The human footprint in the west: a large-scale analysis of anthropogenic impacts

Anthropogenic features such as urbanization, roads, and power lines, are increasing in western United States landscapes in response to rapidly growing human populations. However, their spatial effects have not been evaluated. Our goal was to model the human footprint across the western United States. We first delineated the actual area occupied by anthropogenic features, the physical effect area. Next, we developed the human footprint model based on the ecological effect area, the zone influenced by features beyond their physical presence, by combining seven input models: three models quantified top-down anthropogenic influences of synanthropic predators (avian predators, domestic dog and cat presence risk), and four models quantified bottom-up anthropogenic influences on habitat (invasion of exotic plants, human-caused fires, energy extraction, and anthropogenic wildland fragmentation). Using independent bird population data, we found bird abundance of four synanthropic species to correlate positively with human footprint intensity and negatively for three of the six species influenced by habitat fragmentation. We then evaluated the extent of the human footprint in relation to terrestrial (ecoregions) and aquatic systems (major rivers and lakes), regional management and conservation status, physical environment, and temporal changes in human actions. The physical effect area of anthropogenic features covered 13% of the western United States with agricultural land (9.8%) being most dominant. High-intensity human footprint areas (class 8-10) overlapped highly productive low-elevation private landholdings and covered 7% of the western United States compared to 48% for low-intensity areas (class 1-3), which were confined to low-productivity high-elevation federal landholdings. Areas within 1 km of rivers were more affected by the human footprint compared to lakes. Percentage human population growth was higher in low-intensity human footprint areas. The disproportional regional effects of the human footprint on landscapes in the western United States create a challenge to management of ecosystems and wildlife populations. Using footprint models, managers can plan land use actions, develop restoration scenarios, and identify areas of high conservation value at local landscapes within a regional context. Moreover, human footprint models serve as a tool to stratify landscapes for studies investigating floral and faunal response to human disturbance intensity gradients.     

Efficacy of Land-Cover Models in Predicting Isolation of Marbled Salamander Populations in a Fragmented Landscape

Abstract:  Amphibians worldwide are facing rapid declines due to habitat loss and fragmentation, disease, and other causes. Where habitat alteration is implicated, there is a need for spatially explicit conservation plans. Models built with geographic information systems (GIS) are frequently used to inform such planning. We explored the potential for using GIS models of functional landscape connectivity as a reliable proxy for genetically derived measures of population isolation. We used genetic assignment tests to characterize isolation of marbled salamander populations and evaluated whether the relative amount of modified habitat around breeding ponds was a reliable indicator of population isolation. Using a resampling analysis, we determined whether certain land-cover variables consistently described population isolation. We randomly drew half the data for model building and tested the performance of the best models on the other half 100 times. Deciduous forest was consistently associated with lower levels of population isolation, whereas salamander populations in regions of agriculture and anthropogenic development were more isolated. Models that included these variables and pond size explained 65–70% of variation in genetically inferred isolation across sites. The resampling analysis confirmed that these habitat variables were consistently good predictors of isolation. Used judiciously, simple GIS models with key land-cover variables can be used to estimate population isolation if field sampling and genetic analysis are not possible.     

Global rarity of intact coastal regions

Management of the land–sea interface is essential for global conservation and sustainability objectives because coastal regions maintain natural processes that support biodiversity and the livelihood of billions of people. However, assessments of coastal regions have focused strictly on either the terrestrial or marine realm. Consequently, understanding of the overall state of Earth's coastal regions is poor. We integrated the terrestrial human footprint and marine cumulative human impact maps in a global assessment of the anthropogenic pressures affecting coastal regions. Of coastal regions globally, 15.5% had low anthropogenic pressure, mostly in Canada, Russia, and Greenland. Conversely, 47.9% of coastal regions were heavily affected by humanity, and in most countries (84.1%) >50% of their coastal regions were degraded. Nearly half (43.3%) of protected areas across coastal regions were exposed to high human pressures. To meet global sustainability objectives, all nations must undertake greater actions to preserve and restore the coastal regions within their borders.     

