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At least 541 records · Page 30Linked to original sources
USGS2006

Stand and landscape level effects of a major outbreak of spruce beetles on forest vegetation in the Copper River Basin, Alaska

From 1989 to 2003, a widespread outbreak of spruce beetles (Dendroctonus rufipennis) in the Copper River Basin, Alaska, infested over 275,000 ha of forests in the region. During 1997 and 1998, we measured forest vegetation structure and composition on one hundred and thirty-six 20-m ?? 20-m plots to assess both the immediate stand and landscape level effects of the spruce beetle infestation. A photo-interpreted vegetation and infestation map was produced using color-infrared aerial photography at a scale of 1:40,000. We used linear regression to quantify the effects of the outbreak on forest structure and composition. White spruce (Picea glauca) canopy cover and basal area of medium-to-large trees [???15 cm diameter-at-breast height (1.3 m, dbh)] were reduced linearly as the number of trees attacked by spruce beetles increased. Black spruce (Picea mariana) and small diameter white spruce (<15 cm dbh) were infrequently attacked and killed by spruce beetles. This selective attack of mature white spruce reduced structural complexity of stands to earlier stages of succession and caused mixed tree species stands to lose their white spruce and become more homogeneous in overstory composition. Using the resulting regressions, we developed a transition matrix to describe changes in vegetation types under varying levels of spruce beetle infestations, and applied the model to the vegetation map. Prior to the outbreak, our study area was composed primarily of stands of mixed white and black spruce (29% of area) and pure white spruce (25%). However, the selective attack on white spruce caused many of these stands to transition to black spruce dominated stands (73% increase in area) or shrublands (26% increase in area). The post-infestation landscape was thereby composed of more even distributions of shrubland and white, black, and mixed spruce communities (17-22% of study area). Changes in the cover and composition of understory vegetation were less evident in this study. However, stands with the highest mortality due to spruce beetles had the lowest densities of white spruce seedlings suggesting a longer forest regeneration time without an increase in seedling germination, growth, or survival. ?? 2006 Elsevier B.V. All rights reserved.

Forest Ecology and Management↗
USGS2013

Landscape-scale effects of fire severity on mixed-conifer and red fir forest structure in Yosemite National Park

While fire shapes the structure of forests and acts as a keystone process, the details of how fire modifies forest structure have been difficult to evaluate because of the complexity of interactions between fires and forests. We studied this relationship across 69.2 km2 of Yosemite National Park, USA, that was subject to 32 fires ⩾40 ha between 1984 and 2010. Forests types included ponderosa pine ( Pinus ponderosa ), white fir-sugar pine ( Abies concolor/Pinus lambertiana ), and red fir ( Abies magnifica ). We estimated and stratified burned area by fire severity using the Landsat-derived Relativized differenced Normalized Burn Ratio (RdNBR). Airborne LiDAR data, acquired in July 2010, measured the vertical and horizontal structure of canopy material and landscape patterning of canopy patches and gaps. Increasing fire severity changed structure at the scale of fire severity patches, the arrangement of canopy patches and gaps within fire severity patches, and vertically within tree clumps. Each forest type showed an individual trajectory of structural change with increasing fire severity. As a result, the relationship between estimates of fire severity such as RdNBR and actual changes appears to vary among forest types. We found three arrangements of canopy patches and gaps associated with different fire severities: canopy-gap arrangements in which gaps were enclosed in otherwise continuous canopy (typically unburned and low fire severities); patch-gap arrangements in which tree clumps and gaps alternated and neither dominated (typically moderate fire severity); and open-patch arrangements in which trees were scattered across open areas (typically high fire severity). Compared to stands outside fire perimeters, increasing fire severity generally resulted first in loss of canopy cover in lower height strata and increased number and size of gaps, then in loss of canopy cover in higher height strata, and eventually the transition to open areas with few or no trees. However, the estimated fire severities at which these transitions occurred differed for each forest type. Our work suggests that low severity fire in red fir forests and moderate severity fire in ponderosa pine and white fir-sugar pine forests would restore vertical and horizontal canopy structures believed to have been common prior to the start of widespread fire suppression in the early 1900s. The fusion of LiDAR and Landsat data identified post-fire structural conditions that would not be identified by Landsat alone, suggesting a broad applicability of combining Landsat and LiDAR data for landscape-scale structural analysis for fire management.

