Land-cover patterns surrounding Caucasian grouse leks in Arasbaran region, East Azerbaijan, Iran

2016 ◽  
Vol 43 (3) ◽  
pp. 267 ◽  
Author(s):  
Nader Habibzadeh ◽  
Omid Rafieyan
Keyword(s):  
Land Cover ◽  
Landscape Metrics ◽  
Spatial Scales ◽  
Landscape Composition ◽  
Additive Models ◽  
Theoretic Approach ◽  
Habitat Types ◽  
Habitat Mosaic ◽  
Composition And Structure ◽  
East Azerbaijan

Context To create management strategies with the goal of sustaining a species such as Caucasian grouse (Lyrurus mlokosiewiczi), it is important to identify the habitat requirements of species, not just in terms of a correlation with a given habitat feature, but also the relationship between species presence and vegetation coverage, proximity to other habitat types, and importance at different spatial scales. Aims To predict the proportions and spatial configuration of major habitat types that are associated with high probabilities of Caucasian grouse lek occurrence. Methods Using minimum mapping-unit scale (i.e. grain) for land cover, we applied spatial analysis at three spatial extents (472-, 702- and 867-m-radius circles) to assess how the importance of different land-cover patterns and patch characteristics surrounding leks of Caucasian grouse changed with scale within the Arasbaran landscape (316.56 km2) in East Azerbaijan, Iran. A set of a priori models has been developed on the basis of landscape metrics linked to hypotheses that could explain the spatial pattern of Caucasian black habitat use at each scale. We used an information-theoretic approach based on Akaike’s information criterion (AIC) within a general additive models framework to model habitat selection, so as to compare the values of landscape metrics calculated for Caucasian grouse lek sites (n = 22) with those calculated for non-lek points (n = 44). Key results The probability of lek occurrence at each of the spatial scales increases with a larger amount of open, young forests in the landscape. At each scale, we could indicate the landscape composition and structure required to create an ideal habitat mosaic for Caucasian grouse. Such an ideal habitat mosaic within mountain forests of Arasbaran, for a 702-m-radius area around a potential lek site, would consist of non-square (i.e. more geometrically complex) patches of rangeland cover and deciduous stands with canopy cover of <50%, which encompass over 30% of landscape. Conclusions Our results identified differences in black grouse requirements at several scales within the landscape. We believe this will help managers improve the habitat focusing on the area around existing or inactive leks, to adapt the landscape to species requirements, and to encourage targeting new sites. Implications These findings demonstrated that not only can we identify important landscape requirements at a range of scales, but by characterising landscape composition and structure across these scales, forest managers can help prioritise combinations of habitats that best serve the conservation of the target species.

scholarly journals Suburban frog ponds: mapping local land cover yields different estimates of landscape composition than the National Land Cover Database

2014 ◽  
Author(s):  
Max Lambert
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Spatial Scales ◽  
Landscape Composition ◽  
Ecological Processes ◽  
Simple Method ◽  
Fine Grain ◽  
Land Cover Data ◽  
Ecological Patterns

Suburban neighborhoods are rapidly spreading globally. As such, there is an increasing need to study the environmental and ecological effects of suburbanization. At large spatial extents, from county-level to global, remote sensing-derived land cover data, such as the National Land Cover Dataset (NLCD), have yielded insight into patterns of urbanization and concomitant large-scale ecological patterns in response. However, the components of suburban land cover (houses, yards, etc.) are dispersed throughout the landscape at a finer scale than the relatively coarse grain size (30m pixels) of NLCD may be able to detect. Our understanding of ecological processes in heterogeneous landscapes is reliant upon the accuracy and resolution of our measurements as well as the scale at which we measure the landscape. Analyses of ecological processes along suburban gradients are restricted by the currently available data. As ecologists are becoming increasingly interested in describing phenomena at spatial extents as small as individual households, we need higher-resolution landscape measurements. Here, I describe a simple method of translating the components of suburban landscapes into finer-grain, local land cover (LLC) data in GIS. Using both LLC and NLCD, I compare the suburban matrix surrounding ponds occupied by two different frog species. I illustrate large discrepancies in Forest, Yard, and Developed land cover estimates between LLC and NLCD, leading to markedly different interpretations of suburban landscape composition. NLCD, relative to LLC, estimates lower proportions of forest cover and higher proportions of anthropogenic land covers in general. These two land cover datasets provide surprisingly different descriptions of the suburban landscapes, potentially affecting our understanding of how organisms respond to an increasingly suburban world. LLC provides a free and detailed fine-grain depiction of the components of suburban neighborhoods and will allow ecologists to better explore heterogeneous suburban landscapes at multiple spatial scales.

