Assessing the potential impacts of alternative landscape designs on amphibian population dynamics

An individual-based, spatially explicit population model was used to predict the consequences of future land-use alternatives for populations of four amphibian species in two central Iowa (midwest USA) agricultural watersheds. The model included both breeding and upland habitat and incorporated effects of climatic variation and demographic stochasticity. Data requirements of the model include life history characteristics, dispersal behavior, habitat affinities, as well as land use and landcover in geographic information systems databases. Future scenarios were ranked according to change in breeder abundance, saturation, and distribution, compared to baseline conditions. Sensitivity of simulation results to changes in model parameters was also examined. Simulated results suggest that while all four species modeled are likely to persist under present and future scenario conditions, two may be more at risk from future landscape change. Although the study species are all widespread generalists regarded as having a low conservation priority, they depend on wetlands and ponds, increasingly endangered habitats in agricultural landscapes. Broader conservation strategies in the region would ensure that these currently common organisms do not become the endangered species of the future.This revised version was published online in May 2005 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.     

Using behavioral landscape ecology to predict species’ responses to land-use and climate change

Climate change and habitat destruction are widely recognized as major threats to species’ survival. As a result of these anthropogenic impacts, species are often forced into novel landscapes where their persistence is difficult to predict. Knowledge of how individuals move or disperse through the landscape, choose habitat in which to settle, and produce offspring which survive to repeat the process can greatly improve our ability to predict species’ persistence. The field of behavioral landscape ecology uses a strong theoretical base to explore, often experimentally, how the behavior of a particular species is affected by heterogeneous and rapidly changing landscapes and can offer valuable insight for managing species in the face of human-induced environmental changes. When interpreted by modelers, results of landscape-level behavioral experiments can be quantified for use in predictive models. To this end, we summarize the methods and results of research using direct experimental manipulation techniques broken into the following categories: translocations, playback experiments, food resource manipulations, manipulations of reproductive success, direct manipulations of the landscape, and manipulations of predation risk. We review and place in a theoretical framework the results from this emerging body of research regarding how organisms move in and respond to different types of landscapes, both natural and human-altered. We go onto highlight the potential of each experimental method to quantify different processes, which may be useful when interpreted by modelers attempting to parameterize predictive models. Finally, we suggest future directions for experimental research that will allow for greater integration of behavioral landscape ecology and predictive modeling.     

Dispersal of the endangered flightless beetle Dorcadion fuliginator (Coleoptera: Cerambycidae) in spatially realistic landscapes

Habitat destruction and degradation are the major causes for the decline of the endangered grass-feeding beetle Dorcadion fuliginator in Central Europe. In the southern part of the Upper Rhine valley (border region of Switzerland, Germany and France) the habitat suitable for this flightless beetle has been reduced to small remnants of extensively managed dry grassland, usually surrounded by intensively cultivated agricultural fields or settlements. Using a mark-release-resight technique we examined movement patterns in three D. fuliginator populations to obtain basic information on the dispersal ability and longevity of this beetle. Estimated daily survival rates ranged from 88.8% to 90.8% in the populations examined. This corresponds to a mean life span of 10.5 days. Distances moved by D. fuliginator differed among populations. The beetles walked the largest distances in the verges of a field track. Several beetles moved distances of 20-100 m along the track, with a maximum distance of 218 m (a male in 12 days). The shortest displacements were recorded in the bank of the river Rhine, a narrow habitat surrounded by tarmac roads. We also assessed the spatial arrangement of 12 patches with D. fuliginator populations in two regions and estimated the size of each population over 4 years. Data on dispersal, daily survival, population size and spatial arrangement of patches were used to simulate patch-specific migration rates. The simulations suggested that in both areas the beetles regularly moved between neighbouring patches separated by distances shorter than 100 m, whereas patches separated by distances exceeding 500 m are isolated.     

Long-distance plant dispersal and habitat fragmentation: identifying conservation targets for spatial landscape planning under climate change

