Landscape-Genetic Analysis of Population Structure in the Texas Gray Fox Oral Rabies Vaccination Zone

In west-central Texas, USA, abatement efforts for the gray fox (Urocyon cinereoargenteus) rabies epizootic illustrate the difficulties inherent in large-scale management of wildlife disease. The rabies epizootic has been managed through a cooperative oral rabies vaccination program (ORV) since 1996. Millions of edible baits containing a rabies vaccine have been distributed annually in a 16-km to 24-km zone around the perimeter of the epizootic, which encompasses a geographic area >4 x 105 km2. The ORV program successfully halted expansion of the epizootic into metropolitan areas but has not achieved the ultimate goal of eradication. Rabies activity in gray fox continues to occur periodically outside the ORV zone, preventing ORV zone contraction and dissipation of the epizootic. We employed a landscape-genetic approach to assess gray fox population structure and dispersal in the affected area, with the aim of assisting rabies management efforts. No unique genetic clusters or population boundaries were detected. Instead, foxes were weakly structured over the entire region in an isolation by distance pattern. Local subpopulations appeared to be genetically non-independent over distances >30 km, implying that long-distance movements or dispersal may have been common in the region. We concluded that gray foxes in west-central Texas have a high potential for long-distance rabies virus trafficking. Thus, a 16-km to 24-km ORV zone may be too narrow to contain the fox rabies epizootic. Continued expansion of the ORV zone, although costly, may be critical to the long-term goal of eliminating the Texas fox rabies virus variant from the United States.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Spatial and temporal analysis of land cover and landscape structure change in Zagros Forests

The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.

The Aeolian Flux of Calcium, Chloride and Nitrate to the McMurdo Dry Valleys Landscape: Evidence from Snow Pit Analysis

We have determined the flux of calcium, chloride and nitrate to the McMurdo Dry Valleys region by analysing snow pits for their chemical composition and their snow accumulation using multiple records spanning up to 48 years. The fluxes demonstrate patterns related to elevation and proximity to the ocean. In general, there is a strong relationship between the nitrate flux and snow accumulation, indicating that precipitation rates may have a great influence over the nitrogen concentrations in the soils of the valleys. Aeolian dust transport plays an important role in the deposition of some elements (e.g. C(2+)) into the McMurdo Dry Valleys' soils. Because of the antiquity of some of the soil surfaces in the McMurdo Dry Valleys regions, the accumulated atmospheric flux of salts to the soils has important ecological consequences. Although precipitation may be an important mechanism of salt deposition to the McMurdo Dry Valley surfaces, it is poorly understood because of difficulties in measurement and high losses from sublimation.

Cultural landscape report for the Vanderbilt Mansion formal gardens : Vanderbilt Mansion National Historic Site, Hyde Park, New York : site history, existing conditions, analysis and evaluation, treatment /

Includes bibliographical references.

Integrated Ecological Modeling and Decision Analysis Within the Everglades Landscape

Planning for complex ecosystem restoration projects involves integrating ecological modeling with analysis of performance trade-offs among restoration alternatives. The authors used the Everglades Landscape Model and Multi-Criteria Decision Analysis to explore the effect of simulated ecosystem performance, risk preferences, and criteria weights on the ranking of three alternatives to restoring overland sheet flow in the Everglades. The ecological model outputs included both hydrologic and water quality criteria. Results were scored in the decision analysis framework, highlighting the trade-offs between hydrologic restoration and water quality constraints. Given equal weighting of performance measures, the alternative with more homogenous sheet flow was preferred over other alternatives, despite evidence of some localized eutrophication risk.

Land-cover detection and landscape structure analysis in the Pachitea Basin, Peruvian Amazon

Classification procedures, including atmospheric correction satellite images as well as classification performance utilizing calibration and validation at different levels, have been investigated in the context of a coarse land-cover classification scheme for the Pachitea Basin. Two different correction methods were tested against no correction in terms of reflectance correction towards a common response for pseudo-invariant features (PIF). The accuracy of classifications derived from each of the three methods was then assessed in a discriminant analysis using crossvalidation at pixel, polygon, region, and image levels. Results indicate that only regression adjusted images using PIFs show no significant difference between images in any of the bands. A comparison of classifications at different levels suggests though that at pixel, polygon, and region levels the accuracy of the classifications do not significantly differ between corrected and uncorrected images. Spatial patterns of land-cover were analyzed in terms of colonization history, infrastructure, suitability of the land, and landownership. The actual use of the land is driven mainly by the ability to access the land and markets as is obvious in the distribution of land cover as a function of distance to rivers and roads. When considering all rivers and roads a threshold distance at which disproportional agro-pastoral land cover switches from over represented to under represented is at about 1km. Best land use suggestions seem not to affect the choice of land use. Differences in abundance of land cover between watersheds are more prevailing than differences between colonist and indigenous groups.

From policy development to effectiveness and alignment: An analysis of the UK’s Higher Education Open Access policy landscape

The number of Open Access (OA) policies that have been adopted by universities, research institutes and research funders has been increasing at a fast pace. The Registry of Open Access Repository Mandates and Policies (ROARMAP) records the existence of 724 OA policies across the world, of which 512 have been adopted by universities and research institutions. The UK is one of the leading countries in terms of OA policy development and implementation with a total of 85 institutional1 and an estimated 35 funder2 OA policies. In order to understand and contextualise how OA policies are developed and how they can be effectively implemented and aligned, this brief looks at two areas. The first section provides an overview on the processes evolving around policy making, policy effectiveness and policy alignment. In particular, it summarises the criteria and elements generally specified in OA policies, it points out some of the relevant steps informing the development, monitoring and revision of OA policies, it outlines what OA policy elements contribute to policy effectiveness, and highlights the benefits in aligning OA policies. The second section revisits the issues previously discussed within the context of the UK institutional (universities) OA policy landscape.

Development of an historical landscape photography database to support landscape change analysis in the Northeast of Portugal

Repeat photography is an efficient, effective and useful method to identify trends of changes in the landscapes. It was used to illustrate long-term changes occurring in the landscapes. In the Northeast of Portugal, landscapes changes is currently driven mostly by agriculture abandonment and agriculture and energy policy. However, there is a need to monitoring changes in the region using a multitemporal and multiscale approach. This project aimed to establish an online repository of oblique digital photography from the region to be used to register the condition of the landscape as recorded in historical and contemporary photography over time as well as to support qualitative and quantitative assessment of change in the landscape using repeat photography techniques and methods. It involved the development of a relational database and a series of web-based services using PHP: Hypertext Preprocessor language, and the development of an interface, with Joomla, of pictures uploading and downloading by users. The repository will make possible to upload, store, search by location, theme, or date, display, and download pictures for Northeastern Portugal. The website service is devoted to help researchers to obtain quickly the photographs needed to apply RP through a developed search engine. It can be accessed at: http://esa.ipb.pt/digitalandscape/.

Detecting phase transitions in community structures using big data analysis of the engineering education research landscape: a European perspective

Comunicação apresentada na 44th SEFI Conference, 12-­15 September 2016, Tampere, Finland