Landscape and habitat factors affecting cabot's tragopan Tragopan caboti occurrence in habitat fragments.

Cabot's tragopan Tragopan caboti is an endemic and endangered pheasant of the lower montane forests of southeastern China. The typical habitats of the tragopan have been seriously fragmented because of forest management for timber production and farmland reclamation in recent years. The effects of the fragment size and isolation on the distribution of the cabot's tragopan were studied in Wuyanling Natural Reserve. Thirty one habitat fragments (2.5-48.5 ha) surrounded by non-habitat sapling coniferous forests, in an intensively managed forested landscape, were surveyed over four seasons for the occurrence of cabot's tragopan. Five of the 31 fragments were occupied in all four seasons and nine were not occupied. Both landscape and habitat factors affected the occurrence of cabot's tragopan, with landscape factors having the greatest effect. Large and less isolated habitat fragments containing a larger amount of the tree Daphniphyllum macropodum were occupied significantly more often than small, isolated fragments. The appearance of cabot's tragopan in the habitat fragments was best explained by the size of the fragments, the distance to the nearest suitable habitat and the amount of macropdous daphniphyllum trees. Our results could be used to improve the management of the forests where Cabot's tragopan occurs in southeastern China.     

超级居群：连接生境多样性和生物多样性之桥

在达尔文（1859）看来,新物种只有通过竞争或者自然选择的方式淘汰原有物种才能进入由其他物种占据的生境并成功定居下来。然而,新物种进入生境并成功定居还有另外一个途径,那就是由于超级居群能在全球尺度上改变整个地球环境,从而能在原有环境中创造出一些全新的微环境来,正是这些全新的微环境使新物种避开了和原有定居者的剧烈竞争,很容易地进入了一直由其他物种占据的生境中并成功地定居下来。换句话说,超级居群导致了全球环境的分化,导致了全球尺度上的生境多样性。同时,超级居群通过环境的异质化为新物种准备好了很多全新的微环境,新物种在全新的微环境中的成功定居实现了新物种和原有定居者的长期共存。而这种长期共存导致了整个生物圈的生物多样性的增加。超级居群是地球上很多新环境的创造者,是生境多样性和生物多样性之间的桥梁,据此就能很容易地解释新物种为什么不时能和原有定居者共存甚至依赖于原有定居者,从而导致二者间剧烈竞争缺失的现象。     

The influence of sampling scheme and interpolation method on the power to detect spatial effects of forest birds in Ontario (Canada)

Spatial ecology is becoming an increasingly important component of resource management, and the general monitoring of how human activities affect the distribution and abundance of wildlife. Yet most work on the reliability of sampling strategies is based on a non-spatial analysis of variance paradigm, and little work has been done assessing the power of alternative spatial methods for creating reliable maps of animal abundance. Such a map forms a critical response variable for multiple scale studies relating landscape structure to biotic function. The power to reconstruct patterns of distribution and abundance is influenced by sample placement strategy and density, the nature of spatial auto-correlation among points, and by the technique used to extrapolate points into an animal abundance map. Faced with uncertainty concerning the influence of these factors, we chose to first synthesize a model reference system of known properties and then evaluate the relative performance of alternative sampling and mapping procedures using it. We used published habitat associations of tree nesting boreal neo-tropical birds, a classified habitat map from the Manitou Lakes area of northwestern Ontario, and point count means and variances determined from field studies in boreal Canada to create 4 simulated models of avian abundance to function as reference maps. Four point sampling strategies were evaluated by 4 spatial mapping methods. We found mixed-cluster sampling to be an effective point sampling strategy, particularly when high habitat fragmentation was avoided by restricting samples to habitat patches >10 ha in size. We also found that of the 4 mapping methods, only stratified ordinary point kriging (OPK) was able to generate maps that reproduced an embedded landscape-scale spatial effect that reduced nesting bird abundance in areas of higher forest age-class fragmentation. Global OPK was effective only for detecting broader, regional-scale differences. This revised version was published online in July 2006 with corrections to the Cover Date.     