California↗
USGS2016

Landscape-scale habitat selection by fishers translocated to the Olympic Peninsula of Washington

The fisher was extirpated from much of the Pacific Northwestern United States during the mid- to late-1900s and is now proposed for federal listing as a threatened species in all or part of its west coast range. Following the translocation of 90 fishers from central British Columbia, Canada, to the Olympic Peninsula of Washington State from 2008 to 2010, we investigated the landscape-scale habitat selection of reintroduced fishers across a broad range of forest ages and disturbance histories, providing the first information on habitat relationships of newly reintroduced fishers in coastal coniferous forests in the Pacific Northwest. We developed 17 a priori models to evaluate several habitat-selection hypotheses based on premises of habitat models used to forecast habitat suitability for the reintroduced population. Further, we hypothesized that female fishers, because of their smaller body size than males, greater vulnerability to predation, and specific reproductive requirements, would be more selective than males for mid- to late-seral forest communities, where complex forest structural elements provide secure foraging, resting, and denning sites. We assessed 11 forest structure and landscape characteristics within the home range core-areas used by 19 females and 12 males and within randomly placed pseudo core areas that represented available habitats. We used case-controlled logistic regression to compare the characteristics of used and pseudo core areas and to assess selection by male and female fishers. Females were more selective of core area placement than males. Fifteen of 19 females (79%) and 5 of 12 males (42%) selected core areas within federal lands that encompassed primarily forests with an overstory of mid-sized or large trees. Male fishers exhibited only weak selection for core areas dominated by forests with an overstory of small trees, primarily on land managed for timber production or at high elevations. The amount of natural open area best distinguished the use of core areas between males and females, with females using substantially less natural open area than males. Although sex-specific selection has been suspected for fishers, we identified factors that distinguish the selection of core areas by females from those of males, information which will be valuable to managers planning reintroductions or providing suitable habitat to promote fisher recovery in the Pacific Northwest.

Washington↗
USGS2007

Landscape scale controls on the vascular plant component of dissolved organic carbon across a freshwater delta

Lignin phenol concentrations and compositions were determined on dissolved organic carbon (DOC) extracts (XAD resins) within the Sacramento-San Joaquin River Delta (the Delta), the tidal freshwater portion of the San Francisco Bay Estuary, located in central California, USA. Fourteen stations were sampled, including the following habitats and land-use types: wetland, riverine, channelized waterway, open water, and island drains. Stations were sampled approximately seasonally from December, 1999 through May, 2001. DOC concentrations ranged from 1.3 mg L -1 within the Sacramento River to 39.9 mg L -1 at the outfall from an island drain (median 3.0 mg L -1 ), while lignin concentrations ranged from 3.0 &mu;L -1 within the Sacramento River to 111 &mu;L -1 at the outfall from an island drain (median 11.6 &mu;L -1 ). Both DOC and lignin concentrations varied significantly among habitat/land-use types and among sampling stations. Carbon-normalized lignin yields ranged from 0.07 mg (100 mg OC) -1 at an island drain to 0.84 mg (100 mg OC) -1 for a wetland (median 0.36 mg (100 mg OC) -1 ), and also varied significantly among habitat/land-use types. A simple mass balance model indicated that the Delta acted as a source of lignin during late autumn through spring (10-83% increase) and a sink for lignin during summer and autumn (13-39% decrease). Endmember mixing models using S:V and C:V signatures of landscape scale features indicated strong temporal variation in sources of DOC export from the Delta, with riverine source signatures responsible for 50% of DOC in summer and winter, wetland signatures responsible for 40% of DOC in summer, winter, and late autumn, and island drains responsible for 40% of exported DOC in late autumn. A significant negative correlation was observed between carbon-normalized lignin yields and DOC bioavailability in two of the 14 sampling stations. This study is, to our knowledge, the first to describe organic vascular plant DOC sources at the level of localized landscape features, and is also the first to indicate a significant negative correlation between lignin and DOC bioavailability within environmental samples. Based upon observed trends: (1) Delta features exhibit significant spatial variability in organic chemical composition, and (2) localized Delta features appear to exert strong controls on terrigenous DOC as it passes through the Delta and is exported into the Pacific Ocean.

