Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

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.

     

Assessing wild bees in perennial bioenergy landscapes: effects of bioenergy crop composition,landscape configuration,and bioenergy crop area

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.

     

Landscape dynamics of floral resources affect the supply of a biodiversity-dependent cultural ecosystem service

Context

Cultural ecosystem services, many of which depend on biodiversity, are recognized as important but seldom quantified biophysically across landscapes. Furthermore, many ecosystem service models are static, and the supply of cultural ecosystem services may be misrepresented if seasonal shifts in biotic communities are ignored.

Objectives

We modeled landscape dynamics of wildflower blooms in a temperate montane landscape to determine (1) how floral resources (wildflower species richness, abundance, timing, and presence of charismatic species) changed over the growing season, (2) how projected wildflower viewing hotspots varied over space and time, and (3) how spatial shifts in floral resources affected potential public access to wildflower viewing.

Methods

Data were collected at 63 sites across a rural-to-urban gradient in the Southern Appalachian Mountains (USA). Generalized linear models were used to identify factors affecting floral resources at two temporal scales. Floral resources were projected across the landscape and hotspots of wildflower viewing were quantified using overlay analysis.

Results

Floral resources were affected by topoedaphic conditions, climate, and surrounding building density and changed seasonally. Seasonal models revealed locational shifts in ecosystem service hotspots, which changed the proportion of hotspots accessible to the public and identified wildflower-viewing opportunities unnoticed by static models.

Conclusion

Relationships between landscape gradients, biodiversity, and ecosystem service supply varied seasonally, and our models identified cultural ecosystem service hotspots otherwise obscured by simple proxies. Landscape models of biodiversity-based cultural ecosystem services should include seasonal dynamics of biotic communities to avoid under- or over-emphasizing the importance of particular locations in ecosystem service assessments.

     

Using unsupervised learning techniques to assess interactions among complex traits in soybeans

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.     

How climate change might affect tree regeneration following fire at northern latitudes: a review

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...     

Pesticide contamination of the upper Elbe River and an adjacent floodplain area

Journal of Soils and Sediments - Pesticide contamination of river waters is a global problem, and therefore, authorities regularly monitor the water quality status. Especially, flood events might...     

Application of Portfolio Theory for the optimal choice of dairy veterinary management programs

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.     

Analysis of cerebrospinal fluid from field cases of some common ovine neurological diseases.

Analysis of cerebrospinal fluid (CSF) samples from normal sheep and from cases of some common neurological diseases revealed a significant increase (P less than 0.05) in the group mean CSF protein concentration for meningitis, listeriosis and spinal abscess but not for scrapie, spinal injury, ovine pregnancy toxaemia or polioencephalomalacia. The CSF white blood cell count (WBC) was significantly increased (P less than 0.05) in the meningitis group and in those cases of listeriosis which failed to respond to antibiotic therapy. All cases of bacterial infection of the central nervous system (CNS) could be identified by the combined interpretation of the protein concentration and the differential WBC count. It is concluded that CSF analysis is useful clinically in differentiating traumatic from infective spinal lesions and toxic or metabolic lesions from bacterial meningitis in sheep.     

Transendoscopic biopsy of the horse's airway mucosa

Transtracheal wash and bronchoalveolar lavage are diagnostic techniques that have been adopted from human medicine for monitoring inflammatory changes in the airway of the horse. Transendoscopic biopsy has also proven to be a valuable tool for obtaining samples of the airway mucosa in human patients. A transendoscopic technique was developed in this study for obtaining a respiratory mucosal biopsy from standing, sedated horses. Six normal adult horses were sampled at eight-week intervals for a total of three sample periods. Horses were monitored for adverse effects of the technique and none were noted. Sample sites were completely healed after eight weeks with no gross or histologic abnormalities. Biopsy samples were 3 to 4 millimeters in diameter, and 17 of 18 samples provided interpretable histological sections. Methods for handling, staining and evaluating tissue were also developed. The results of this study demonstrated that airway mucosal biopsy is a safe, repeatable technique that can be performed in the sedated, standing horse.     

Organic globules in the Tagish Lake meteorite: remnants of the protosolar disk

Coordinated transmission electron microscopy and isotopic measurements of organic globules in the Tagish Lake meteorite shows that they have elevated ratios of nitrogen-15 to nitrogen-14 (1.2 to 2 times terrestrial) and of deuterium to hydrogen (2.5 to 9 times terrestrial). These isotopic anomalies are indicative of mass fractionation during chemical reactions at extremely low temperatures (10 to 20 kelvin), characteristic of cold molecular clouds and the outer protosolar disk. The globules probably originated as organic ice coatings on preexisting grains that were photochemically processed into refractory organic matter. The globules resemble cometary carbon, hydrogen, oxygen, and nitrogen (CHON) particles, suggesting that such grains were important constituents of the solar system starting materials.