Effects of land ownership and landscape-level factors on rare-species richness in natural areas of southern Ontario,Canada

Surprisingly few studies have considered the extent to which the nature of the ownership of land is associated with differences in biodiversity. We analysed ownership and other landscape-level effects on rare-species richness for both globally- and regionally-rare biota (including birds, herpetofauna, butterflies, mammals, and plants) in 289 designated natural areas (NAs) in southern Ontario, Canada. Information about each NA −including area, number of plant communities, ownership status and details of species diversity were collected from published sources. Length of perimeter of NA, relative isolation, and an estimate of fragmentation were measured using image analysis and GIS techniques. NAs were in general relatively small, with mean area of 158 ha (median 85 ha, range from 0.9 to 1278 ha) for private NAs; public NAs had mean area of 132 ha (median 16 ha, range from 0.1 to 1481 ha). Mean number of plant communities was 4.6 (median 4, range 1- 13) at private NAs and 3.8 (median 3, range 1-16) at public NAs. Our results show that, of several landscape-level factors, area had the greatest effects on rare-species richness and other biotic indices. Effects of area were followed by effects of plant community diversity, however this was itself significantly affected by area and the extent of perimeter of the NA. Both these factors were followed by effects of ownership of the NA and by effects of isolation of the NA (represented by minimum distance to nearest NA and by number of NAs in 10 km radius). Other landscape- level factors did not appear to have overall significant effects. Variation in area accounted for 0.1% to 29% of variation in number of rare species, with lower values for globally-rare, than for regionally-rare taxa. For all biotic groups, public ownership of NAs was associated with significantly greater rare-species richness compared to private ownership, even after other factors such as area were controlled. For all globally-rare biota except butterflies, area of NA had greater effects on rare-species richness than did ownership. Richness of regionally- rare birds was more affected by plant community diversity than by area of NA. Number of recorded plant communities accounted from 2.1% of variation in number of globally-rare plant species to as high as 31% of variation in regionally-rare butterflies. The diversity of plant communities was itself influenced by total site area (accounting for 45% of variation), extent of elongation of the NA, and both external- and interior- edge perimeters. Public NAs had greatest numbers of rare biota and so should be a significant focus for conservation programs. Smaller, privately-owned patches of natural area dominate (by number and area) in this densely populated region and their significance should not be overlooked. This revised version was published online in July 2006 with corrections to the Cover Date.     

Population dynamics and habitat connectivity affecting the spatial spread of populations – a simulation study

In this paper we show how the spatialconfiguration of habitat quality affects the spatial spread of apopulation in a heterogeneous environment. Our main result is thatfor species with limited dispersal ability and a landscape withisolated habitats, stepping stone patches of habitat greatlyincrease the ability of species to disperse. Our results showthat increasing reproductive rate first enables and thenaccelerates spatial spread, whereas increasing the connectivity has aremarkable effect only in case of low reproductive rates. Theimportance of landscape structure varied according to thedemographic characteristics of the population. To show this wepresent a spatially explicit habitat model taking into accountpopulation dynamics and habitat connectivity. The population dynamicsare based on a matrix projection model and are calculated on eachcell of a regular lattice. The parameters of the Leslie matrix dependon habitat suitability as well as density. Dispersal between adjacentcells takes place either unrestricted or with higher probability inthe direction of a higher habitat quality (restricted dispersal).Connectivity is maintained by corridors and stepping stones ofoptimal habitat quality in our fragmented model landscape containinga mosaic of different habitat suitabilities. The cellular automatonmodel serves as a basis for investigating different combinations ofparameter values and spatial arrangements of cells with high and lowquality.This revised version was published online in May 2005 with corrections to the Cover Date.     

Landscape patterns as habitat predictors: building and testing models for cavity-nesting birds in the Uinta Mountains of Utah,USA

The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus),tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified,respectively)compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models. This revised version was published online in July 2006 with corrections to the Cover Date.     

Analysis of the association among three viruses infecting hop in Australia

Associations among Hop latent virus (HpLV), Hop mosaic virus (HpMV), and Apple mosaic virus (ApMV) were assessed in five hop cultivars at four commercial hop-growing regions in Victoria and Tasmania, Australia. The presence or absence of each virus was confirmed by double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA). Spatial patterns of virus-infected plants were characterized using the Spatial Analysis by Distance IndicEs ( sadie ) system of pattern analysis. The association among viruses (occurrence and covariation) was assessed using the Jaccard similarity index, Spearman's rank correlation coefficient, and sadie . The spatial pattern of plants infected by HpLV and HpMV ranged from random to highly aggregated depending upon the cultivar infected and the mean disease incidence. The spatial pattern of plants infected by ApMV was aggregated in six of the seven plots where ApMV was present. A strong positive association between HpLV and HpMV was found in all cultivars at all locations. This association may be the result of the viruses sharing a common aphid vector species, the presence of one virus enhancing the ability of the aphid vector to acquire the other virus either through transencapsidation or influences on virus titre, or mixed infections within source plants. Significant associations, positive or negative, were found less frequently between HpLV and ApMV, and HpMV and ApMV.     