California↗
USGS2015

Machine learning for predicting soil classes in three semi-arid landscapes

Mapping the spatial distribution of soil taxonomic classes is important for informing soil use and management decisions. Digital soil mapping (DSM) can quantitatively predict the spatial distribution of soil taxonomic classes. Key components of DSM are the method and the set of environmental covariates used to predict soil classes. Machine learning is a general term for a broad set of statistical modeling techniques. Many different machine learning models have been applied in the literature and there are different approaches for selecting covariates for DSM. However, there is little guidance as to which, if any, machine learning model and covariate set might be optimal for predicting soil classes across different landscapes. Our objective was to compare multiple machine learning models and covariate sets for predicting soil taxonomic classes at three geographically distinct areas in the semi-arid western United States of America (southern New Mexico, southwestern Utah, and northeastern Wyoming). All three areas were the focus of digital soil mapping studies. Sampling sites at each study area were selected using conditioned Latin hypercube sampling (cLHS). We compared models that had been used in other DSM studies, including clustering algorithms, discriminant analysis, multinomial logistic regression, neural networks, tree based methods, and support vector machine classifiers. Tested machine learning models were divided into three groups based on model complexity: simple, moderate, and complex. We also compared environmental covariates derived from digital elevation models and Landsat imagery that were divided into three different sets: 1) covariates selected a priori by soil scientists familiar with each area and used as input into cLHS, 2) the covariates in set 1 plus 113 additional covariates, and 3) covariates selected using recursive feature elimination. Overall, complex models were consistently more accurate than simple or moderately complex models. Random forests (RF) using covariates selected via recursive feature elimination was consistently the most accurate, or was among the most accurate, classifiers between study areas and between covariate sets within each study area. We recommend that for soil taxonomic class prediction, complex models and covariates selected by recursive feature elimination be used. Overall classification accuracy in each study area was largely dependent upon the number of soil taxonomic classes and the frequency distribution of pedon observations between taxonomic classes. Individual subgroup class accuracy was generally dependent upon the number of soil pedon observations in each taxonomic class. The number of soil classes is related to the inherent variability of a given area. The imbalance of soil pedon observations between classes is likely related to cLHS. Imbalanced frequency distributions of soil pedon observations between classes must be addressed to improve model accuracy. Solutions include increasing the number of soil pedon observations in classes with few observations or decreasing the number of classes. Spatial predictions using the most accurate models generally agree with expected soil–landscape relationships. Spatial prediction uncertainty was lowest in areas of relatively low relief for each study area.

New Mexico, Utah, Wyoming↗
USGS2016

Using NDVI to measure precipitation in semi-arid landscapes

Measuring precipitation in semi-arid landscapes is important for understanding the processes related to rainfall and run-off; however, measuring precipitation accurately can often be challenging especially within remote regions where precipitation instruments are scarce. Typically, rain-gauges are sparsely distributed and research comparing rain-gauge and RADAR precipitation estimates reveal that RADAR data are often misleading, especially for monsoon season convective storms. This study investigates an alternative way to map the spatial and temporal variation of precipitation inputs along ephemeral stream channels using Normalized Difference Vegetation Index (NDVI) derived from Landsat Thematic Mapper imagery. NDVI values from 26 years of pre- and post-monsoon season Landsat imagery were derived across Yuma Proving Ground (YPG), a region covering 3,367 km 2 of semiarid landscapes in southwestern Arizona, USA. The change in NDVI from a pre-to post-monsoon season image along ephemeral stream channels explained 73% of the variance in annual monsoonal precipitation totals from a nearby rain-gauge. In addition, large seasonal changes in NDVI along channels were useful in determining when and where flow events have occurred.