Environmental drivers of decadal change of a mangrove forest in the North coast of the Yucatan peninsula,Mexico

Mangrove forests provide important ecosystem services, but are under constant pressure from natural, anthropogenic, and climate change related disturbances. Environmental drivers on mangrove change at large spatial scales, other than sea level rise, are not well understood. In here, we use spatially explicit methods to identify the main environmental drivers of mangrove coverage change over a decade in the landscape of the North coast of the Yucatan peninsula, Mexico. A post-supervised classification approach on seven SPOT 5 multispectral satellite images was used to construct thematic maps of mangrove coverage between 2004 and 2014. A linear regression model between the thematic maps was performed to estimate the mangrove coverage change rate per pixel. Climate surfaces for annual maximum, minimum and mean temperature, and annual mean and cumulative precipitation for the region were calculated for the period 1980–2009 using data obtained from the National Meteorological Service. The effect of environmental variables on mangrove coverage change rates was assessed with a boosted generalized additive model (boosted GAM). The lowest and highest overall accuracy obtained for the time series thematic maps were 87.14% (Kappa?=?0.78), and 97.5% (Kappa?=?0.95), respectively. The most influential environmental variables on mangrove coverage change were annual cumulative precipitation (21%), and annual maximum temperature (9%). Current climate change scenarios for the region predict an increase in temperature and a decrease in precipitation, intensifying environmental stress on this ecosystem. Therefore, adequate management strategies are fundamental to help maintain the mangrove forest under changing environmental conditions.     

Effect of biochar addition on short-term N<Subscript>2</Subscript>O and CO<Subscript>2</Subscript> emissions during repeated drying and wetting of an anthropogenic alluvial soil

Agricultural soils are an important source of greenhouse gases (GHG). Biochar application to such soils has the potential of mitigating global anthropogenic GHG emissions. Under irrigation, the topsoils in arid regions experience repeated drying and wetting during the crop growing season. Biochar incorporation into these soils would change the soil microbial environment and hence affect GHG emissions. Little information, however, is available regarding the effect of biochar addition on carbon dioxide (CO₂) and nitrous oxide (N₂O) emissions from agricultural soils undergoing repeated drying and wetting. Here, we report the results of a 49-day aerobic incubation experiment, incorporating biochar into an anthropogenic alluvial soil in an arid region of Xinjiang Province, China, and measuring CO₂ and N₂O emissions. Under both drying–wetting and constantly moist conditions, biochar amendment significantly increased cumulative CO₂ emission. At the same time, there was a significant reduction (up to ~20 %) in cumulative N₂O emission, indicating that the addition of biochar to irrigated agricultural soils may effectively slow down global warming in arid regions of China.     

Auswahl repräsentativer Standorte zur Modellierung der Ausbreitung von gentechnisch veränderten Pflanzen in Nord-Deutschland

Goal and Scope

The use of genetically modified plants (GMP) in agriculture is increasing rapidly. While GMP in North and South America are already established an extensive cultivation in Germany is yet to come. Risk assessment on possible effects of released GMP are mainly based on empirical studies with a small spatial extent (laboratories, small-scale field trials). The joint research project ‘Generic detection and extrapolation of genetically modified rape (GenEERA)’ aimed at estimating the dispersal and persistence of genetically modified oilseed rape (Brassica napus) by the use of individual based models. The objective of the article at hand is to give a detailed account of the spatial variability of climate in Northern Germany (German Federal States of Brandenburg, Lower Saxony and Bremen Mecklenburg Western Pomerania, Schleswig-Holstein and Hamburg). Based on this, a method was developed that includes both, the determination of representative oilseed rapefields for modelling the dispersal of GM oilseed rape at field scale, and the subsequent generalisation of the results to landscapes.