Quantifying patch distribution at multiple spatial scales: Applications to wildlife-habitat models

Multiscale analyses are widely employed for wildlife-habitat studies. In most cases, however, each scale is considered discrete and little emphasis is placed on incorporating or measuring the responses of wildlife to resources across multiple scales. We modeled the responses of three Arctic wildlife species to vegetative resources distributed at two spatial scales: patches and collections of patches aggregated across a regional area. We defined a patch as a single or homogeneous collection of pixels representing 1 of 10 unique vegetation types. We employed a spatial pattern technique, three-term local quadrat variance, to quantify the distribution of patches at a larger regional scale. We used the distance at which the variance for each of 10 vegetation types peaked to define a moving window for calculating the density of patches. When measures of vegetation patch and density were applied to resource selection functions, the most parsimonious models for wolves and grizzly bears included covariates recorded at both scales. Seasonal resource selection by caribou was best described using a model consisting of only regional scale covariates. Our results suggest that for some species and environments simple patch-scale models may not capture the full range of spatial variation in resources to which wildlife may respond. For mobile animals that range across heterogeneous areas we recommend selection models that integrate resources occurring at a number of spatial scales. Patch density is a simple technique for representing such higher-order spatial patterns.     

Associations of fish with various types of littoral habitats in reservoirs

Fish associations with different types of littoral habitats were studied in four canyon‐shaped reservoirs in the Czech Republic in years 2010 and 2011 by gillnets. Two to three habitats per reservoir–beaches (former meadows), stump fields (former forest) and rubble slopes–were defined and sampled along the longitudinal axis of reservoirs. Effects of reservoir, habitat and locality (position along longitudinal axis) on fish biomass, abundance and species structure were tested for juvenile and adult fish separately. Hierarchical analysis of variance revealed that habitats differed significantly in fish biomass and abundance. Redundancy analysis showed that analysed environmental variables had significant influence on fish community structure. Most variability in community structure was explained by reservoir and then by combination of habitat and slope steepness. Locality position had the smallest influence on community structure. For both adult and juvenile fish total abundance and biomass, the most inhabited habitat was beaches; rubble slopes were the least inhabited. Habitat associations differed among species. Among adults, bream Abramis brama, white bream Blicca bjoerkna and roach Rutilus rutilus were associated with beaches and stump fields, whereas perch Perca fluviatilis, ruffe Gymnocephalus cernuus, asp Aspius aspius and pike Esox lucius were associated with rubble slopes. Bream, white bream, bleak Alburnus alburnus, roach, ruffe and pikeperch Sander lucioperca were associated with beaches among juveniles, whereas the only juvenile associated with rubble slopes was perch. We showed that most common species are associated with distinct habitats and also that utilisation of various littoral habitats differs in general.     

Conservation planning with dynamic threats: The role of spatial design and priority setting for species’ persistence

Conservation actions frequently need to be scheduled because both funding and implementation capacity are limited. Two approaches to scheduling are possible. Maximizing gain (MaxGain) which attempts to maximize representation with protected areas, or minimizing loss (MinLoss) which attempts to minimize total loss both inside and outside protected areas. Conservation planners also choose between setting priorities based solely on biodiversity pattern and considering surrogates for biodiversity processes such as connectivity. We address both biodiversity processes and habitat loss in a scheduling framework by comparing four different prioritization strategies defined by MaxGain and MinLoss applied to biodiversity patterns and processes to solve the dynamic area selection problem with variable area cost. We compared each strategy by estimating predicted species’ occurrences within a landscape after 20 years of incremental reservation and loss of habitat. By incorporating species-specific responses to fragmentation, we found that you could improve the performance of conservation strategies. MinLoss was the best approach for conserving both biodiversity pattern and process. However, due to the spatial autocorrelation of habitat loss, reserves selected with this approach tended to become more isolated through time; losing up to 40% of occurrences of edge-sensitive species. Additionally, because of the positive correlation between threats and land cost, reserve networks designed with this approach contained smaller and fewer reserves compared with networks designed with a MaxGain approach. We suggest a possible way to account for the negative effect of fragmentation by considering both local and neighbourhood vulnerability to habitat loss.