Population Dynamics of Songbirds in the Boreal Mixedwood Forests of Alberta,Canada: Estimating Minimum and Maximum Extents of Spatial Population Synchrony

Ecological phenomena vary over space and time and interpretation of these processes also varies depending on the measurement scale. As the spatial scale of observation increases and decreases, changes in population abundance will likely exhibit alternating patterns of asynchrony and synchrony. While the study of how and why population dynamics change with spatial scale of measurement is intrinsically interesting, most population ecologists seek to study mechanisms of population change on a discrete study area. Our study develops methods that population ecologists can use to determine spatially appropriate sampling designs, and demonstrates how such spatial scales can be determined for 25 species of songbirds using long-term data from the boreal mixedwood forest of Alberta, Canada. To determine minimum scales of synchrony in population dynamics, we calculated the average correlation of changes in population abundance over time across different numbers of fixed-radius point-count samples. We then used a randomization test to remove the effect of number of replicates from the determination of appropriate spatial scale. The maximum extent of synchrony was estimated as the distance where population dynamics were no longer correlated. Estimates of the minimum scale of synchrony differed between species, ranging from 3.1 to 18.6 ha. The maximum scale of synchrony was estimated to be greater than or equal to 8 km for 14 of the 25 species examined, and to be greater than or equal to 70 km for Tennessee Warbler (Vermivora peregrina). Maximum spatial extents were significantly correlated with body mass and territory size.     

Demographic network and multi-season occupancy modeling of Rana sylvatica reveal spatial and temporal patterns of population connectivity and persistence

Many populations are spatially structured with frequent extinction–colonization events. A clear understanding of these processes is necessary for making informed and effective management decisions. Due to the spatially and temporally dynamic nature of many systems, population connectivity and local extinction–colonization processes can be difficult to assess, but graph theoretic and occupancy modeling approaches are increasingly being utilized to answer such vital ecological questions. In our study, we used 6 years of egg mass counts from 34 ponds for Rana sylvatica to parameterize spatially explicit demographic network models. Our models revealed that the studied populations have spatial structure with strong source–sink dynamics. We also assessed the colonization and persistence probability of each pond using multi-season occupancy modeling. We observed extreme fluctuation in reproductive effort among years, resulting in variable levels of connectivity across the landscape. Pond colonization and persistence were most influenced by local population dynamics, but colonization was also affected by precipitation. Our demographic network model had moderate ability to predict reproductive effort, but accuracy was hindered by variation in annual precipitation. Source populations had higher colonization and persistence rates as well as a greater proportion of ravine habitat within 1,000 m than sink populations. By linking a spatially explicit connectivity model with a temporal occupancy/persistence model, we provide a framework for interpreting patterns of occupancy and dispersal that can serve as an initial guide for future habitat management and restoration.     

Spatial and temporal analysis of landscape patterns

A variety of ecological questions now require the study of large regions and the understanding of spatial heterogeneity. Methods for spatial-temporal analyses are becoming increasingly important for ecological studies. A grid cell based spatial analysis program (SPAN) is described and results of landscape pattern analysis using SPAN are presentedd. Several ecological topics in which geographic information systems (GIS) can play an important role (landscape pattern analysis, neutral models of pattern and process, and extrapolation across spatial scales) are reviewed. To study the relationship between observed landscape patterns and ecological processes, a neutral model approach is recommended. For example, the expected pattern (i.e., neutral model) of the spread of disturbance across a landscape can be generated and then tested using actual landscape data that are stored in a GIS. Observed spatial or temporal patterns in ecological data may also be influenced by scale. Creating a spatial data base frequently requires integrating data at different scales. Spatial is shown to influence landscape pattern analyses, but extrapolation of data across spatial scales may be possible if the grain and extent of the data are specified. The continued development and testing of new methods for spatial-temporal analysis will contribute to a general understanding of landscape dynamics.     