Arizona↗
USGS2022

Sediment source fingerprinting as an aid to large-scale landscape conservation and restoration: A review for the Mississippi River Basin

Reliable quantitative information on sediment sources to rivers is critical to mitigate contamination and target conservation and restoration actions. However, the determination of the relative importance of sediment sources is complicated at the scale of large river basins by immense variability in erosional processes and sediment sources over space and time, heterogeneity in sediment transport and deposition, and a paucity of sediment monitoring data. Sediment source fingerprinting is an increasingly adopted field-based technique that identifies the nature and relative source contribution of sediment transported in waterways. Notably, sediment source fingerprinting provides information that is independent of other field, modeling, or remotely sensed techniques. However, the diversity in sediment fingerprinting sampling, analytical, and interpretive methods has been recognized as a problem in terms of developing standardized procedures for its application at the scale of large river basins. Accordingly, this review focuses on established sediment source fingerprinting studies conducted within the Mississippi River Basin (MRB), summarizes unique information provided by sediment source fingerprinting that is distinct from traditional monitoring techniques, evaluates consistency and reliability of methodological approaches among MRB studies, and provides prospects for the use of the sediment source fingerprinting technique as an aid to large-scale landscape conservation and restoration under current management frameworks. Most established MRB studies got creditable fingerprinting results and considered near-channel sources as the dominant sediment sources in most cases, while the comparability of their results suffers from a lack of standardization in procedural steps. Findings from MRB studies demonstrate that sediment source fingerprinting is a highly valuable and reliable sediment source assessment approach to assist land and water resource management under current management frameworks, but efforts are still needed to make this technique ready to be used in a more predominant way in large-scale landscape conservation and restoration efforts. We summarized research needs and suggested the best fingerprinting practices for management purposes with the aim of ensuring that this technique is as robust and reliable as it moves forward.

Mississippi River Basin↗
USGS2020

Habitat use by tiger prey in Thailand’s Western Forest Complex: What will it take to fill a half-full tiger landscape?

Tiger populations are declining globally, and depletion of major ungulate prey is an important contributing factor. To better understand factors affecting prey distribution in Thailand’s Western Forest Complex (WEFCOM), we conducted sign surveys for gaur (Bos gaurus ), banteng ( Bos javanicus ), and sambar ( Rusa unicolor ) along 3517 1-km transects and used occupancy models to identify important covariates associated with habitat use by each species. Habitat use by both gaur and sambar was lowest in areas closest to human settlements, although sambar preferred lower slopes near streams whereas gaur preferred steeper slopes at higher elevations. Banteng were found in only one of 17 protected areas (Huai Kha Khaeng [HKK] Wildlife Sanctuary), where they used low elevations and low slopes. We used these modeled relationships to predict occurrence of gaur, sambar, and banteng across each square km of the 19,000 km 2 WEFCOM landscape, using > 60 % occupancy probability to define suitable habitat use for each species. Based on this criterion, gaur and sambar occupied 28 and 50 % of suitable habitat in WEFCOM, and banteng occupied 57 % of suitable habitat in HKK. We used our models to assess the effectiveness of two hypothetical conservation initiatives. First, we modeled the impact of decreasing human activities around nine villages in the core of WEFCOM, which increased predicted suitable habitat in WEFCOM to 68 and 75 % for guar and sambar. We also modeled the extent of potential banteng habitat that still remains in the other 16 protected areas. This could result in a 4-fold increase in banteng suitable habitat in WEFCOM. This is the first study to use occupancy surveys to determine where large prey species can be restored to support management to increase the distribution of tigers, and potentially fill a half-full tiger landscape.