Data and Methods

The statistically founded selection of modelling sites was performed by a compilation of available indicators within a GIS environment which are supposed to be important for the dispersal and the persistence of oilseed rape. Meteorological data on precipitation (P), air temperature (T), and sunshine duration (S) collected at up to 1,200 monitoring sites from 1961–1990 were as well as data on wind conditions (W) aggregated multivariate-statistically by Ward cluster analysis. An ecoregionalisation was used for characterising Northern Germany ecologically. Phenological data on the start of the oil seed rape bloom differentiated in the monitoring periods 1961–1990 and 1991–1999, respectively, were regionalised by performing variogram analysis and kriging interpolation. These maps were used to select appropriate Landsat images to identify rape fields by remote sensing algorithms as well as to define the respective flowering periods for individual based modelling.

Results

The separately generated P-T-S-W-Cluster were aggregated to four homogenic climatic regions. In combination with agricultural clusters defining typical landuse patterns (crop rotation, cultivation management) eight model regions were derived which describe the climatic and agronomic variations in Northern Germany. For each of these regions a representative monitoring site was selected serving for individual based modelling. At last, the modelling results were extrapolated back to the model regions applying corresponding GIS queries.

Discussion

The generated climatic regions reflect the transition of marine climate at the North Sea to continental climate in Northeast Germany. The shift in flowering of oil seed rape coincides with other studies on phenological changes of agricultural crops and wild plants.

Conclusions

Due to the huge calculation efforts and the lack of adequate land registers it was not possible to simulate the potential dispersal of GM oil seed rape at farm scale. Thus, generalisations were used to describe the variations of relevant ecological drivers affecting the dispersal of GMP. It could be shown that the aggregation of those factors to homogenic climatic regions was a successful approximation.

Recommendations and Perspectives

Due to the limited empirical data base it is necessary to validate and substantiate the modelling results by a GMP monitoring. The EU Directive 2001/18/EC on the deliberate release of genetically modified organisms into the environment stipulates assessment of direct and indirect effects of GMP on humans and the environment by case-specific monitoring and general surveillance. It should be realised as soon as possible, since the release and the cultivation of GMP in Germany have been started, already. The monitoring should be complemented by the implementation of a web-based geoinformation system (WebGIS) which enables access to relevant geodata and monitoring data and assists in analysing possible GMP impacts.     

Modeling Species' Distributions to Improve Conservation in Semiurban Landscapes: Koala Case Study

Abstract:  Models of species' distributions are commonly used to inform landscape and conservation planning. In urban and semiurban landscapes, the distributions of species are determined by a combination of natural habitat and anthropogenic impacts. Understanding the spatial influence of these two processes is crucial for making spatially explicit decisions about conservation actions. We present a logistic regression model for the distribution of koalas (  Phascolarctos cinereus ) in a semiurban landscape in eastern Australia that explicitly separates the effect of natural habitat quality and anthropogenic impacts on koala distributions. We achieved this by comparing the predicted distributions from the model with what the predicted distributions would have been if anthropogenic variables were at their mean values. Similar approaches have relied on making predictions assuming anthropogenic variables are zero, which will be unreliable if the training data set does not include anthropogenic variables close to zero. Our approach is novel because it can be applied to landscapes where anthropogenic variables are never close to zero. Our model showed that, averaged across the study area, natural habitat was the main determinant of koala presence. At a local scale, however, anthropogenic impacts could be more important, with consequent implications for conservation planning. We demonstrated that this modeling approach, combined with the visual presentation of predictions as a map, provides important information for making decisions on how different conservation actions should be spatially allocated. This method is particularly useful for areas where wildlife and human populations exist in close proximity.     

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.     