Assessing Spatial Uncertainty Associated with Forest Fire Boundary Delineation

Uncertainty in managing forested landscapes arises from many sources, including complexities inherent in forest ecosystems and their disturbance processes. However, gaining knowledge about forested ecosystems at the landscape level is often impeded by limitations in collecting comprehensive, representative, as well as accurate data sets. Historical reference data sets about past disturbances are also mostly lacking. In the case of ground fires, however, records of past fires can be obtained by analyzing fire scars using dendrochronology. While the temporal series of disturbance can be determined, there is still uncertainty about the spatial limits of individual forest surface fires. Here, we investigate how a patch-based method (fuzzy set membership) and a boundary-based uncertainty method (boundary membership) can help determine the spatial uncertainty related to forest fire events and their boundary locations. We compare these methods using fire scar data from ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) sampled at 33 1-ha plots in a 1500-ha study area within the Stein River watershed (British Columbia). Patch-based fire maps, using multiple constraints, were derived for years 1785–1937. We compared the resulting total fire event maps with the boundary-based method, finding that depending on values chosen for the patch-based method, negative correlation was present (though very modest: r = − 0.1, p ≤ 0.05) between some maps. However, significant positive correlation between maps (though again modest: r = 0.22, p ≤ 0.05) was found under the least constrained patch-based methods, suggesting that fire patches are counted more than once in riparian zones. Our results suggest that these two methods provide complementary information about historical fire size and spatial limits. Quantifying spatial uncertainty about fire size and fire boundary location using a boundary membership method can contribute to not only understanding past fire regimes but also to providing better estimates of area burned.     

Mapping sources,sinks, and connectivity using a simulation model of northern spotted owls

Source-sink dynamics are an emergent property of complex species–landscape interactions. A better understanding of how human activities affect source-sink dynamics has the potential to inform and improve the management of species of conservation concern. Here we use a study of the northern spotted owl (Strix occidentalis caurina) to introduce new methods for quantifying source-sink dynamics that simultaneously describe the population-wide consequences of changes to landscape connectivity. Our spotted owl model is mechanistic, spatially-explicit, individual-based, and incorporates competition with barred owls (Strix varia). Our observations of spotted owl source-sink dynamics could not have been inferred solely from habitat quality, and were sensitive to landscape connectivity and the spatial sampling schemes employed by the model. We conclude that a clear understanding of source-sink dynamics can best be obtained from sampling simultaneously at multiple spatial scales. Our methodology is general, can be readily adapted to other systems, and will work with population models ranging from simple and low-parameter to complex and data-intensive.     

Ecosystem-level dynamics of soil-vegetation features, with implications for conserving a narrowly endemic reptile

Narrow endemism presents challenges to species occurrence modeling particularly when the distribution of key local habitat features changes across space and time as a function of processes operating at larger scales. One need facing conservation in such settings is a better understanding of the biogeographic dynamics of the larger features that govern occurrence of critical local habitat. The Mescalero–Monahans shinnery sands region of western North America is a dynamic landscape where sand shinnery oak interacts with wind-driven sand to establish dune habitat. This ecosystem supports several narrowly endemic dune-dwelling species including the dunes sagebrush lizard. Using near-anniversary satellite and aerial imagery from 1986, 1998, and 2011, we integrated object-based image classification and statistical analysis to develop and validate a spatially explicit estimate of the sand shinnery oak ecosystem, including dynamics associated with its attrition and emergence, at high resolution throughout an 89,849-km² study area encompassing the range of the dunes sagebrush lizard. The spatial estimate of the distribution and extent of the sand shinnery oak soil-vegetation association validated reasonably well (overall accuracy = 0.79; sensitivity = 0.49; specificity = 0.91) and showed that the association declined 10.3 % in extent during the 25-year assessment window. The presence of sand shinnery oak, patch size, and patch isolation were dynamic across space and time; a regression model showed that smaller, isolated patches on the periphery of the system were more likely to be lost over time whereas larger, less isolated, and centrally distributed patches were more likely to persist or expand. This study details broadly applicable methods to accurately delineate landforms throughout large extents, and offers mapping tools specific to issues surrounding Mescalero–Monahans shinnery sands endemics that are readily amenable to testing, refinement, and application in efforts to focus sustainable landscape management including conservation of endemic species.     