Journal for Nature Conservation↗
USGS2005

Paleoenvironmental analyses of an organic deposit from an erosional landscape remnant, Arctic Coastal Plain of Alaska

The dominant landscape process on the Arctic Coastal Plain of northern Alaska is the formation and drainage of thaw lakes. Lakes and drained thaw-lake basins account for approximately 75% of the modern surface expression of the Barrow Peninsula. The thaw-lake cycle usually obliterates lacustrine or peat sediments from previous cycles, which could otherwise be used for paleoecological reconstruction of long-term landscape and vegetation changes. Several possible erosional remnants of a former topographic surface that predates the formation of the thaw lakes have been tentatively identified. These remnants are characterized by a higher elevation, a thick organic layer with very high ground ice content in the upper permafrost and a plant community somewhat atypical of the region. Ten soil cores were collected from one site, and one core was intensively sampled for soil organic carbon content, pollen analysis and 14 C dating. The lowest level of the organic sediments represents the earliest phase of plant growth and dates to ca. 9000 cal BP. Palynological evidence indicates the presence of mesic shrub tundra (including sedge, birch, willow and heath vegetation), and microfossil indicators point to wetter eutrophic conditions during this period. Carbon accumulation was rapid due to high net primary productivity in a relatively nutrient-rich environment. These results are interpreted as the local response to ameliorating climate during the early Holocene. The middle Holocene portion of the record contains an unconformity, indicating that between 8200 and 4200 cal BP sediments were eroded from the site, presumably in response to wind activity during a drier period centered around 4500 cal BP. The modern vegetation community of the erosional remnant was established after 4200 cal BP and peat growth resumed. During the late Holocene, carbon accumulation rates (CARs) were greatly reduced in response to the combined effects of declining productivity associated with climatic cooling, and increased nutrient stress as paludification and permafrost aggradation sequestered mineral nutrients.

Alaska↗
USGS2015

Rangeland monitoring reveals long-term plant responses to precipitation and grazing at the landscape scale

Managers of rangeland ecosystems require methods to track the condition of natural resources over large areas and long periods of time as they confront climate change and land use intensification. We demonstrate how rangeland monitoring results can be synthesized using ecological site concepts to understand how climate, site factors, and management actions affect long-term vegetation dynamics at the landscape-scale. Forty-six years of rangeland monitoring conducted by the Bureau of Land Management (BLM) on the Colorado Plateau reveals variable responses of plant species cover to cool-season precipitation, land type (ecological site groups), and grazing intensity. Dominant C 3 perennial grasses (Achnatherum hymenoides , Hesperostipa comata) , which are essential to support wildlife and livestock on the Colorado Plateau, had responses to cool-season precipitation that were at least twice as large as the dominant C 4 perennial grass (Pleuraphis jamesii) and woody vegetation. However, these C 3 perennial grass responses to precipitation were reduced by nearly one-third on grassland ecological sites with fine- rather than coarse-textured soils, and there were no detectable C 3 perennial grass responses to precipitation on ecological sites dominated by a dense-growing shrub, Coleogyne ramosissima . Heavy grazing intensity further reduced the responses of C 3 perennial grasses to cool-season precipitation on ecological sites with coarse-textured soils and surprisingly reduced the responses of shrubs as well. By using ecological site groups to assess rangeland condition, we were able to improve our understanding of the long-term relationships between vegetation change and climate, land use, and site characteristics, which has important implications for developing landscape-scale monitoring strategies.

Arizona, Colorado, New Mexico, Utah↗
USGS2016

Lesser prairie-chicken avoidance of trees in a grassland landscape

Grasslands are among the most imperiled ecosystems in North America. Reasons that grasslands are threatened include conversion to row-crop agriculture, fragmentation, and changes in fire regimes. The reduction of fire processes in remaining prairies has resulted in tree encroachment and establishment in grasslands, further reducing grassland quantity and quality. Grassland birds have been experiencing precipitous population declines in recent decades, commensurate with landscape changes to grasslands. The lesser prairie-chicken ( Tympanuchus pallidicinctus Ridgway) is a declining species of prairie grouse of conservation concern. We used second- and third-order habitat selection metrics to test if female lesser prairie-chickens avoid grasslands where trees were present. Our results indicated that female lesser prairie-chickens selected habitats avoiding the nearest trees by 283 m on average, nearly twice as far as would be expected at random. Lesser prairie-chickens were 40 times more likely to use habitats with tree densities of 0 trees ∙ ha − 1 than habitats with 5 trees ∙ ha − 1 . Probability of use indicated that lesser prairie-chickens were 19 times more likely to use habitats 1000 m from the nearest tree when compared with using habitats 0 m from the nearest tree. Nest survival was not affected at densities < 2 trees ∙ ha − 1 ; however, we could not test if nest survival was affected at greater tree densities as no nests were detected at densities > 2 trees ∙ ha − 1 . Avoidance of trees could be due to perceived increased predation risk, reduced habitat quality, or a combination of these potentially confounding factors. Preventing further establishment and expansion of trees in landscapes occupied by lesser prairie-chickens could contribute to the continued persistence of the species. Additionally, restoring grasslands through tree removal may facilitate conservation efforts for grassland species such as the lesser prairie-chicken by improving habitat quality and promoting expansion of occupied range.

