scholarly journals Persistence-Based Area Prioritization for Conservation: Applying Occupancy and Habitat Threats and Risks Analyses

2018 ◽  
Vol 9 (2) ◽  
pp. 554-564
Author(s):  
Liani M. Yirka ◽  
Jaime A. Collazo ◽  
Steven G. Williams ◽  
David T. Cobb
Keyword(s):  
Land Cover ◽  
Habitat Management ◽  
Decision Support Tool ◽  
Single Species ◽  
Illustrative Case ◽  
Occupancy Models ◽  
Support Tool ◽  
Persistence Probability ◽  
Area Of Interest ◽  
Maritime Forest

Abstract Effective habitat conservation is predicated on maintaining high levels or increasing local persistence probability of the species it purports to protect. Thus, methodological approaches that improve the inferential value of local persistence are of utmost value to guide conservation planning as they inform area selection processes. Herein we used the painted bunting Passerina ciris, a species of conservation interest in North Carolina, as an illustrative case that combined single-season, single-species occupancy analyses and a threats and risk decision support tool to rank five areas of conservation interest in terms of local persistence probability. We used survey data from two seasons (2008–2009) grouped into 21 natal dispersal sampling units and land-cover data from 12 habitat classes to establish the relationship between local occupancy probability and habitat. Occupancy increased most strongly with increasing amount of maritime forest. Projections to year 2050, relative to year 2000, indicated that a potential loss of maritime forest of 200–1,300 ha, depending on the area of interest. Projected loss was lowest at Bald Head Island–Wilmington (2%) and highest at Camp Lejune (27%). Bald Head Island–Wilmington ranked highest in projected local persistence probability (0.91; 95% confidence interval [CI] = 0.53–0.99), whereas Top Sail–Hammocks Beach Park ranked lowest (0.28; 95% CI = 0.03–0.82). Estimates of local persistence offer decision-makers another criterion to prioritize areas for conservation and help guide efforts aimed at maintaining or enhancing local persistence. These include in situ habitat management, expanding or connecting existing areas of interest. In the future, we recommend the use of multiseason occupancy models, coupled with measures of uncertainty of land-cover projections, to strengthen inferences about local persistence, particularly useful in nonstationary landscapes driven by human activities.

scholarly journals Semi-automated land cover mapping using an ensemble of support vector machines with moderate resolution imagery integrated into a custom decision support tool

2021 ◽  
Author(s):  
Kristofer Lasko ◽  
Elena Sava
Keyword(s):  
Land Cover ◽  
Decision Support Tool ◽  
Support Vector ◽  
Landsat 8 ◽  
Terrain Analysis ◽  
Land Cover Type ◽  
Support Tool ◽  
Cover Type ◽  
On Demand ◽  
Sentinel 2

Land cover type is a fundamental remote sensing-derived variable for terrain analysis and environmental mapping applications. The currently available products are produced only for a single season or a specific year. Some of these products have a coarse resolution and quickly become outdated, as land cover type can undergo significant change over a short time period. In order to enable on-demand generation of timely and accurate land cover type products, we developed a sensor-agnostic framework leveraging pre-trained machine learning models. We also generated land cover models for Sentinel-2 (20m) and Landsat 8 imagery (30m) using either a single date of imagery or two dates of imagery for mapping land cover type. The two-date model includes 11 land cover type classes, whereas the single-date model contains 6 classes. The models’ overall accuracies were 84% (Sentinel-2 single date), 82% (Sentinel-2 two date), and 86% (Landsat 8 two date) across the continental United States. The three different models were built into an ArcGIS Pro Python toolbox to enable a semi-automated workflow for end users to generate their own land cover type maps on demand. The toolboxes were built using parallel processing and image-splitting techniques to enable faster computation and for use on less-powerful machines.

scholarly journals Decision Support Tool for Tree Species Selection in Forest Regeneration Based on Harvester Data

Forests ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 1329
Author(s):  
Timo Saksa ◽  
Jori Uusitalo ◽  
Harri Lindeman ◽  
Esko Häyrynen ◽  
Sampo Kulju ◽  
...  
Keyword(s):  
Tree Species ◽  
Stand Structure ◽  
Grid Cell ◽  
Decision Support Tool ◽  
Single Species ◽  
Species Selection ◽  
Stand Age ◽  
Local Growth ◽  
Support Tool ◽  
Regeneration Phase

