves, most of the reserves consist of land types least suitable for pastoralism (but not necessarily lacking conservation value). The land types most subject to preferential grazing and most threatened from a nature conservation perspective are poorly (three types) or not (four types) represented, and certainly not replicated, in nature reserves of the survey area, which exceeds 100 000 km2. Of the 23 priority plant species for nature conservation occurring in the survey area, 21 are not known to occur in nature reserves. Nature conservation in the area needs to improve because of the unrepresentativeness of the existing nature reserves and the absence of numerous priority plant species for nature conservation from these areas. We should recognize that reservation is but one nature conservation strategy. Viewed as a land tenure issue, this paper presents a case for a more representative nature reserve system, and substantial changes in outlook towards off-reserve nature conservation. First, an integrated appraisal of findings from rangeland and biological surveys is required. Together they provide a strong foundation for nature conservation planning, from which a more representative nature reserve system can be planned. Given that off-reserve nature conservation values are still likely to be substantial, partly as a result of compromise with existing land uses, new approaches to land management, sensitive to these values, may be required.The second major issue concerns the success of maintaining regional biological diversity in the arid shrubland rangelands of Western Australia, which will be strongly influenced by the use of the semi-natural matrix of lands under pastoral management. In six suggested opportunities, this paper addresses how this use may be achieved. Central to the ideas is a regional approach in which all stakeholders can contribute to, and have ownership of, regional environmental management plans. This paper emphasizes the role that conservative pastoral management might be able to play and some approaches to encourage more widespread participation of pastoralists in nature conservation management.     

Reserve networks based on richness hotspots and representation vary with scale.

While the importance of spatial scale in ecology is well established, few studies have investigated the impact of data grain on conservation planning outcomes. In this study, we compared species richness hotspot and representation networks developed at five grain sizes. We used species distribution maps for mammals and birds developed by the Arizona and New Mexico Gap Analysis Programs (GAP) to produce 1-km2, 100-kmn2, 625-km2, 2500-km2, and 10,000-km2 grid cell resolution distribution maps. We used these distribution maps to generate species richness and hotspot (95th quantile) maps for each taxon in each state. Species composition information at each grain size was used to develop two types of representation networks using the reserve selection software MARXAN. Reserve selection analyses were restricted to Arizona birds due to considerable computation requirements. We used MARXAN to create best reserve networks based on the minimum area required to represent each species at least once and equal area networks based on irreplaceability values. We also measured the median area of each species' distribution included in hotspot (mammals and birds of Arizona and New Mexico) and irreplaceability (Arizona birds) networks across all species. Mean area overlap between richness hotspot reserves identified at the five grain sizes was 29% (grand mean for four within-taxon/state comparisons), mean overlap for irreplaceability reserve networks was 32%, and mean overlap for best reserve networks was 53%. Hotspots for mammals and birds showed low overlap with a mean of 30%. Comparison of hotspots and irreplaceability networks showed very low overlap with a mean of 13%. For hotspots, median species distribution area protected within reserves declined monotonically from a high of 11% for 1-km2 networks down to 6% for 10,000-km2 networks. Irreplaceability networks showed a similar, but more variable, pattern of decline. This work clearly shows that map resolution has a profound effect on conservation planning outcomes and that hotspot and representation outcomes may be strikingly dissimilar. Thus, conservation planning is scale dependent, such that reserves developed using coarse-grained data do not subsume fine-grained reserves. Moreover, preserving both full species representation and species rich areas may require combined reserve design strategies.     

Effectiveness of Environmental Surrogates for the Selection of Conservation Area Networks

Abstract:  Rapid biodiversity assessment and conservation planning require the use of easily quantified and estimated surrogates for biodiversity. Using data sets from Québec and Queensland, we applied four methods to assess the extent to which environmental surrogates can represent biodiversity components: (1) surrogacy graphs; (2) marginal representation plots; (3) Hamming distance function; and (4) Syrjala statistical test for spatial congruence. For Québec we used 719 faunal and floral species as biodiversity components, and for Queensland we used 2348 plant species. We used four climatic parameter types (annual mean temperature, minimum temperature during the coldest quarter, maximum temperature during the hottest quarter, and annual precipitation), along with slope, elevation, aspect, and soil types, as environmental surrogates. To study the effect of scale, we analyzed the data at seven spatial scales ranging from 0.01° to 0.10° longitude and latitude. At targeted representations of 10% for environmental surrogates and biodiversity components, all four methods indicated that using a full set of environmental surrogates systematically provided better results than selecting areas at random, usually ensuring that ≥90% of the biodiversity components achieved the 10% targets at scales coarser than 0.02°. The performance of surrogates improved with coarser spatial resolutions. Thus, environmental surrogate sets are useful tools for biodiversity conservation planning. A recommended protocol for the use of such surrogates consists of randomly selecting a set of areas for which distributional data are available, identifying an optimal surrogate set based on these areas, and subsequently prioritizing places for conservation based on the optimal surrogate set.     