Effects of changing spatial resolution on the results of landscape pattern analysis using spatial autocorrelation indices

Understanding the relationship between pattern and scale is a central issue in landscape ecology. Pattern analysis is necessarily a critical step to achieve this understanding. Pattern and scale are inseparable in theory and in reality. Pattern occurs on different scales, and scale affects pattern to be observed. The objective of our study is to investigate how changing scale might affect the results of landscape pattern analysis using three commonly adopted spatial autocorrelation indices,i.e., Moran Coefficient, Geary Ratio, and Cliff-Ord statistic. The data sets used in this study are spatially referenced digital data sets of topography and biomass in 1972 of Peninsular Malaysia. Our results show that all three autocorrelation indices were scale-dependent. In other words, the degree of spatial autocorrelation measured by these indices vary with the spatial scale on which analysis was performed. While all the data sets show a positive spatial autocorrelation across a range of scales, Moran coefficient and Cliff-Ord statistic decrease and Geary Ratio increases with increasing grain size, indicating an overall decline in the degree of spatial autocorrelation with scale. The effect of changing scale varies in their magnitude and rate of change when different types of landscape data are used. We have also explored why this could happen by examining the formulation of the Moran coefficient. The pattern of change in spatial autocorrelation with scale exhibits threshold behavior,i.e., scale effects fade away after certain spatial scales are reached (for elevation). We recommend that multiple methods be used for pattern analysis whenever feasible, and that scale effects must be taken into account in all spatial analysis.     

Habitat Preferences of Clethrionomys Rufocanus in Boreal Sweden

A long-term decline of vole populations in boreal Sweden, especially of the grey-sided vole (Clethrionomys rufocanus Sund.), has been revealed by snap-trapping in 1971–2004. We identified important habitats for the grey-sided vole by mapping the distribution of cumulated number of reproductive females in 1971–1978, prior to the major decline in the 1980s. Mean abundance of C. rufocanus was higher in the western (inland) than eastern (coastland) part of the study area. As the inland appeared to represent the most, as far as we know, pristine, abundant part of the population, we based identification of high quality habitats on inland data only. Four habitats were more important than others and yielded nearly 86% of the reproductive females in spring: (1) forests of dry, (2) moist and (3) wet/hydric dwarf-shrub type, in addition to (4) forest/swamp complexes rich in dwarf-shrubs. The latter three habitats were used more frequently than expected from their occurrence in the landscape. Still, the variation in density of reproductive females within patches of the same habitat was frequently high. This suggested that habitat composition in the surrounding landscape, perhaps may have affected local vole density at the patch scale. Clear-cut sampling plots appeared to be low-frequently used by reproductive females, but also by males and immatures. In conclusion, our study indicated the importance of also studying habitat at a larger scale than that of the patch to get a deeper understanding on how habitat influences local and regional densities and population dynamics of C. rufocanus.     

Evaluating effects of low quality habitats on regional population growth in <Emphasis Type="Italic">Peromyscus leucopus</Emphasis>: Insights from field-parameterized spatial matrix models

Due to complex population dynamics and source–sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive field-based analyses of demography and migration and spatial matrix models of white-footed mouse (Peromyscus leucopus) population dynamics. We interpret asymptotic population growth rates from these spatial models as fitness-based measures of habitat-quality and use elasticity analysis to further explore model behavior and the roles of migration. In addition, we compare population growth rates at the spatial scale of single habitats and the landscape-level scale at which these habitats are assembled. To this end, we employ emerging techniques in multi-scale estimation of demography and movement and recently described vec-permutation methods for spatial matrix notation and analysis. Our findings indicate that the loss of low quality habitats or reductions in movement from these habitats into higher quality areas could negatively affect landscape-level population fitness.     

Resource landscapes and movement strategy shape Queensland Fruit Fly population dynamics

Context

Animal population dynamics are shaped by their movement decisions in response to spatial and temporal resource availability across landscapes. The sporadic availability and diversity of resources can create highly dynamic systems. This is especially true in agro-ecological landscapes where the dynamic interplay of insect movement and heterogeneous landscapes hampers prediction of their spatio-temporal dynamics and population size.

Objectives

We therefore systematically looked at population-level consequences of different movement strategies in temporally-dynamic resource landscapes for an insect species whose movement strategy is slightly understood: the Queensland Fruit Fly (Bactrocera tryoni)

Methods

We developed a spatially-explicit model to predict changes in population dynamics and sizes in response to varying resources across a landscape. We simulated the temporal dynamics of fruit trees as the main resource using empirical fruiting dates. Movement strategies were derived from general principles and varied in directedness of movement and movement trigger.