Effects of land cover on coyote abundance

2016 ◽  
Vol 43 (8) ◽  
pp. 662 ◽  
Author(s):  
Michael J. Cherry ◽  
Paige E. Howell ◽  
Cody D. Seagraves ◽  
Robert J. Warren ◽  
L. Mike Conner
Keyword(s):  
North America ◽  
Land Cover ◽  
Spatial Variation ◽  
Spatial Scales ◽  
Mixed Forest ◽  
Landscape Composition ◽  
Ecological Communities ◽  
Apex Predators ◽  
Agricultural Ecosystem ◽  
Patch Type

Context Throughout the world, declines in large mammalian carnivores have led to the release of smaller meso-mammalian predators. Coyotes (Canis latrans) have increased in abundance, distribution and ecological influence following the extirpation of apex predators in North America. Coyotes have had substantial influence on many ecosystems in recently colonised portions of their range, but those influences can vary across land cover types. Thus, understanding the relationship between coyote abundance and land cover may enhance our ability to predict spatial variation in the ecological effects of coyotes. Aims Our objective was to examine the influence of landscape attributes on eastern coyote abundance to ultimately facilitate predictions of spatial variation in the effects of coyotes on prey populations, ecological communities and human interests. Methods We collected count data from repeated visits to 24 sites by eliciting howl responses from coyotes. We fit abundance models to howl-response data to examine the effects of landscape composition and configuration on coyote abundance in a mixed forest/agricultural ecosystem in south-western Georgia, USA. Key results Our investigation revealed that coyote abundance was positively associated with grasslands that were predominantly used for livestock production, and negatively associated with patch diversity. Conclusions Our results supported the prediction that coyotes would be positively associated with open habitats and that they are well adapted for areas structurally similar to the plains of central North America, where the species originated. In addition, these results suggest that aspects of fragmentation, such as patch diversity, can negatively affect coyote abundance. Our results highlight the importance of patch type and landscape juxtaposition on the abundance of coyotes in complex heterogeneous landscapes. Implications Our results further our understanding of the spatial variation in coyote abundances across a recently colonised portion of the species range. Combining howl-response surveys with abundance modelling is a promising approach for studying the associations between population dynamics of vocal canids and landscape structure over large spatial scales.

scholarly journals Suburban frog ponds: mapping local land cover yields different estimates of landscape composition than the National Land Cover Database

2014 ◽  
Author(s):  
Max Lambert
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Spatial Scales ◽  
Landscape Composition ◽  
Ecological Processes ◽  
Simple Method ◽  
Fine Grain ◽  
Land Cover Data ◽  
Ecological Patterns

Suburban neighborhoods are rapidly spreading globally. As such, there is an increasing need to study the environmental and ecological effects of suburbanization. At large spatial extents, from county-level to global, remote sensing-derived land cover data, such as the National Land Cover Dataset (NLCD), have yielded insight into patterns of urbanization and concomitant large-scale ecological patterns in response. However, the components of suburban land cover (houses, yards, etc.) are dispersed throughout the landscape at a finer scale than the relatively coarse grain size (30m pixels) of NLCD may be able to detect. Our understanding of ecological processes in heterogeneous landscapes is reliant upon the accuracy and resolution of our measurements as well as the scale at which we measure the landscape. Analyses of ecological processes along suburban gradients are restricted by the currently available data. As ecologists are becoming increasingly interested in describing phenomena at spatial extents as small as individual households, we need higher-resolution landscape measurements. Here, I describe a simple method of translating the components of suburban landscapes into finer-grain, local land cover (LLC) data in GIS. Using both LLC and NLCD, I compare the suburban matrix surrounding ponds occupied by two different frog species. I illustrate large discrepancies in Forest, Yard, and Developed land cover estimates between LLC and NLCD, leading to markedly different interpretations of suburban landscape composition. NLCD, relative to LLC, estimates lower proportions of forest cover and higher proportions of anthropogenic land covers in general. These two land cover datasets provide surprisingly different descriptions of the suburban landscapes, potentially affecting our understanding of how organisms respond to an increasingly suburban world. LLC provides a free and detailed fine-grain depiction of the components of suburban neighborhoods and will allow ecologists to better explore heterogeneous suburban landscapes at multiple spatial scales.

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

EcoHealth ◽  
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.

scholarly journals Factors affecting relative abundance of low-mobility fishing resources: spiny lobster in the Galapagos Marine Reserve

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7278 ◽  
Author(s):  
Juan Carlos Murillo-Posada ◽  
Silvia Salas ◽  
Iván Velázquez-Abunader
Keyword(s):  
Monitoring System ◽  
Relative Abundance ◽  
Spatial Scales ◽  
Marine Reserve ◽  
Spiny Lobster ◽  
Fishing Effort ◽  
Additive Models ◽  
Catch Per Unit Effort ◽  
Monthly Basis ◽  
Galapagos Marine Reserve