Reserve Coverage and Requirements in Relation to Partitioning and Generalization of Land Classes: Analyses for Western New South Wales

The extent to which existing conservation reserves cover or represent the different land classes in a region depends on the scale at which those land classes are defined. In a previous review of regional studies we could not separate the influence on reserve coverage from aspects of scale of classification or mapping. In this study we measured the influence of three aspects of scale on the coverage of existing reserves and the area of new reserves required to represent all land classes. The aspects of scale we used were agglomerative (bottom-up) partitioning, divisive (top-down) partitioning, and generalization of the polygons representing discrete map units. The analyses were based on two existing classifications of a large region. One of these was originally produced at two scales of divisive partitioning. We modified the second classification to produce wide differences in the two other aspects of scale. For all aspects of scale the results confirm that existing reserves in the region tend to represent more coarse- than fine-scale classes, but this depends on the criteria used to determine when classes are "represented." For all aspects of scale, larger total areas of new reserves are needed to represent fine-scale rather than coarse-scale land classes. This trend holds regardless of the minimum proportional area of each land class to be represented but varies with the size of the sites considered reserves. The results reinforce the scale-dependence of assessments of reserve coverage and establish the scale-dependence of assessments of reserve requirements. They also indicate that comparisons of coverage and requirements between regions or in the same region through time must be standardized for type and scale of classification.     

Use of Inverse Spatial Conservation Prioritization to Avoid Biological Diversity Loss Outside Protected Areas

Globally expanding human land use sets constantly increasing pressure for maintenance of biological diversity and functioning ecosystems. To fight the decline of biological diversity, conservation science has broken ground with methods such as the operational model of systematic conservation planning (SCP), which focuses on design and on‐the‐ground implementation of conservation areas. The most commonly used method in SCP is reserve selection that focuses on the spatial design of reserve networks and their expansion. We expanded these methods by introducing another form of spatial allocation of conservation effort relevant for land‐use zoning at the landscape scale that avoids negative ecological effects of human land use outside protected areas. We call our method inverse spatial conservation prioritization. It can be used to identify areas suitable for economic development while simultaneously limiting total ecological and environmental effects of that development at the landscape level by identifying areas with highest economic but lowest ecological value. Our method is not based on a priori targets, and as such it is applicable to cases where the effects of land use on, for example, individual species or ecosystem types are relatively small and would not lead to violation of regional or national conservation targets. We applied our method to land‐use allocation to peat mining. Our method identified a combination of profitable production areas that provides the needed area for peat production while retaining most of the landscape‐level ecological value of the ecosystem. The results of this inverse spatial conservation prioritization are being used in land‐use zoning in the province of Central Finland.     

Species distribution modelling: Does one size fit all? A phytogeographic analysis of Salix in Ontario

Empirical models for predicting the distribution of organisms from environmental data have often focused on principles of ecological niche theory. However, even at large scales, there is little agreement over how to represent the dimensions of a species’ niche. The performance of such models is greatly affected by the nature of species distributional and environmental data. Regional scale distribution models were developed for 30 willow species in Ontario to examine (i) the predictive ability of logistic regression analysis, and (ii) the effects of using different distributional and environmental data sets. Two original measures of model accuracy and over-prediction were employed and evaluated using independent data. Models based on unique combinations of monthly climate data predicted distributions most accurately for all species. Models based on a fixed set of variables, while generating the highest average probabilities of occurrence for certain species with limited ranges, resulted in the greatest under- and over-estimates of willow distributions. Comparisons of models demonstrated climatic patterns among willows of differing habit and habitat. The distribution of dwarf willow species, present only in the Ontario arctic, followed gradients of summer maximum temperatures. The distribution of the tree species in the southerly portions of the province followed gradients of fall and winter minimum temperatures. Regardless of distributional and environmental data input, no algorithm maximized model performance for all species. Individual species models require individual approaches; i.e., the variable selection technique, the set of environmental factors used as predictors, and the nature of species distributional data must be carefully matched to the intended application. An understanding of evolutionary processes enhances the meaningful interpretation of individual species models. Unless sampling bias and species prevalence can be accounted for, models based on collection point data are best used to guide field surveys. While inferred range data may be better suited to determine potential ecological niches, overestimation of species prevalence and environmental tolerance must be recognized. A combination of available distributional data types is recommended to best determine species niches, an important step in developing conservation strategies.     

基于模糊聚类法研究绥宁黄桑自然保护区种子植物多样性与邻近地区之间的关系

通过对绥宁黄桑自然保护区植物多样性与其相邻的其余的9个地区植物多样性进行模糊聚类分析,结果表明,按与其区系关系的密切程度的大小进行排列,与绥宁县黄桑自然保护区的关系的密切从大至小的顺序为：台湾岛〉井冈山〉武夷山〉大罗山〉白云山〉北山〉北仑山〉黄山〉神农架,旨在对植物分类方法的研究作一个有益的尝试,探索一条植物分类的新方法,同时其结果对黄桑自然保护区的经营管理和保护具有一定的实践指导意义．图1,表2,参14．