Results

We showed that temporal continuity in resource availability was the main contributing factor for large and persistent populations. This explicitly included presence of continuous low-density resources such as fruit trees in urban areas. Analysing trapping data from SE Australia supported this finding. We also found strong effects of movement strategies, with directed movement supporting higher population densities.

Conclusions

These results give insight into structuring processes of spatial population dynamics of Queensland Fruit Fly in realistic and complex food production landscapes, but can also be extended to other systems. Such mechanistic understanding will help to improve forecasting of spatio-temporal hotspots and bottlenecks and will, in the end, enable more targeted population management.

     

Towards a comprehensive framework for modeling urban spatial dynamics

The increasing availability of spatial micro data offers new potential for understanding the micro foundations of urban spatial dynamics. However, because urban systems are complex, induction alone is insufficient. Nonlinearities and path dependence imply that qualitatively new dynamics can emerge due to stochastic shocks or threshold effects. Given the policy needs for managing urban growth and decline and the growing desire for sustainable urban forms, models must be able not only to explain empirical regularities, but also characterize system-level dynamics and assess the plausible range of outcomes under alternative scenarios. Towards this end, we discuss a comprehensive modeling approach that is comprised of bottom-up and top-down models in which both inductive and deductive approaches are used to describe and explain urban spatial dynamics. We propose that this comprehensive modeling approach consists of three iterative tasks: (1) identify empirical regularities in the spatial pattern dynamics of key meso and macro variables; (2) explain these regularities with process-based micro models that link individual behavior to the emergence of meso and macro dynamics; and (3) determine the systems dynamical equations that characterize the relationships between micro processes and meso and macro pattern dynamics. Along the way, we also clarify types of complexity (input and output) and discuss dimensions of complexity (spatial, temporal, and behavioral). While no one to date has achieved this kind of comprehensive modeling, meaningful progress has been made in characterizing and explaining urban spatial dynamics. We highlight examples of this work from the recent literature and conclude with a discussion of key challenges.     

Fractal characterization of Mytilus edulis L. spatial structure in intertidal landscapes using GIS methods

The blue mussel, Mytilus edulis L., forms dense and variable patch mosaics composed of aggregates of mussel individuals. Knowledge of mussel bed spatial pattern at multiple scales is important for understanding the form and function of intertidal systems where mussels are prominent features. This study extends prior work demonstrating fractal patterns of mussel boundaries in soft-bottom systems at the quadrat-scale by investigating fractal structure using GIS methods at both the quadrat- and bed-scales. The study pursues three goals for mussel beds in eastern Maine: (1) to compare quadrat-scale fractal dimensions obtained using manual methods with those obtained using digital imagery and techniques, (2) to determine if fractal patterns identified at the quadrat-scale are also present at the bed-scale, (3) and to evaluate the effectiveness of aerial photography and image analysis techniques. Photographs of randomly located quadrats (2500 cm² each) were scan digitized and classified into mussel presence/absence classes. Fractal dimensions of mussel/non-mussel boundaries were calculated using the box-counting method and compared with results obtained using analog photographs and methods. Digital aerial photographs at low tide were acquired for beds at two sites and classified using image processing techniques, and bed-scale fractal dimensions were calculated. At the quadrat-scale, fractal dimensions and their relationship with percent cover differed consistently in absolute value from results using manual methods but agreed in demonstrating fractal patterns for all quadrats and a parabolic trend with percent cover very similar to the one revealed manually. At the bed-scale, both sites were shown to be fractal, with higher dimension value for the bed that subjectively appeared more fragmented and highly dissected. Because mussels are important soft-bottom ecosystem engineers, i.e., foundation species that regulate species composition and abundances, the fractal spatial distribution identified in this study suggests that the species affected by them also exhibit fractal patterns. These results indicate the effectiveness of archive imagery and GIS methods for characterizing intertidal systems and point to the feasibility of future image acquisition.     