Metapopulation Extinction Risk under Spatially Autocorrelated Disturbance

Abstract:  Recent extinction models generally show that spatial aggregation of habitat reduces overall extinction risk because sites emptied by local extinction are more rapidly recolonized. We extended such an investigation to include spatial structure in the disturbance regime. A spatially explicit metapopulation model was developed with a wide range of dispersal distances. The degree of aggregation of both habitat and disturbance pattern could be varied from a random distribution, through the intermediate case of a fractal distribution, all the way to complete aggregation (single block). Increasing spatial aggregation of disturbance generally increased extinction risk. The relative risk faced by populations in different landscapes varied greatly, depending on the disturbance regime. With random disturbance, the spatial aggregation of habitat reduced extinction risk, as in earlier studies. Where disturbance was spatially autocorrelated, however, this advantage was eliminated or reversed because populations in aggregated habitats are at risk of mass extinction from coarse-scale disturbance events. The effects of spatial patterns on extinction risk tended to be reduced by long-distance dispersal. Given the high levels of spatial correlation in natural and anthropogenic disturbance processes, population vulnerability may be greatly underestimated both by classical (nonspatial) models and by those that consider spatial structure in habitat alone.     

Spatial variability of biotic and abiotic tree establishment constraints across a treeline ecotone in the Alaska range

Throughout interior Alaska (U.S.A.), a gradual warming trend in mean monthly temperatures occurred over the last few decades (approximatlely 2-4 degrees C). The accompanying increases in woody vegetation at many alpine treeline (hereafter treeline) locations provided an opportunity to examine how biotic and abiotic local site conditions interact to control tree establishment patterns during warming. We devised a landscape ecological approach to investigate these relationships at an undisturbed treeline in the Alaska Range. We identified treeline changes between 1953 (aerial photography) and 2005 (satellite imagery) in a geographic information system (GIS) and linked them with corresponding local site conditions derived from digital terrain data, ancillary climate data, and distance to 1953 trees. Logistic regressions enabled us to rank the importance of local site conditions in controlling tree establishment. We discovered a spatial transition in the importance of tree establishment controls. The biotic variable (proximity to 1953 trees) was the most important tree establishment predictor below the upper tree limit, providing evidence of response lags with the abiotic setting and suggesting that tree establishment is rarely in equilibrium with the physical environment or responding directly to warming. Elevation and winter sun exposure were important predictors of tree establishment at the upper tree limit, but proximity to trees persisted as an important tertiary predictor, indicating that tree establishment may achieve equilibrium with the physical environment. However, even here, influences from the biotic variable may obscure unequivocal correlations with the abiotic setting (including temperature). Future treeline expansion will likely be patchy and challenging to predict without considering the spatial variability of influences from biotic and abiotic local site conditions.     

Mapping shifts in spatial synchrony in grassland birds to inform conservation planning

Spatial synchrony, defined as the correlated fluctuations in abundance of spatially separated populations, can be caused by regional fluctuations in natural and anthropogenic environmental population drivers. Investigations into the geography of synchrony can provide useful insight to inform conservation planning efforts by revealing regions of common population drivers and metapopulation extinction vulnerability. We examined the geography of spatial synchrony and decadal changes in these patterns for grassland birds in the United States and Canada, which are experiencing widespread and persistent population declines. We used Bayesian hierarchical models and over 50 years of abundance data from the North American Breeding Bird Survey to generate population indices within a 2° latitude by 2° longitude grid. We computed and mapped mean local spatial synchrony for each cell (mean detrended correlation of the index among neighboring cells), along with associated uncertainty, for 19 species in 2, 26-year periods, 1968–1993 and 1994–2019. Grassland birds were predicted to increase in spatial synchrony where agricultural intensification, climate change, or interactions between the 2 increased. We found no evidence of an overall increase in synchrony among grassland bird species. However, based on the geography of these changes, there was considerable spatial heterogeneity within species. Averaging across species, we identified clusters of increasing spatial synchrony in the Prairie Pothole and Shortgrass Prairie regions and a region of decreasing spatial synchrony in the eastern United States. Our approach has the potential to inform continental-scale conservation planning by adding an additional layer of relevant information to species status assessments and spatial prioritization of policy and management actions. Our work adds to a growing literature suggesting that global change may result in shifting patterns of spatial synchrony in population dynamics across taxa with broad implications for biodiversity conservation.     