Kansas↗
USGS2011

Relating nutrient and herbicide fate with landscape features and characteristics of 15 subwatersheds in the Choptank River watershed

Excess nutrients and agrochemicals from non-point sources contribute to water quality impairment in the Chesapeake Bay watershed and their loading rates are related to land use, agricultural practices, hydrology, and pollutant fate and transport processes. In this study, monthly baseflow stream samples from 15 agricultural subwatersheds of the Choptank River in Maryland USA (2005 to 2007) were characterized for nutrients, herbicides, and herbicide transformation products. High-resolution digital maps of land use and forested wetlands were derived from remote sensing imagery. Examination of landscape metrics and water quality data, partitioned according to hydrogeomorphic class, provided insight into the fate, delivery, and transport mechanisms associated with agricultural pollutants. Mean Nitrate-N concentrations (4.9 mg/L) were correlated positively with percent agriculture (R 2 = 0.56) and negatively with percent forest (R 2 = 0.60). Concentrations were greater ( p = 0.0001) in the well-drained upland (WDU) hydrogeomorphic region than in poorly drained upland (PDU), reflecting increased denitrification and reduced agricultural land use intensity in the PDU landscape due to the prevalence of hydric soils. Atrazine and metolachlor concentrations (mean 0.29 &mu;g/L and 0.19 &mu;g/L) were also greater ( p = 0.0001) in WDU subwatersheds than in PDU subwatersheds. Springtime herbicide concentrations exhibited a strong, positive correlation (R 2 = 0.90) with percent forest in the WDU subwatersheds but not in the PDU subwatersheds. In addition, forested riparian stream buffers in the WDU were more prevalent than in the PDU where forested patches are typically not located near streams, suggesting an alternative delivery mechanism whereby volatilized herbicides are captured by the riparian forest canopy and subsequently washed off during rainfall. Orthophosphate, CIAT (6-chloro- N -(1-methylethyl)-1,3,5-triazine-2,4-diamine), CEAT (6-chloro- N -ethyl-1,3,5-triazine-2,4-diamine), and MESA (2-[(2-ethyl-6-methylphenyl) (2-methoxy-1-methylethyl)amino]-2-oxoethanesulfonic acid) were also analyzed. These findings will assist efforts in targeting implementation of conservation practices to the most environmentally-critical areas within watersheds to achieve water quality improvements in a cost-effective manner.

Delaware, Maryland↗
USGS2013

Landscape factors and hydrology influence mercury concentrations in wading birds breeding in the Florida Everglades, USA

The hydrology of wetland ecosystems is a key driver of both mercury (Hg) methylation and waterbird foraging ecology, and hence may play a fundamental role in waterbird exposure and risk to Hg contamination. However, few studies have investigated hydrological factors that influence waterbird Hg exposure. We examined how several landscape-level hydrological variables influenced Hg concentrations in great egret and white ibis adults and chicks in the Florida Everglades. The great egret is a visual “exploiter” species that tolerates lower prey densities and is less sensitive to hydrological conditions than is the white ibis, which is a tactile “searcher” species that pursues higher prey densities in shallow water. Mercury concentrations in adult great egrets were most influenced by the spatial region that they occupied in the Everglades (higher in the southern region); whereas the number of days a site was dry during the previous dry season was the most important factor influencing Hg concentrations in adult ibis (Hg concentrations increased with the number of days dry). In contrast, Hg concentrations in egret chicks were most influenced by calendar date (increasing with date), whereas Hg concentrations in ibis chicks were most influenced by chick age, region, and water recession rate (Hg concentrations decreased with age, were higher in the southern regions, and increased with positive water recession rates). Our results indicate that both recent (preceding two weeks) hydrological conditions, and those of the prior year, influence Hg concentrations in wading birds. Further, these results suggest that Hg exposure in wading birds is driven by complex relationships between wading bird behavior and life stage, landscape hydrologic patterns, and biogeochemical processes.