Regeneration Strategies,Disturbance and Plant Interactions as Organizers of Vegetation Spatial Patterns in a Pine Forest

To determine how vegetation pattern in early successional forests may be related to plant traits and types of disturbance, we measured percent cover of individual taxa annually in a South Carolina Pinus elliottii forest, starting one year before, and ending four years after harvest and tree girdling disturbances were applied. The 17 most important taxa surveyed were grouped into four regeneration strategies chosen a priori, and the spatial patterns of these groups and of the soil were investigated using global variability, semivariograms and kriged maps. We also examined spatial correlations across years, across taxa, and between species and soil disturbance. Seed bank taxa represented by Dichanthelium spp. increased rapidly and formed large patches, and then quickly declined. Taxa that regenerate by newly dispersed seeds, represented by Rhus copallina and Rubus spp. occurred at first in a few patches, and became widespread later. Stump sprouters, represented by Quercus spp. and Myrica cerifera, had rapid increases in cover, but their spatial patterns were largely determined by their pre-disturbance patterns. Prunus serotina, which relies on both sprouting and dispersed seed, had moderate cover and a random distribution. Within-species temporal correlation of spatial pattern was lower in girdled than in harvested plots, and was not clearly related to regeneration strategy. Forest floor disturbance was patchy and affected the pattern of Dichanthelium spp. in the harvested plots. Negative correlations between herbs and woody plants in harvested plots reflected the role of biotic (i.e., successional) filters on vegetation pattern. Surprisingly, no spatial correlations were detected between the nitrogen fixer, Myrica cerifera and other taxa in this N-limited system. In comparing the spatial and temporal patterns, we found kriged maps more informative than analysis of semivariograms alone. The maps and correlation statistics demonstrated that regeneration traits, spatial patterns of soil disturbances, and interactions among taxa influence dynamics of the spatial patterns of the plants. We also demonstrated that disturbance types affected the importance and interactions among these three factors, and caused different spatial patterns of the plant taxa.     

Towards a measure of functional connectivity: local synchrony matches small scale movements in a woodland edge butterfly

This study investigates the sensitivity of local synchrony to movement patterns of the Ringlet butterfly (Aphantopus hyperantus). We examine whether population synchrony, describing the correlated fluctuations of conspecific populations, may prove an effective surrogate measure for monitoring functional connectivity in this species without the requirement of exhaustive sampling. We compared the effect on population synchrony of two different distance measures, direct (Euclidean) distance and distance via woodland rides and edges, and also of habitat matrix composition. Population synchrony of A. hyperantus was calculated as the pairwise correlation between population time-series using 20?years of data from UK butterfly monitoring scheme transects. Local population synchrony was better explained by distance via woodland edges than direct distance, especially for woodland-dominated transects. These results are consistent with mark-recapture data previously collected on the Ringlet butterfly. The results indicate a sensitivity of population synchrony to butterfly local dispersal behaviour, particularly, to the use of habitat corridors and other functional dispersal routes. Population synchrony is considered to have potential as a surrogate measure of functional connectivity. With development, this method could become a valuable conservation tool for identifying important landscape features which promote species?? connectivity.     

Effects of spatial habitat heterogeneity on habitat selection and annual fecundity for a migratory forest songbird

Understanding how spatial habitat patterns influence abundance and dynamics of animal populations is a primary goal in landscape ecology. We used an information-theoretic approach to investigate the association between habitat patterns at multiple spatial scales and demographic patterns for black-throated blue warblers (Dendroica caerulescens) at 20 study sites in west-central Vermont, USA from 2002 to 2005. Sites were characterized by: (1) territory-scale shrub density, (2) patch-scale shrub density occurring within 25 ha of territories, and (3) landscape-scale habitat patterns occurring within 5 km radius extents of territories. We considered multiple population parameters including abundance, age ratios, and annual fecundity. Territory-scale shrub density was most important for determining abundance and age ratios, but landscape-scale habitat structure strongly influenced reproductive output. Sites with higher territory-scale shrub density had higher abundance, and were more likely to be occupied by older, more experienced individuals compared to sites with lower shrub density. However, annual fecundity was higher on sites located in contiguously forested landscapes where shrub density was lower than the fragmented sites. Further, effects of habitat pattern at one spatial scale depended on habitat conditions at different scales. For example, abundance increased with increasing territory-scale shrub density, but this effect was much stronger in fragmented landscapes than in contiguously forested landscapes. These results suggest that habitat pattern at different spatial scales affect demographic parameters in different ways, and that effects of habitat patterns at one spatial scale depends on habitat conditions at other scales.     