Precision forestry—i.e., the division of a stand to smaller units and managing of the stand at a micro-stand level—provides new possibilities to increase forest growth, arrange forest stand structure and enhance forest health. In the regeneration phase by adjusting the tree species selection, soil preparation, intensity of regeneration measures (method, planting density, and material), and young stand management procedures according to precise information on soil properties (e.g., site fertility, wetness, and soil type) and microtopography will inevitably lead to an increase in growth of the whole stand. A new approach to utilizing harvester data to delineate micro-stands inside a large forest stand and to deciding the tree species to plant for each micro-stand was piloted in central Finland. The case stands were situated on Finsilva Oyj forest property. The calculation of the local growth (m3/ha/year) for each 16 × 16-m grid cell was based on the height of the dominant trees and the stand age of the previous tree generation. Tree heights and geoinformation were collected during cutting operation as the harvester data, and the dominant height was calculated as the mean of the three largest stems in each grid cell. The stand age was obtained from the forest management plan. The estimated local growth (average of nine neighboring grid cells) varied from 3 to 14 m3/ha/year in the case stands. When creating micro-stands, neighboring grid cells with approximately the same local growth were merged. The minimum size for an acceptable micro-stand was set to 0.23 ha. In this case study, tree species selection (Scots pine or Norway spruce) was based on the mean growth of each micro-stand. Different threshold values, varying from 6 to 8 m3/ha/year, were tested for tree species change, and they led to different solutions in the delineation of micro-stands. Further stand development was simulated with the Motti software and the net present values (NPVs (3%)) for the next rotation were estimated for different micro-stand solutions. The mixed Norway spruce–Scots pine stand structure never produced a clearly economically inferior solution compared to the single species stand, and in one case out of six, it provided a distinctly better solution in terms of NPV (3%) than the single species option did. Our case study showed that this kind of method could be used as a decision support tool at the regeneration phase.

scholarly journals A DECISION SUPPORT TOOL ON DERELICT BUILDINGS FOR URBAN REGENERATION

2018 ◽  
Vol IV-4/W7 ◽  
pp. 19-25
Author(s):  
I. Blečić ◽  
A. Cecchini ◽  
M. Minchilli ◽  
L. F. Tedeschi ◽  
G. A. Trunfio
Keyword(s):  
Decision Support ◽  
Economies Of Scale ◽  
Search Algorithm ◽  
Urban Regeneration ◽  
Decision Support Tool ◽  
Support Tool ◽  
Area Of Interest ◽  
The City ◽  
Selection Of

<p><strong>Abstract.</strong> We present a decision suppport tool for the comparison and selection of projects of integrated renovation of derelict buildings and areas for the purpose of urban regeneration. Each project is defined as a subset of derelict properties to renovate together with their respective designated use, and is scored by the decision support tool on two criteria: expected effort and estimated effectiveness in terms of improved urban capabilities in the urban area of interest. The expected effort is estimated as a global transformation cost, factoring in legal and management overhead costs as well as possible economies of scale. The effectiveness in evaluated in terms of extension of urban capabilities centred on walkable distances. We have implemented a bi-objective evolutionary search algorithm to address the computational complexity of the problem of search for efficient (non-dominated) projects over the two criteria. For the purpose of illustration, we present an example case-study application on the historical core of the city of Sassari, Italy.</p>

Decision support tool: Mottled duck habitat management and conservation in the Western Gulf Coast

2019 ◽  
Vol 230 ◽  
pp. 43-52
Author(s):  
Anastasia Krainyk ◽  
Bart M. Ballard ◽  
Michael G. Brasher ◽  
Barry C. Wilson ◽  
Mark W. Parr ◽  
...  
Keyword(s):  
Decision Support ◽  
Habitat Management ◽  
Gulf Coast ◽  
Decision Support Tool ◽  
Support Tool ◽  
Mottled Duck ◽  
Management And Conservation

scholarly journals LAND SUITABILITY ANALYSIS AS MULTI CRITERIA DECISION MAKING TO SUPPORT THE EGYPTIAN URBAN DEVELOPMENT

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Marwa Adel El Sayed
Keyword(s):  
Urban Development ◽  
Land Development ◽  
Decision Support Tool ◽  
Development Planning ◽  
Land Suitability ◽  
Suitability Analysis ◽  
Support Tool ◽  
Land Suitability Analysis ◽  
Planning Decisions ◽  
Area Of Interest