Climate change presents a potentially severe threat to biodiversity. Species will be required to disperse rapidly through fragmented landscapes in order to keep pace with the changing climate. An important challenge for conservation is therefore to manage landscapes so as to assist species in tracking the environmental conditions to which they are adapted. Here we develop a stochastic spatially explicit model to simulate plant dispersal across artificial fragmented landscapes. Based on certain assumptions as to the dispersal mechanism, we assess the impact that varying potential for rare long-distance dispersal (LDD) has on the ability to move over landscapes with differing spatial arrangements of suitable habitat (clumped versus fragmented). Simulations demonstrate how the relative importance of landscape structure in determining migration ability may decrease as the potential for LDD increases. Thus, if LDD is the principal mechanism by which rapid large-scale migrations are achieved, strategically planned networks of protected habitat may have a limited impact on rates of large-scale plant migrations. We relate our results to conventional principles for conservation planning and the geometric design of reserves, and demonstrate how reversal of these principles may maximise the potential for conservation under future climates. In particular, we caution against the justification of large-scale corridors on grounds of climate change since migration along corridors by standard dispersal mechanisms is unlikely to keep pace with projected change for many species. An improved understanding of the dispersal mechanisms by which species achieve rapid migrations, and the way that these processes are affected by patterns of landscape fragmentation, will be important to inform future conservation strategies.     

The utility and limitations of size and spacing guidelines for designing marine protected area (MPA) networks

Marine protected areas (MPAs) implemented to conserve biodiversity must protect many species with a broad range of movement characteristics. To meet that goal, size and spacing guidelines have been used in MPA network design as a proxy for explicitly representing connectivity and species movement. However, there has been no assessment of the biological effects of these simple rules. We evaluated these guidelines by estimating population persistence with a spatially explicit population model over: (1) an idealized coastline and (2) an example from California, USA. Persistence of a species within an MPA network depends strongly on its movement characteristics; therefore we used the number of combinations of larval dispersal distances and adult home range diameters as an index representing the number of species that could be protected by a MPA network. The index of species protected usually increased steadily with increasing MPA size. By contrast, decreasing MPA spacing only produced large increases in the index when spacing became close enough to allow species persistence via network connectivity rather than self replenishment. Species persistence also depended on the exploitation rate outside MPAs. Size and spacing guidelines are a simple and useful way to begin the MPA network design process, but meeting these guidelines does not guarantee persistence for all populations one may wish to protect. The use of spatially explicit population dynamics models that evaluate population persistence directly provides a more comprehensive basis for comparing proposed MPA network designs.     

基于不相关性的非稳态信号解耦技

对两路非稳态随机实值信号通过一个线性未知系统后得到两路输出信号的解耦问题进行了探讨.首先建立了非稳态信号的两路输入、两路输出系统的数学模型,将系统的解耦问题转换成求解系统的解耦系数问题.然后对解耦系数的求解进行推导,并给出算法适用的必要条件是信号为非稳态和不相关.通过计算出的解耦系数将源信号从测得的输出耦合信号中分离.通过本算法对人工耦合成的两路信号进行了解耦,结果证明了本算法的正确性.最后将算法应用到了研发的差速器检测试验台上,解耦结果满足了工程实际需要.     

Analysis of two variants of a spatially distributed crop model,using wavelet transforms and geostatistics

Models of crop yield are important for the assessment and optimization of agricultural systems. It is therefore necessary that crop models are suitably validated. In many circumstances, a model is required for prediction at a particular spatial scale (e.g. at a within-field scale for precision agriculture), and validation of the model should account for this. We compared spatially explicit methods to validate a grain yield model applied to a transect of 267 contiguous 0.72 × 0.72 m plots on an arable field at Silsoe, eastern England. Grain yield of wheat was determined in each plot during two growing seasons, and a crop model was used to predict the yield retrospectively. We used two variants of the model, each of which used different spatial variables as input. Observed and predicted yield were then compared with non-spatial statistics, but also with wavelet transforms (i.e. the adapted maximal overlap discrete wavelet transform) and geostatistics (i.e. a linear mixed model estimated by residual maximum likelihood). The latter two are spatially explicit statistical methods. The most successful of the variants required as input the daily evolution of leaf-area index in each plot. Validation of this variant with spatial statistics revealed that (i) the variance of the predictions tended to underestimate that of the observations, particularly at relatively coarse spatial scales, however, in relative terms, the distribution of observed variance across scales was described adequately by the model; (ii) the correlation of the predictions with the observations was weak at relatively fine scales but strong at relatively coarse scales; (iii) there was evidence that the correlation of the predictions with the observations was not uniform across the transect at relatively fine scales, which was possibly due to the underlying soil variation; and, (iv) the spatial pattern of model error suggested that some of the fine-scale yield variation, especially in the first growing season, could be attributed to soil compaction, a process not included in the model. These details were not apparent with non-spatial statistics; wavelets and geostatistics are therefore more appropriate tools for validating a spatially distributed crop model. We conclude that this variant of the model is therefore potentially useful for precision agriculture where we need to predict crop behaviour within small management zones, at the scale of tens of metres, but not to predict yield at finer scales. We outline how the most appropriate statistical technique for a particular study depends on whether the observations can be sampled regularly in space, whether we can assume the statistics are uniform across the landscape, the number of spatial scales of interest, and whether interpolation of the predictions, observations, and errors is required.     