Coral reef habitat mapping: how much detail can remote sensing provide?

The capability of satellite and airborne remote-sensing methods for mapping Caribbean coral reefs is evaluated. Reef habitats were categorised into coarse, intermediate and fine detail, using hierarchical classification of field data (percent cover in 1 m quadrats and seagrass standing-crop). Habitats were defined as assemblages of benthic macro-organisms and substrata and were mapped using the satellite sensors Landsat MSS, Landsat TM, SPOT XS, SPOT Pan and merged Landsat TM/SPOT Pan. Habitats were also mapped using the high-resolution digital airborne sensor, CASI (compact airborne spectrographic imager). To map areas >60 km in any direction with coarse detail, Landsat TM was the most accurate and cost-effective satellite sensor (SPOT XS when <60 km). For maps with intermediate habitat detail, aerial photography (from a comparable study in Anguilla) exhibited similar accuracy to Landsat TM, SPOT XS, SPOT Pan and merged Landsat TM/SPOT Pan. Landsat MSS was consistently the least accurate sensor. Maps from CASI were significantly (p<0.001) more accurate than satellite sensors and aerial photographs. Maps with detailed habitat information (i.e. >9 reef classes) had a maximum accuracy of 37% when based on satellite imagery, but aerial photography and CASI achieved accuracies of 67 and 81%, respectively. Commissioning of new aerial photography does not appear to be a cost-effective option; satellites are cheaper for coarse habitat-mapping, and detailed habitat-mapping can be conducted more accurately and cheaply with CASI. The results will guide practitioners in matching survey objectives to appropriate remote-sensing methods. Received: 11 July 1997 / Accepted: 6 August 1997     

Effect of prior disturbances on the extent and severity of wildfire in Colorado subalpine forests

Disturbances are important in creating spatial heterogeneity of vegetation patterns that in turn may affect the spread and severity of subsequent disturbances. Between 1997 and 2002 extensive areas of subalpine forests in northwestern Colorado were affected by a blowdown of trees, bark beetle outbreaks, and salvage logging. Some of these stands were also affected by severe fires in the late 19th century. During a severe drought in 2002, fires affected extensive areas of these subalpine forests. We evaluated and modeled the extent and severity of the 2002 fires in relation to these disturbances that occurred over the five years prior to the fires and in relation to late 19th century stand-replacing fires. Occurrence of disturbances prior to 2002 was reconstructed using a combination of tree-ring methods, aerial photograph interpretation, field surveys, and geographic information systems (GIS). The extent and severity of the 2002 fires were based on the normalized difference burn ratio (NDBR) derived from satellite imagery. GIS and classification trees were used to analyze the effects of prefire conditions on the 2002 fires. Previous disturbance history had a significant influence on the severity of the 2002 fires. Stands that were severely blown down (> 66% trees down) in 1997 burned more severely than other stands, and young (approximately 120 year old) postfire stands burned less severely than older stands. In contrast, prefire disturbances were poor predictors of fire extent, except that young (approximately 120 years old) postfire stands were less extensively burned than older stands. Salvage logging and bark beetle outbreaks that followed the 1997 blowdown (within the blowdown as well as in adjacent forest that was not blown down) did not appear to affect fire extent or severity. Conclusions regarding the influence of the beetle outbreaks on fire extent and severity are limited, however, by spatial and temporal limitations associated with aerial detection surveys of beetle activity. Thus, fire extent in these forests is largely independent of prefire disturbance history and vegetation conditions. In contrast, fire severity, even during extreme fire weather and in conjunction with a multiyear drought, is influenced by prefire stand conditions, including the history of previous disturbances.     