Management of low-mobility or benthic fisheries is a difficult task because variation in the spatial distribution and population dynamics of the resources make the monitoring and assessment of these fisheries challenging. We assumed that environmental, spatial, and temporal factors can contribute to the variability of the relative abundance of such species; we used Generalized Additive Models for Location Scale and Shape (GAMLSS) to test this hypothesis using as a case study the lobster fishery (targeting two species) in the Galapagos Marine Reserve, Ecuador. We gathered data on each of the two species of lobster on a monthly basis over seven years, including: (a) onboard observers’ records of catch data, fishing effort, and ground location by trip, and (b) data from interviews undertaken with fishers at their arrival to port, recording the same type of information as obtained from onboard observers. We use this information to analyze the effect of the measured variables and to standardize the Catch per Unit Effort (CPUE) in each case, using the GAMLSS. For both species, the temperature, region, fishing schedule, month, distance, and the monitoring system were significant variables of the selected models associated with the variability of the catch rate. ForPanulirus penicillatus, CPUE was higher at night than during the day, and forPanulirus gracilisit was higher during the day. Increased temperature resulted in a decrease of CPUE values. It was evident that temporal, spatial scales and monitoring system can influence the variability of this indicator. We contend that the identification of drivers of change of relative abundance in low-mobility species can help to support the development of monitoring and assessment programs for this type of fisheries.

scholarly journals RANDOM AND SYSTEMATIC LAND-COVER TRANSITIONS IN NORTH-EASTERN WOLLEGA, ETHIOPIA

2017 ◽  
Vol 332 ◽  
pp. 3-15 ◽  
Author(s):  
Alemayehu Adugna ◽  
Assefa Abegaz ◽  
Asmamaw Legass ◽  
Diogenes L. Antille
Keyword(s):  
Land Cover ◽  
Agricultural Land ◽  
Spatial Scales ◽  
Random Processes ◽  
Processes Of Change ◽  
Landsat Data ◽  
Loss Ratio ◽  
Agricultural Abandonment ◽  
North Eastern ◽  
Transi Tions

Africa has seen significant changes in land cover at different spatial scales. Changes in Land Use and Land Cover (LULC) include deforestation and subse- quent use of the land for arable cropping, conversion to grassland or urbanization. The work reported in this article was conducted to examine land cover transi- tions in north-eastern Wollega (Ethiopia) between 2005 and 2015. The analysis focused on land cover transitions that occurred systematically or randomly, and identified the main drivers for these changes. Landsat data from 2005 and 2015 were examined to better unders- tand the various dimensions of land cover transitions, namely: swaps, losses, gains, persistency and vulnerability. Results showed that shrubland exhibited the largest gain (22%), with a 63% gain- to-loss ratio, a 47% gain-to-persistence ratio and a positive net change-to-persis- tence ratio of 46%. Cropland showed the largest loss (19%) while grassland was the most stable type of land cover des- pite some fluctuation (»10%) observed during the 10-year period. The land cover transition was dominated by systematic processes, with few random processes of change. Systematic land cover transitions such as agricultural abandonment and vegetation re-growth were attributed to regular or common processes of change. This study suggests that the implementa- tion of practices conducive to sustainable intensification of existing agricultural land, supported by policies that promote increased diversification of Ethiopian agriculture, would mitigate pressure on forests by avoiding their future conver- sion to cropland.

scholarly journals Continuous and consistent land use/cover change estimates using socio-ecological data

2016 ◽  
Author(s):  
Michael Marshall ◽  
Michael Norton-Griffiths ◽  
Harvey Herr ◽  
Richard Lamprey ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Surface ◽  
Natural Vegetation ◽  
Additive Models ◽  
Sub Saharan Africa ◽  
Land Cover Types ◽  
Remote Sensing Classification ◽  
Functional Relationships ◽  
Macro Scale

Abstract. A growing body of research shows the importance of land use/cover change (LULCC) on modifying the earth system. Land surface models are used to stimulate land-atmosphere dynamics at the macro- (regional to global) scale, but bias and uncertainty remain that need to be addressed, before the importance of LULCC is fully realized. In this study, we propose a method of improving LULCC estimates for land surface modelling exercises. The method yields continuous (annual) long-term (30-year) estimates of LULCC driven by socio-ecological geospatial predictors available seamlessly across sub-Saharan Africa that can be used for both retrospective and prospective analyses. The method was developed with 2252 5 × 5 km2 sample frames of the proportion of several land cover types in Kenya over multiple years. Forty-three socio-ecological predictors were evaluated for model development. Machine learning was used for data reduction and simple (functional) relationships defined by generalized additive models were constructed on a subset of the highest ranked predictors (p ≤ 10) to estimate LULCC. The predictors explained 62 % and 65 % of the variance in the proportion of agriculture and natural vegetation, respectively, but were less successful at estimating more descriptive land cover types. In each case, population density on an annual basis was the highest ranked predictor. The approach was compared to a commonly used remote sensing classification procedure, given the wide use of such techniques for macro-scale LULCC detection, and out-performed it for each land cover type. The approach was used to demonstrate significant trends in expanding (declining) agricultural (natural vegetation) land cover in Kenya from 1983–2012, with the largest increases (declines) occurring in densely populated high agricultural production zones.

Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics

2013 ◽  
pp. 228-244
Author(s):  
Carmelo Riccardo Fichera ◽  
Giuseppe Modica ◽  
Maurizio Pollino
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Landscape Metrics ◽  
Landsat Images ◽  
Aerial Photos ◽  
Multi Temporal ◽  
Urban Rural ◽  
Remote Sensing Techniques

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.

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