Spatial prediction of caterpillar (<Emphasis Type="Italic">Ormiscodes</Emphasis>) defoliation in Patagonian <Emphasis Type="Italic">Nothofagus</Emphasis> forests

In the temperate forests of the southern Andes, southern beech species (Nothofagus), the dominant tree species of the region, experience severe defoliation caused by caterpillars of the Ormiscodes genus (Lepidoptera: Saturniidae). Despite the recent increase in defoliation frequency in some areas, there is no quantitative information on the spatial extent and dynamics of these outbreaks. This study examines the spatial patterns of O. amphimone outbreaks in relation to landscape heterogeneity. We mapped defoliation events caused by O. amphimone in northern (ca. 40–41°S) and southern Patagonian (ca. 49°S) Nothofagus forests from Landsat imagery and analyzed their spatial associations with vegetation cover type, topography (elevation, slope angle, aspect) and mean annual precipitation using overlay analyses. We used these data and relationships to develop a logistic regression model in order to generate maps of predicted susceptibility to defoliation by O. amphimone for each study area. Forests of N. pumilio are typically more susceptible to O. amphimone outbreaks than lower elevation forests of other Nothofagus species (N. dombeyi and N. antarctica). Stands located at intermediate elevations and on gentle slopes (<15°) are also more susceptible to defoliation than higher and lower elevation stands located on high angle slopes. Stands in areas with intermediate to high precipitation, relative to the distribution of Nothofagus along the precipitation gradient, are more susceptible to O. amphimone attack than are drier areas. Our study represents the first mapping and spatial analysis of insect defoliator outbreaks in Nothofagus forests in South America.     

Accuracy of fractal dimension estimates for small samples of ecological distributions

We carry out a simulation study of the estimation of fractal dimension in a grid-based setting typical of ecological species distributions, using null landscape models. We calculate the box-counting dimension for samples taken in various types of sampling geometry. Sampler geometries include simple blocks,Cantor grids and line transects. This method may be used to measure fractal dimension of a species distribution, but the accuracy depends on a number of criteria. The most important is sampling effort: any estimate will be inaccurate if the sampling effort is low. We also find the geometry of the sampler to be important. For a given sampling effort, schemes based on the Cantor grids performed better than either line transects or simple blocks. Sampling effort can be improved either by using a bigger sampler over a larger area or by repeated sampling of a smaller area: optimum performance is often a trade-off between these two mechanisms. However, performance is also highly sensitive to the type of fractal object being sampled, with certain types of object requiring a much greater effort for an accurate estimate of fractal dimension. These results raise the possibilities of using novel sampling techniques to estimate fractal dimension, when confronted with limited resources and time, but underline also the need for an understanding of the “type” of fractality expected in ecological situations. This revised version was published online in July 2006 with corrections to the Cover Date.     

Introducing spatial grazing impacts into the prediction of moorland vegetation dynamics

Grazing by large herbivores is a major determinant of vegetation dynamics in many semi-natural ecosystems, including ghe replacement of heather moorland by rough grassland in the British uplands. Herbivore foraging is influenced by vegetation patterns and, in turn, their grazing drives vegetation dynamics. Although vegetation impacts are local, spatially heterogeneous local impacts can have different conseqences as would the same impact distributed uniformly. We constructed a simulation model of the spatial effects of grazing by sheep on the vegetation dynamics of heather moorland, a vegetation community of international conservation importance in the UK. The model comprised three sub-models to predict (1) annual average heather utilisation, (2) spatial variation in heather utilisation (higher near the edge of grass patches) and (3) competition between heather and grass. Here we compare the predicted heather utilisation and vegetation dynamics of the spatial model, relative to those of a non-spatial model. The spatial model resulted in a reduced loss of heather cover for a given sheep stocking rate. The model demonstrtaes how spatial interactions between large herbivores and their forage drive vegetation dynamics, leading to changes in community structure and composition. Indeed, omitting spatial effects in grazing models may lead to inaccurate predictions. We have shown that ecosystem modelling, based around an iterative dialogue between developers and experienced researchers, has the potential to make a substantial contribution towards the conservation and management of vulnerable landscapes. Combining modelling with experimental studies will facilitate progress towards understanding long-term vegetation/herbivore dynamics.