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51.
Summary
Azolla accessions (section Azolla) from the germplasm collections of the International Rice Research Institute and Washington State University were fingerprinted and classified by enzyme electrophoresis and leaf trichome morphology. A. filiculoides was enzymatically distinctive and also reliably identified by its prominent one-celled trichomes. Neotropical accessions labelled as A. filiculoides proved to be members of other species. Two groups of isolates were designated A. rubra, but those from Japan were identified as A. filiculoides. The A. rubra of Australia-New Zealand was biochemically unique and possessed less protuberant trichomes than A. filiculoides. A. microphylla, A. mexicana, and A. caroliniana were phenetically similar, but a. microphylla was identifiable from the others in the banding patterns of certain enzymes. A. mexicana and A. caroliniana were closely related enzymatically. The two-celled leaf trichomes of these three species were similar in size and shape. 相似文献
52.
Kamlesh Jangid Mark A. Williams Thomas M. Schmidt William B. Whitman 《Soil biology & biochemistry》2011,43(10):2184-2193
The response of soil microbial communities following changes in land-use is governed by multiple factors. The objectives of this study were to investigate (i) whether soil microbial communities track the changes in aboveground vegetation during succession; and (ii) whether microbial communities return to their native state over time. Two successional gradients with different vegetation were studied at the W. K. Kellogg Biological Station, Michigan. The first gradient comprised a conventionally tilled cropland (CT), mid-succession forest (SF) abandoned from cultivation prior to 1951, and native deciduous forest (DF). The second gradient comprised the CT cropland, early-succession grassland (ES) restored in 1989, and long-term mowed grassland (MG). With succession, the total microbial PLFAs and soil microbial biomass C consistently increased in both gradients. While bacterial rRNA gene diversity remained unchanged, the abundance and composition of many bacterial phyla changed significantly. Moreover, microbial communities in the relatively pristine DF and MG soils were very similar despite major differences in soil properties and vegetation. After >50 years of succession, and despite different vegetation, microbial communities in SF were more similar to those in mature DF than in CT. In contrast, even after 17 years of succession, microbial communities in ES were more similar to CT than endpoint MG despite very different vegetation between CT and ES. This result suggested a lasting impact of cultivation history on the soil microbial community. With conversion of deciduous to conifer forest (CF), there was a significant change in multiple soil properties that correlated with changes in microbial biomass, rRNA gene diversity and community composition. In conclusion, history of land-use was a stronger determinant of the composition of microbial communities than vegetation and soil properties. Further, microbial communities in disturbed soils apparently return to their native state with time. 相似文献
53.
Arendt AA Echelmeyer KA Harrison WD Lingle CS Valentine VB 《Science (New York, N.Y.)》2002,297(5580):382-386
We have used airborne laser altimetry to estimate volume changes of 67 glaciers in Alaska from the mid-1950s to the mid-1990s. The average rate of thickness change of these glaciers was -0.52 m/year. Extrapolation to all glaciers in Alaska yields an estimated total annual volume change of -52 +/- 15 km3/year (water equivalent), equivalent to a rise in sea level (SLE) of 0.14 +/- 0.04 mm/year. Repeat measurements of 28 glaciers from the mid-1990s to 2000-2001 suggest an increased average rate of thinning, -1.8 m/year. This leads to an extrapolated annual volume loss from Alaska glaciers equal to -96 +/- 35 km3/year, or 0.27 +/- 0.10 mm/year SLE, during the past decade. These recent losses are nearly double the estimated annual loss from the entire Greenland Ice Sheet during the same time period and are much higher than previously published loss estimates for Alaska glaciers. They form the largest glaciological contribution to rising sea level yet measured. 相似文献
54.
Peterman William E. Winiarski Kristopher J. Moore Chloe E. Carvalho Carolina da Silva Gilbert Anthony L. Spear Stephen F. 《Landscape Ecology》2019,34(9):2197-2208
Landscape Ecology - Landscape resistance surfaces are often used to address questions related to movement, dispersal, or population connectivity. However, modeling landscape resistance is... 相似文献
55.
Louis R. Iverson Frank R. ThompsonIII Stephen Matthews Matthew Peters Anantha Prasad William D. Dijak Jacob Fraser Wen J. Wang Brice Hanberry Hong He Maria Janowiak Patricia Butler Leslie Brandt Christopher Swanston 《Landscape Ecology》2017,32(7):1327-1346
Context
Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process-based ecosystem and landscape models, respectively, were used concurrently on four regional climate change assessments in the eastern Unites States.Objectives
We compared predictions for 30 species from TreeAtlas, Linkages, and LANDIS PRO, using two climate change scenarios on four regions, to derive a more robust assessment of species change in response to climate change.Methods
We calculated the ratio of future importance or biomass to current for each species, then compared agreement among models by species, region, and climate scenario using change classes, an ordinal agreement score, spearman rank correlations, and model averaged change ratios.Results
Comparisons indicated high agreement for many species, especially northern species modeled to lose habitat. TreeAtlas and Linkages agreed the most but each also agreed with many species outputs from LANDIS PRO, particularly when succession within LANDIS PRO was simulated to 2300. A geographic analysis showed that a simple difference (in latitude degrees) of the weighted mean center of a species distribution versus the geographic center of the region of interest provides an initial estimate for the species’ potential to gain, lose, or remain stable under climate change.Conclusions
This analysis of multiple models provides a useful approach to compare among disparate models and a more consistent interpretation of the future for use in vulnerability assessments and adaptation planning.56.