Florida↗
USGS2020

Estuarine submerged aquatic vegetation habitat provides organic carbon storage across a shifting landscape

Submerged aquatic vegetation (SAV) thrives across the estuarine salinity gradient providing valuable ecosystem services. Within the saline portion of estuaries, seagrass areas are frequently cited as hotspots for their role in capturing and retaining organic carbon (C org ). Non-seagrass SAV, located in the fresh to brackish estuarine areas, may also retain significant soil C org , yet their role remains unquantified. Given rapidly occurring landscape and salinity changes due to human and natural disturbances, landscape level carbon pool estimates from estuarine SAV habitat blue carbon estimates are needed. We assessed C org stocks in SAV habitat soils from estuarine freshwater to saline habitats (interior deltaic) to saline barrier islands (Chandeleur Island) within the Mississippi River Delta Plain (MRDP), Louisiana, USA. SAV habitats contain C org stocks equivalent to those reported for other estuarine vegetation types (seagrass, salt marsh, mangrove). Interior deltaic SAV C org stocks (231.6 ± 19.5 Mg C org ha −1 ) were similar across the salinity gradient, and significantly higher than at barrier island sites (56.6 ± 10.4 Mg C org ha −1 ). Within the MRDP, shallow water SAV habitat covers up to an estimated 28,000 ha, indicating that soil C org storage is potentially 6.4 ± 0.1 Tg representing an unaccounted C org pool. Extrapolated across Louisiana, and the Gulf of Mexico, this represents a major unaccounted pool of soil C org . As marshes continue to erode, the ability of coastal SAV habitat to offset some of the lost carbon sequestration may be valuable. Our estimates of C org sequestration rates indicated that conversion of eroding marsh to potential SAV habitat may help to offset the reduction of C org sequestration rates. Across Louisiana, we estimated SAV to offset this loss by as much as 79,000 Mg C yr −1 between the 1960s and 2000s.

Louisiana↗
USGS2015

Landscape community genomics: understanding eco-evolutionary processes in complex environments

Extrinsic factors influencing evolutionary processes are often categorically lumped into interactions that are environmentally (e.g., climate, landscape) or community-driven, with little consideration of the overlap or influence of one on the other. However, genomic variation is strongly influenced by complex and dynamic interactions between environmental and community effects. Failure to consider both effects on evolutionary dynamics simultaneously can lead to incomplete, spurious, or erroneous conclusions about the mechanisms driving genomic variation. We highlight the need for a landscape community genomics (LCG) framework to help to motivate and challenge scientists in diverse fields to consider a more holistic, interdisciplinary perspective on the genomic evolution of multi-species communities in complex environments.

Trends in Ecology and Evolution↗
USGS2001

Effects of Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper plus radiometric and geometric calibrations and corrections on landscape characterization