Recruitment limitation in forests: Lessons from an unprecedented mountain pine beetle epidemic

Since the mid-1990s the forests of central British Columbia have undergone an unprecedented Mountain Pine Beetle (Dendroctonus ponderosae Hopkins) (MPB) epidemic that has resulted in extensive mortality of canopy lodgepole pine (Pinus contorta var. latifolia Engelm.). This study investigated how seed-source availability, seedbed substrate, overstory structure, and time since MPB attack interact to affect post-MPB seedling recruitment of the dominant tree species of these forests. In addition to post-MPB recruitment, these forests may be regenerated by trees established in the understory prior to MPB disturbance. Accordingly, we examined abundance and patterns of all regeneration less than 130 cm tall. We found post-MPB recruitment was sparse. Subalpine fir (Abies laciocarpa (Hook.) Nutt.) comprised the majority of the post-MPB recruitment. It increased with local parent tree basal area and increased strongly with proximity to a major seed source. This resulted in a patchy distribution for subalpine fir post-MPB regeneration. Lodgepole pine post-MPB recruitment was limited by overstory shading. Recruitment of pine decreased as the total overstory basal area increased. Interior spruce (Picea glauca × engelmannii) post-MPB recruitment was similarly limited by total overstory basal area. Seedbed substrates were uniform and dominated by moss. Substrate type distribution did not change as time since MPB disturbance increased. The overall low post-MPB recruitment observed was likely due to a lack of disturbance to the moss-dominated forest floor. Moss is known to be a poor substrate in northern forests. The distribution of all regeneration less than 130 cm tall showed the same trends as the post-MPB regeneration. We believe the post-MPB seedling recruitment dynamics of these forests was not substantially changed from conditions prior to MPB disturbance. There was no pulse of regeneration up to 10 years post-MPB disturbance. Unless this changes, future stand structure will be dominated by the seedling bank established prior to the MPB epidemic. Subalpine fir dominated the seedling bank (68%) and post-MPB recruitment (94%). This suggests that MPB-disturbed forests are undergoing a substantial shift in landscape-level species composition.     

Long-term adaptation potential of Central European mountain forests to climate change: a GIS-assisted sensitivity assessment

An ecological risk assessment is described for determining the adaptation potential of the approximately 11 000 Swiss Forest Inventory points (FIP) to a hypothetically changing climate. The core of the study is a spatially explicit forest community model that generates estimates of the potential natural vegetation for the entire potential forest area of Switzerland under today's as well as under altered climate regimes. The model is based on the Bayes formula. The probabilities of the communities occurring along ecological gradients are derived from empirical data featuring the relationships between quasi-natural vegetation types and measured site variables. Bioclimatological input variables are the quotient between July temperature and annual precipitation (model version A) or mean annual temperature (model version B). Other site variables include aspect, acidity of top soil and, to account for continentality, geographical region. Climate change scenarios are defined as follows: ‘Moderate climate change’ implies an increase of the mean annual temperature of 4°C to 1.4°C depending on the region (model version B) or an increase of the July temperature of 1.5°C (model version A). ‘Strong climate change’ implies an increase of the mean annual temperature of 2°C to 2.8°C (model version B) or an increase of the July temperature of 3.0°C (model version A).

The simulation experiment showed that the geographical distribution of 15 potential natural forest types (distinguished on the basis of floristic affinities) varies considerably with changing temperature. Under moderate warming 30–55% of the FIP change their potential natural vegetation type, whereas under strong climate change the values increase to 55–89% depending on the model version used. In the ecological risk assessment the existing tree species composition on any FIP was compared with the expected tree species composition under today's as well as under altered climate regimes. A major finding indicated that, under the current climate conditions, approximately 25–30% (depending on the model version used) of all FIP must be considered as poorly adapted, i.e. less than 20% of the actual basal area consists of tree species that are expected as dominating taxa. This definition applies for trees with a diameter at breast height (DBH) ≥ 12 cm. Moderate warming increases the percentage of poorly adapted FIP by 5–10% (relative to all FIP considered), strong warming leads to a 10–30% increase of poorly adapted FIP (relative to all FIP considered). If trees with a DBH < 12cm are considered, the percentage of FIP that have to be classified as poorly adapted is reduced significantly. There are strong regional differences as exhibited in risk maps of 10 km × 10 km resolution.