Intertidal habitat composition and regional-scale shoreline morphology along the Benguela coast

The Benguela Current Large Marine Ecosystem off southwest Africa is a regionally valued system because of its biological productivity, which supports high biomass throughout the foodweb, and a rich diversity of habitats and species. However, the region is exposed to numerous anthropogenic pressures that are likely to escalate under future economic growth. In response, the Benguela Current Commission called for a spatial biodiversity assessment (BCC-SBA) to identify conservation priorities, including potential areas for marine protected areas. The systematic conservation-planning approach to this assessment requires a fine-scale map of coastal habitats, which was not previously available for the region. Our aim was to undertake this mapping, within tight logistic and resource limitations. We used a previously derived methodology for mapping the distribution of coastal habitats from aerial imagery. The Benguela coast is approximately 5,047 km long. Half of this extent is sandy beach, a third is rocky and mixed shores, 13 % comprises lagoonal features, and the remainder (4 %) comprises estuaries and offshore islands. The distribution and extent of these coastal habitats differs substantially alongshore (i.e. with latitude), with conditions ranging north–south from hot, humid mangrove-lined lagoons, to hyper-arid coastal desert sandy beaches. Patterns in regional geology, climate and oceanography are proposed as the main drivers of spatial heterogeneity in coastal habitat types. The resulting ecological and socio-economic wealth requires proactive protection (supported through the BCC-SBA, for example), to ensure sustainable utilization of the rich natural resources, and persistence of these resources for the benefit of current and future generations.     

Background values and distribution trends of Cu and Zn in soils of humid Mediterranean environment

Soil is the foundation of the entire biosphere. Knowledge of its heavy metal content and regional variability is essential to assess the environmental quality of soil and the extent of any contamination. In this study, 250 soil samples (within 125 soil profiles) were collected in undisturbed soils of the La Rioja region (an ideal place of the humid Mediterranean environment of Spain). The ‘total and bioavailable’ contents of copper (Cu) and zinc (Zn) were measured and their spatial variability assessed. The results indicate that Zn and Cu values were found to be very close to national and global averages. The spatial distribution of those elements was related to the nature of the bedrock and, to a lesser extent, was of anthropogenic origin. The variation of vertical distributions can be related, firstly, to natural sources – mainly the bedrock – and, secondly, to soil processes. From an ecological perspective, the ecosystem has not been affected by pollution.     

Realizing the potential of GIS in community-based management of protected areas

SUMMARY

This paper explores the roles GIS technology can play in support of land management, focusing in particular on its application in protected environments such as Biosphere Reserves. These ecologically significant areas present complex planning situations since, unlike areas set aside solely for conservation, they must continue to support human populations that depend on natural resources for their economic and social well being. In situations such as marginal tropical locations, land managers often face major economic and political disincentives to the conservation of precious natural resources. The necessity for community participation and local expertise in the planning process becomes increasingly critical as GIS evolves from a basic presentation aid for spatial data to a synthesizing problem-solving tool. Coupled with enhanced community participation is the opportunity for greater education of stakeholders; the potential for GIS to serve as a medium for information gathering and dissemination is discussed. A case study in the Sierra de Manantlán Biosphere Reserve (SMBR), México, is presented.     

Nest selection by snow petrels Pagodroma nivea in East Antarctica: Validating predictive habitat selection models at the continental scale