Maria Garcia-Martin Nora Fagerholm Claudia Bieling Dimitris Gounaridis Thanasis Kizos Anu Printsmann Matthias Müller Juraj Lieskovský Tobias Plieninger 《Landscape Ecology》2017,32(11):2133-2150
Context
Human–nature interactions are reflected in the values people assign to landscapes. These values shape our understanding and actions as landscape co-creators, and need to be taken into account to achieve an integrated management of the landscape that involves civil society.Objectives
The aim of this research was to increase the current knowledge on the most and least common landscape values perceived by local stakeholders, the patterns in the spatial distribution of values, and their connection to different socio-economic backgrounds and landscape characteristics across Europe.Methods
The research consisted of a cross-site comparison study on how landscape values are perceived in six areas of Europe using Public Participation GIS surveys. Answers were analysed combining contingency tables, spatial autocorrelation and bivariate correlation methods, kernel densities, land cover ratios, and viewshed analyses. Results were discussed in the light of findings derived from other European participatory mapping studies.Results
We identified shared patterns in the perception of landscape values across Europe. Recreation, aesthetics, and social fulfilment were the most common values. Landscape values showed common spatial patterns mainly related to accessibility and the presence of water, settlements, and cultural heritage. However, respondents in each study site had their own preferences connected to the intrinsic characteristics of the local landscape and culture.Conclusions
The results encourage land planners and researchers to approach landscape values in relation to socio-cultural and bio-physical land characteristics comprehensibly, acknowledging the complexity in the relationship between people’s perception and the landscape, to foster more effective and inclusive landscape management strategies.57.
John B. Graham Joan I. Nassauer William S. Currie Herbert Ssegane M. Cristina Negri 《Landscape Ecology》2017,32(5):1023-1037
Context
Wild bee populations are currently under threat, which has led to recent efforts to increase pollinator habitat in North America. Simultaneously, U.S. federal energy policies are beginning to encourage perennial bioenergy cropping (PBC) systems, which have the potential to support native bees.Objectives
Our objective was to explore the potentially interactive effects of crop composition, total PBC area, and PBC patches in different landscape configurations.Methods
Using a spatially-explicit modeling approach, the Lonsdorf model, we simulated the impacts of three perennial bioenergy crops (PBC: willow, switchgrass, and prairie), three scenarios with different total PBC area (11.7, 23.5 and 28.8% of agricultural land converted to PBC) and two types of landscape configurations (PBC in clustered landscape patterns that represent realistic future configurations or in dispersed neutral landscape models) on a nest abundance index in an Illinois landscape.Results
Our modeling results suggest that crop composition and PBC area are particularly important for bee nest abundance, whereas landscape configuration is associated with bee nest abundance at the local scale but less so at the regional scale.Conclusions
Strategies to enhance wild bee habitat should therefore emphasize the crop composition and amount of PBC.58.
Alencar Xavier Benjamin Hall Shaun Casteel William Muir Katy Martin Rainey 《Euphytica》2017,213(8):200
Soybean yield components and agronomic traits are connected through physiological pathways that impose tradeoffs through genetic and environmental constraints. Our primary aim is to assess the interdependence of soybean traits by using unsupervised machine learning techniques to divide phenotypic associations into environmental and genetic associations. This study was performed on large scale, jointly analyzing 14 quantitative traits in a large multi-parental population designed for genetic studies. We collected phenotypes from 2012 to 2015 from a soybean nested association panel with 40 families of approximately 140 individuals each. Pearson and Spearman correlations measured phenotypic associations. A multivariate mixed linear model provided genotypic and environmental correlations. To evaluate relationships among traits, the study used principal component and undirected graphical models from phenotypic, genotypic, and environmental correlation matrices. Results indicate that high phenotypic correlation occurs when traits display both genetic and environmental correlations. In genetic terms, length of reproductive period, node number, and canopy coverage play important roles in determining yield potential. Optimal grain yield production occurs when the growing environment favors faster canopy closure and extended reproductive length. Environmental associations found among yield components give insight into the nature of yield component compensation. The use of unsupervised learning methods provides a good framework for investigating interactions among various quantitative traits and defining target traits for breeding. 相似文献
59.
Boucher Dominique Gauthier Sylvie Thiffault Nelson Marchand William Girardin Martin Urli Morgane 《New Forests》2020,51(4):543-571
New Forests - Climate change is projected to increase fire severity and frequency in the boreal forest, but it could also directly affect post-fire recruitment processes by impacting seed... 相似文献
60.
Portfolio theory, an established technique in the selection of stocks and financial instruments for investment purposes, was used as a means of selecting an economic mix of veterinary interventions in a dairy herd. The expected return on investment in six veterinary services and the associated standard deviations (as measures of risk) were calculated using computer simulation modeling techniques. Mathematical programming techniques were applied to identify the optimal combinations of veterinary interventions which maximize expected financial returns while minimizing risk. Parametric analysis was used to show how risk (standard deviation) increases as the required expected return is increased along the efficient risk-return frontier of these optimal combinations. This exercise emphasizes the importance of regarding risk in addition to expected return when considering investment in veterinary services. 相似文献