The Thematic Mapper (TM) instruments onboard Landsats 4 and 5 provide high-quality imagery appropriate for many different applications, including land cover mapping, landscape ecology, and change detection. Precise calibration was considered to be critical to the success of the Landsat 7 mission and, thus, issues of calibration were given high priority during the development of the Enhanced Thematic Mapper Plus (ETM+). Data sets from the Landsat 5 TM are not routinely corrected for a number of radiometric and geometric artifacts, including memory effect, gain/bias, and interfocal plane misalignment. In the current investigation, the effects of correcting vs. not correcting these factors were investigated for several applications. Gain/bias calibrations were found to have a greater impact on most applications than did memory effect calibrations. Correcting interfocal plane offsets was found to have a moderate effect on applications. On June 2, 1999, Landsats 5 and 7 data were acquired nearly simultaneously over a study site in the Niobrara, NE area. Field radiometer data acquired at that site were used to facilitate crosscalibrations of Landsats 5 and 7 data. Current findings and results from previous investigations indicate that the internal calibrator of Landsat 5 TM tracked instrument gain well until 1988. After this, the internal calibrator diverged from the data derived from vicarious calibrations. Results from this study also indicate very good agreement between prelaunch measurements and vicarious calibration data for all Landsat 7 reflective bands except Band 4. Values are within about 3.5% of each other, except for Band 4, which differs by 10%. Coefficient of variation (CV) values derived from selected targets in the imagery were also analyzed. The Niobrara Landsat 7 imagery was found to have lower CV values than Landsat 5 data, implying that lower levels of noise characterize Landsat 7 data than current Landsat 5 data. It was also found that following radiometric normalization, the Normalized Difference Vegetation Index (NDVI) imagery and classification products of Landsats 5 and 7 were very similar. This implies that data from the two sensors can be used to measure and monitor the same landscape phenomena and that Landsats 5 and 7 data can be used interchangeably with proper caution. In addition, it was found that difference imagery produced using Landsat 7 ETM+ data are of excellent quality.

Remote Sensing of Environment↗
USGS2004

Landscape scale measures of steelhead (Oncorhynchus mykiss) bioenergetic growth rate potential in Lake Michigan and comparison with angler catch rates

The relative quality of a habitat can influence fish consumption, growth, mortality, and production. In order to quantify habitat quality, several authors have combined bioenergetic and foraging models to generate spatially explicit estimates of fish growth rate potential (GRP). However, the capacity of GRP to reflect the spatial distributions of fishes over large areas has not been fully evaluated. We generated landscape scale estimates of steelhead ( Oncorhynchus mykiss ) GRP throughout Lake Michigan for 1994-1996, and used these estimates to test the hypotheses that GRP is a good predictor of spatial patterns of steelhead catch rates. We used surface temperatures (measured with AVHRR satellite imagery) and acoustically measured steelhead prey densities (alewife, Alosa pseudoharengus ) as inputs for the GRP model. Our analyses demonstrate that potential steelhead growth rates in Lake Michigan are highly variable in both space and time. Steelhead GRP tended to increase with latitude, and mean GRP was much higher during September 1995, compared to 1994 and 1996. In addition, our study suggests that landscape scale measures of GRP are not good predictors of steelhead catch rates throughout Lake Michigan, but may provide an index of interannual variation in system-wide habitat quality.

Lake Michigan↗
USGS2009

Landsat mapping of local landscape change: The satellite-era context

To set the stage for a vulnerability analysis, investigators must describe and understand the geographic context, including physical characteristics of the landscape and the political and socioeconomic milieu of the population (Jianchu et al . 2005). Vulnerability studies focus on a particular place, at a specific time through its three dimensions, exposure, sensitivity, and adaptive capacity; therefore, understanding place is essential to analyzing vulnerability. Land-use studies are essential to understanding place because they generalize human activities on the physical landscape. Essentially, land use indicates past human decisions and actions, environmental constraints, and, in some cases, gives insight into subsequent change. Like vulnerability, land use is particular to a place at a certain time, and the analysis of that land use can be used as a baseline for future change and its implications. Vulnerability and land use are linked by the concept of place and are fundamental to contemporary research on human–environment interactions. Although the literature on land use, land-use change, and climate change is extensive, the land-use component of vulnerability is usually conceptualized as a feedback mechanism to climate change: forest cutting releases carbon dioxide, which increases atmospheric carbon dioxide concentrations, which increases radiative forcing, which changes climate, and which ultimately changes land cover and subsequent land use (e.g. DeFries and Bounoua 2004; Jianchu et al . 2005; Salinger et al . 2005; Watson 2005). Moreover, land use is rarely specifically identified as a component of vulnerability.

Book chapter↗