Fish-habitat modeling for gap analysis to conserve the endangered Topeka shiner (Notropis topeka)

Decision support tools that predict fish distribution over broad spatial scales are needed to assist in planning watershed management and endangered species recovery. We developed a geographical information system model with multivariate logistic regression to rank valley segments for probable occurrence of the endangered Topeka shiner (Notropis topeka) using stream condition variables (stream size, groundwater potential, channel slope, streamflow, network position) and land-cover variables (percent pasture, percent trees) in streams characteristic of the North American Great Plains. The stream condition and land-cover models correctly classified 89% and 68% of outcomes (i.e., presence or absence), respectively. Field tests of maps of predicted species distribution resulted in more species occurrences than expected in valley segments classified as high potential for presence and less than expected in low-potential valley segments. Gaps between high-priority segments and protected land parcels were found in all basins. In 37 basins with Topeka shiners, protected land coverage was <1% in 17 basins, 15% in 10 basins, and 521.8% in 10 basins. Conservation activities in gaps are long-term conservation measures, but maps of predicted species distribution have many immediate applications.

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Landscape Influences on Stream Habitats and Biological Assemblages

Landscape Influences on Stream Habitats and Biological Assemblages ◽

10.47886/9781888569766.ch14 ◽

2006 ◽

Keyword(s):

Great Plains ◽

Spatial Scales ◽

Management Strategies ◽

Groundwater Potential ◽

Physical Habitat ◽

Habitat Features ◽

Notropis Topeka ◽

Using Data ◽

Topeka Shiner ◽

Valley Segment

Abstract.—The Topeka shiner Notropis topeka is a small cyprinid listed as endangered in 1999 due to an 80% reduction in its former range across six Great Plains states. Conservation and recovery plans require information on structural indices of existing populations, distribution, and habitat relations at several spatial scales. We examined physical habitat associations of Topeka shiners at the valley segment and reach scales, and associations with fish species using stepwise logistic regression. Fish and habitat data were collected at 52 sites. Habitat features at the valley segment scale were acquired using data from a geographic information system. At the valley segment scale, Topeka shiners were associated with stream condition variables (stream size, groundwater potential, channel slope, streamflow, network position) and land-cover variables (% pasture, % trees). At the reach scale, Topeka shiners were associated with low grazing and small trees in riparian zones, low bank height, less submerged vegetation, and coarse substrates. Topeka shiners were associated with five fishes that inhabit small, intermittent, warmwater streams. Evidence of greater abundance of Topeka shiner populations in our region compared to other regions may be a result of the natural character of the streams and associated wetlands, which can influence the habitat variables associated with Topeka shiners at both scales. We identified management strategies that would be effective at conserving habitat of Topeka shiners at large and local scales.

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Fish habitat modeling: from conceptual framework to functional tools

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f00-251 ◽

2001 ◽

Vol 58 (1) ◽

pp. 1-9 ◽

Cited By ~ 35

Author(s):

Daniel Boisclair

Keyword(s):

Spatial Scales ◽

Fish Habitat ◽

Fish Communities ◽

Distribution Patterns ◽

Habitat Modeling ◽

Fish Distribution ◽

Spatially Explicit ◽

Net Energy ◽

Specific Distribution ◽

Physical Attributes

Natural and anthropogenic perturbations do not always equally affect all parts of an ecosystem, and all parts of an ecosystem do not equally contribute to maintain fish communities. The increasing pressure to use natural resources and to modify habitats led to the development of approaches to identify areas of key importance for fish communities. Following these approaches, aquatic systems could be perceived as puzzles, composed of a multitude of pieces with temporally flexible physical attributes and biological roles. Such a spatially explicit framework requires models that may allow one to predict fish distribution patterns and fish net energy gain once they have adopted a specific distribution pattern. Despite the conceptual appeal of spatially explicit approaches, functional tools may be obtained only after their assumptions have been tested and their models have been validated. Efforts must be deployed to identify temporal and spatial scales at which fish distribution and abundance should be estimated and modeled. Studies on fish behaviour and the energetic consequences of these behaviours must be conducted to insure that bioenergetic criteria used to define fish habitat quality do not depend on arbitrary assumptions about fish activity costs.

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Riparian forest structure and stream geomorphic condition: implications for flood resilience

Canadian Journal of Forest Research ◽

10.1139/cjfr-2016-0327 ◽

2017 ◽

Vol 47 (4) ◽

pp. 476-487 ◽

Cited By ~ 5

Author(s):

William S. Keeton ◽

Erin M. Copeland ◽

S. Mažeika P. Sullivan ◽

Mary C. Watzin

Keyword(s):

Land Cover ◽

Forest Structure ◽

Forest Cover ◽

Linear Models ◽

Riparian Forest ◽

Spatial Scales ◽

Basal Area ◽

Riparian Corridors ◽

Stream Condition ◽

Stream Geomorphology

Managing riparian corridors for flood resilience requires understanding of linkages between vegetation condition and stream geomorphology. Stream assessment approaches increasingly use channel morphology as an indicator of stream condition, with only cursory examination of riparian vegetation. Our research (i) examines relationships between stream geomorphic condition, as assessed by Rapid Geomorphic Assessment (RGA) scores, and riparian forest structure, and (ii) investigates scale dependencies in the linkages between land cover and stream geomorphology. We sampled vegetation structure and composition and assessed geomorphic condition at 32 stream reaches within the Lake Champlain Basin, USA. RGA scores were modeled as a function of structural attributes using classification and regression trees. Landsat coverages were used to delineate land uses within five nested spatial scales. Generalized linear models (GLM) evaluated relationships between land cover and RGA scores. Standard deviation of basal area partitioned the greatest variability in RGA scores, but dead tree density and basal area (positively) and shrub density (negatively) were also significant predictors. RGA was related to forest and agricultural cover at the two finest scales. Riparian forest structure is highly dynamic in relation to stand development and disturbance history; simple forest cover information does not capture these differences or their influences on stream geomorphic condition.