Sustainability in urban development is considered as a main concrete stone that effect directly the quality of life for its users. Land Suitability Analysis (LSA) using GIS as a multi criteria support tool reveals the best alternatives for the suitability of sustainable land development. Urban planners working under the umbrella of sustainability using recent technology should contribute their work directly to LSA. This paper aims to develop a new technique to be used by planner to reach best alternative for five main urban sectors (agriculture, Industry, Trade, Tourism, & Residential) using GIS as a multi criteria decision support tool (MCDS), accordingly choosing best city location will be accurately and analyzed upon LSA studies. LSA and MCDS are going to be applied on one survey unit map called Monof along Cairo – Alexandria Road. Results showed that different alternatives could be applied on the area of interest, and all of them are sustainable, but choosing the best deepened on the priority of querying the development sector. The paper suggests a pilot method for land development planning and choosing best city location that would be a guide for the governmental planning organization to support in taking right and analyzed planning decisions.

scholarly journals Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD): data and tools for dynamic management and decision support

Polar Record ◽  
2017 ◽  
Vol 53 (2) ◽  
pp. 160-166 ◽  
Author(s):  
G.R.W. Humphries ◽  
R. Naveen ◽  
M. Schwaller ◽  
C. Che-Castaldo ◽  
P. McDowall ◽  
...  
Keyword(s):  
Decision Support ◽  
Data Transfer ◽  
Monitoring Program ◽  
Decision Support Tool ◽  
Ecosystem Monitoring ◽  
Web Based ◽  
Support Tool ◽  
Management Objectives ◽  
Area Of Interest ◽  
Abundance Estimates

ABSTRACTThe Mapping Application for Penguin Populations and Projected Dynamics (MAPPPD) is a web-based, open access, decision-support tool designed to assist scientists, non-governmental organisations and policy-makers working to meet the management objectives as set forth by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR) and other components of the Antarctic Treaty System (ATS) (that is, Consultative Meetings and the ATS Committee on Environmental Protection). MAPPPD was designed specifically to complement existing efforts such as the CCAMLR Ecosystem Monitoring Program (CEMP) and the ATS site guidelines for visitors. The database underlying MAPPPD includes all publicly available (published and unpublished) count data on emperor, gentoo, Adélie and chinstrap penguins in Antarctica. Penguin population models are used to assimilate available data into estimates of abundance for each site and year. Results are easily aggregated across multiple sites to obtain abundance estimates over any user-defined area of interest. A front end web interface located at www.penguinmap.com provides free and ready access to the most recent count and modelled data, and can act as a facilitator for data transfer between scientists and Antarctic stakeholders to help inform management decisions for the continent.

A protocol for sampling pastures in hill country

2016 ◽  
Vol 78 ◽  
pp. 203-209 ◽  
Author(s):  
K.J. Hutchinson ◽  
D.R. Scobie ◽  
J. Beautrais ◽  
A.D. Mackay ◽  
G.M. Rennie ◽  
...  
Keyword(s):  
Random Sampling ◽  
Geographical Information Systems ◽  
Field Measurements ◽  
Decision Support Tool ◽  
Accurate Estimate ◽  
Ease Of Use ◽  
Geographical Information ◽  
Support Tool ◽  
Topographic Complexity ◽  
Hill Country

To develop a protocol to guide pasture sampling for estimation of paddock pasture mass in hill country, a range of pasture sampling strategies, including random sampling, transects and stratification based on slope and aspect, were evaluated using simulations in a Geographical Information Systems computer environment. The accuracy and efficiency of each strategy was tested by sampling data obtained from intensive field measurements across several farms, regions and seasons. The number of measurements required to obtain an accurate estimate was related to the overall pasture mass and the topographic complexity of a paddock, with more variable paddocks requiring more samples. Random sampling from average slopes provided the best balance between simplicity and reliability. A draft protocol was developed from the simulations, in the form of a decision support tool, where visual determination of the topographic complexity of the paddock, along with the required accuracy, were used to guide the number of measurements recommended. The protocol was field tested and evaluated by groups of users for efficacy and ease of use. This sampling protocol will offer farmers, consultants and researchers an efficient, reliable and simple way to determine pasture mass in New Zealand hill country settings. Keywords: hill country, feed budgeting, protocol pasture mass, slope

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