Little is known on the factors controlling distribution and abundance of snow petrels in Antarctica. Studying habitat selection through modeling may provide useful information on the relationships between this species and its environment, especially relevant in a climate change context, where habitat availability may change. Validating the predictive capability of habitat selection models with independent data is a vital step in assessing the performance of such models and their potential for predicting species’ distribution in poorly documented areas.From the results of ground surveys conducted in the Casey region (2002–2003, Wilkes Land, East Antarctica), habitat selection models based on a dataset of 4000 nests were created to predict the nesting distribution of snow petrels as a function of topography and substrate. In this study, the Casey models were tested at Mawson, 3800 km away from Casey. The location and characteristics of approximately 7700 snow petrel nests were collected during ground surveys (Summer 2004–2005). Using GIS, predictive maps of nest distribution were produced for the Mawson region with the models derived from the Casey datasets and predictions were compared to the observed data. Models performance was assessed using classification matrixes and Receiver operating characteristic (ROC) curves. Overall correct classification rates for the Casey models varied from 57% to 90%. However, two geomorphologically different sub-regions (coastal islands and inland mountains) were clearly distinguished in terms of habitat selection by Casey model predictions but also by the specific variations in coefficients of terms in new models, derived from the Mawson data sets. Observed variations in the snow petrel aggregations were found to be related to local habitat availability.We discuss the applicability of various types of models (GLM, CT) and investigate the effect of scale on the prediction of snow petrel habitats. While the Casey models created with data collected at the nest scale did not perform well at Mawson due to regional variations in nest micro-characteristics, the predictive performance of models created with data compiled at a coarser scale (habitat units) was satisfactory. Substrate type was the most robust predictor of nest presence between Casey and Mawson. This study demonstrate that it is possible to predict at the large scale the presence of snow petrel nests based on simple predictors such as topography and substrate, which can be obtained from aerial photography. Such methodologies have valuable applications in the management and conservation of this top predator and associated resources and may be applied to other Antarctic, Sub-Antarctic and lower latitudes species and in a variety of habitats.     

Flood-risk mapping for storm surge and tsunami at Cocos Bay (Manzanilla), Trinidad

Cocos Bay is a barrier beach under threat of marine erosion from the high energy environment of the Atlantic Ocean. This barrier beach borders the Ramsar listed Nariva Swamp, and helps maintain its delicate wetland ecosystem, however, ongoing coastal erosion at this beach threatens the longevity of this freshwater wetland. Due to the geographical location of Cocos Bay being exposed to Atlantic generated storm events and the low relief of the study area, there is a potential threat of storm surges breaching the barrier beach. Owing to the geological setting of the region (located in an active seismic province with earthquakes, volcanicity and landslides), there also exists the threat of tsunamis. This paper is a GIS simulation of the area extent of inundation and the affected infrastructure from such events. It utilizes a DEM and land-use to quantifying inundation areas, and the extent of vulnerability of various elements. The low relief of the barrier beach renders the area extremely vulnerable from events that trigger sea level increases. Simulations revealed that as little as a 1 m storm surge has the potential to disrupt the Nariva Swamp and threaten coastal infrastructure while higher storm surges and tsunamis have the potential to decimate the entire area. The flood-risk model generated indicates a very high vulnerability to storm surges, along the entire length of the coastline. These results have implications for future development and sustainable management of this ecologically sensitive area.     

Quantifying landscape-ecological succession in a coastal dune system using sequential aerial photography and GIS

Summary This contribution presents an attempt to measure the path of habitat and vegetation succession in a coastal dune system (Kenfig Burrows, South Wales) using remote sensing and GIS. The loss of slack habitats associated with the continuing stabilization of this dune system is a major cause for concern. These habitats support a range of plant species, including the rare fen orchid,Liparis loeselii, as well as other hydrophytes. A decrease in their areal extent implies a reduction in biodiversity. To quantify the overall rate and spatial dimension of these changes, a series of aerial photographs dating from 1962 to 1994 were digitized and analysed in an image processing system. The resultant maps. transferred to a vector-based GIS, were used to derive a transition matrix for the dune system over this period of time. The results indicate that there has been a marked reduction in the total area of bare sand (19.6% of the dune system in 1962, but only 1.5% in 1994) and a decline in both the areal extent and the number of dune slacks. Over the same period of time, there has been an increase inSalix repens dominated habitats, at the expense of pioneer species. Analysis of the habitat maps, together with hydrological data, within the GIS suggests that even the dry slacks have the potential for further greening and to support invasive species. In terms of habitat management however, there is still scope to restore many of the slacks to their original state. It is estimated that at least 24% of the area occupied by partially and moderately vegetated slacks could be rehabilitated.