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Worldview-2 and Landsat 8 Satellite Data for Seaweed Mapping along Karachi Coast

Pakistan Journal of Engineering Technology & Science ◽

10.22555/pjets.v5i2.920 ◽

2016 ◽

Vol 5 (2) ◽

Cited By ~ 1

Author(s):

Muhammad Danish Siddiqui ◽

Arjumand Z Zaidi

Keyword(s):

Satellite Data ◽

Spatial Scales ◽

Economic Value ◽

Vegetation Indices ◽

Cost Effective ◽

Geographical Information ◽

Landsat 8 ◽

Coverage Area ◽

Breeding Sites ◽

Marine Plant

Seaweed is a marine plant or algae which has economic value in many parts of the world. The purpose of this study is to evaluate different satellite sensors such as high-resolution WorldView-2 (WV2) satellite data and Landsat 8 30-meter resolution satellite data for mapping seaweed resources along the coastal waters of Karachi. The continuous monitoring and mapping of this precious marine plant and their breeding sites may not be very efficient and cost effective using traditional survey techniques. Remote Sensing (RS) and Geographical Information System (GIS) can provide economical and more efficient solutions for mapping and monitoring coastal resources quantitatively as well as qualitatively at both temporal and spatial scales. Normalized Difference Vegetation Indices (NDVI) along with the image enhancement techniques were used to delineate seaweed patches in the study area. The coverage area of seaweed estimated with WV-2 and Landsat 8 are presented as GIS maps. A more precise area estimation wasachieved with WV-2 data that shows 15.5Ha (0.155 Km2)of seaweed cover along Karachi coast that is more representative of the field observed data. A much larger area wasestimated with Landsat 8 image (71.28Ha or 0.7128 Km2) that was mainly due to the mixing of seaweed pixels with water pixels. The WV-2 data, due to its better spatial resolution than Landsat 8, have proven to be more useful than Landsat 8 in mapping seaweed patches

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Dispersal and Land Cover Contribute to Pseudorabies Virus Exposure in Invasive Wild Pigs

EcoHealth ◽

10.1007/s10393-020-01508-6 ◽

2021 ◽

Author(s):

Felipe A. Hernández ◽

Amanda N. Carr ◽

Michael P. Milleson ◽

Hunter R. Merrill ◽

Michael L. Avery ◽

...

Keyword(s):

Land Cover ◽

Disease Transmission ◽

Wildlife Conservation ◽

Pseudorabies Virus ◽

Spatial Scales ◽

Information Criterion ◽

Small Scale ◽

Wild Pigs ◽

Bacterial Agent ◽

Open Canopy

AbstractWe investigated the landscape epidemiology of a globally distributed mammal, the wild pig (Sus scrofa), in Florida (U.S.), where it is considered an invasive species and reservoir to pathogens that impact the health of people, domestic animals, and wildlife. Specifically, we tested the hypothesis that two commonly cited factors in disease transmission, connectivity among populations and abundant resources, would increase the likelihood of exposure to both pseudorabies virus (PrV) and Brucella spp. (bacterial agent of brucellosis) in wild pigs across the Kissimmee Valley of Florida. Using DNA from 348 wild pigs and sera from 320 individuals at 24 sites, we employed population genetic techniques to infer individual dispersal, and an Akaike information criterion framework to compare candidate logistic regression models that incorporated both dispersal and land cover composition. Our findings suggested that recent dispersal conferred higher odds of exposure to PrV, but not Brucella spp., among wild pigs throughout the Kissimmee Valley region. Odds of exposure also increased in association with agriculture and open canopy pine, prairie, and scrub habitats, likely because of highly localized resources within those land cover types. Because the effect of open canopy on PrV exposure reversed when agricultural cover was available, we suggest that small-scale resource distribution may be more important than overall resource abundance. Our results underscore the importance of studying and managing disease dynamics through multiple processes and spatial scales, particularly for non-native pathogens that threaten wildlife conservation, economy, and public health.

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Impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand

Soil and Water Research ◽

10.17221/32/2011-swr ◽

2012 ◽

Vol 7 (No. 1) ◽

pp. 10-17 ◽

Cited By ~ 31

Author(s):

S. Wijitkosum

Keyword(s):

Land Use ◽

Soil Erosion ◽

Land Cover ◽

National Park ◽

Land Use Changes ◽

Influential Factors ◽

Geographical Information ◽

Adjacent Area ◽

Erosion Risk ◽

Study Results

Soil erosion has been considered as the primary cause of soil degradation since soil erosion leads to the loss of topsoil and soil organic matters which are essential for the growing of plants. Land use, which relates to land cover, is one of the influential factors that affect soil erosion. In this study, impacts of land use changes on soil erosion in Pa Deng sub-district, adjacent area of Kaeng Krachan National Park, Thailand, were investigated by applying remote sensing technique, geographical information system (GIS) and the Universal Soil Loss Equation (USLE). The study results revealed that land use changes in terms of area size and pattern influenced the soil erosion risk in Pa Deng in the 1990–2010 period. The area with smaller land cover obviously showed the high risk of soil erosion than the larger land cover did.

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