Ecological homogenization of urban USA

Author Posting. © Ecological Society of America, 2014. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Frontiers in Ecology and the Environment 12 (2014): 74-81, doi:10.1890/120374.A visually apparent but scientifically untested outcome of land-use change is homogenization across urban areas, where neighborhoods in different parts of the country have similar patterns of roads, residential lots, commercial areas, and aquatic features. We hypothesize that this homogenization extends to ecological structure and also to ecosystem functions such as carbon dynamics and microclimate, with continental-scale implications. Further, we suggest that understanding urban homogenization will provide the basis for understanding the impacts of urban land-use change from local to continental scales. Here, we show how multi-scale, multi-disciplinary datasets from six metropolitan areas that cover the major climatic regions of the US (Phoenix, AZ; Miami, FL; Baltimore, MD; Boston, MA; Minneapolis–St Paul, MN; and Los Angeles, CA) can be used to determine how household and neighborhood characteristics correlate with land-management practices, land-cover composition, and landscape structure and ecosystem functions at local, regional, and continental scales.We thank the MacroSystems Biology Program in the Emerging Frontiers Division of the Biological Sciences Directorate at NSF for support. The “Ecological Homogenization of Urban America” project was supported by a series of collaborative grants from this program (EF-1065548, 1065737, 1065740, 1065741, 1065772, 1065785, 1065831, 121238320). The work arose from research funded by grants from the NSF Long Term Ecological Research Program supporting work in Baltimore (DEB-0423476), Phoenix (BCS-1026865, DEB-0423704 and DEB-9714833), Plum Island (Boston) (OCE-1058747 and 1238212), Cedar Creek (Minneapolis–St Paul) (DEB-0620652), and Florida Coastal Everglades (Miami) (DBI-0620409)

Plant DNA barcodes and assessment of phylogenetic community structure of a tropical mixed dipterocarp forest in Brunei Darussalam (Borneo)

DNA barcoding is a fast and reliable tool to assess and monitor biodiversity and, via community phylogenetics, to investigate ecological and evolutionary processes that may be responsible for the community structure of forests. In this study, DNA barcodes for the two widely used plastid coding regions rbcL and matK are used to contribute to identification of morphologically undetermined individuals, as well as to investigate phylogenetic structure of tree communities in 70 subplots (10 × 10m) of a 25-ha forest-dynamics plot in Brunei (Borneo, Southeast Asia). The combined matrix (rbcL + matK) comprised 555 haplotypes (from ≥154 genera, 68 families and 25 orders sensu APG, Angiosperm Phylogeny Group, 2016), making a substantial contribution to tree barcode sequences from Southeast Asia. Barcode sequences were used to reconstruct phylogenetic relationships using maximum likelihood, both with and without constraining the topology of taxonomic orders to match that proposed by the Angiosperm Phylogeny Group. A third phylogenetic tree was reconstructed using the program Phylomatic to investigate the influence of phylogenetic resolution on results. Detection of non-random patterns of community assembly was determined by net relatedness index (NRI) and nearest taxon index (NTI). In most cases, community assembly was either random or phylogenetically clustered, which likely indicates the importance to community structure of habitat filtering based on phylogenetically correlated traits in determining community structure. Different phylogenetic trees gave similar overall results, but the Phylomatic tree produced greater variation across plots for NRI and NTI values, presumably due to noise introduced by using an unresolved phylogenetic tree. Our results suggest that using a DNA barcode tree has benefits over the traditionally used Phylomatic approach by increasing precision and accuracy and allowing the incorporation of taxonomically unidentified individuals into analyses

High-Dimensional Coexistence of Temperate Tree Species: Functional Traits, Demographic Rates, Life-History Stages, and Their Physical Context

Theoretical models indicate that trade-offs between growth and survival strategies of tree species can lead to coexistence across life history stages (ontogeny) and physical conditions experienced by individuals. There exist predicted physiological mechanisms regulating these trade-offs, such as an investment in leaf characters that may increase survival in stressful environments at the expense of investment in bole or root growth. Confirming these mechanisms, however, requires that potential environmental, ontogenetic, and trait influences are analyzed together. Here, we infer growth and mortality of tree species given size, site, and light characteristics from forest inventory data from Wisconsin to test hypotheses about growth-survival trade-offs given species functional trait values under different ontogenetic and environmental states. A series of regression analyses including traits and rates their interactions with environmental and ontogenetic stages supported the relationships between traits and vital rates expected from the expectations from tree physiology. A combined model including interactions between all variables indicated that relationships between demographic rates and functional traits supports growth-survival trade-offs and their differences across species in high-dimensional niche space. The combined model explained 65% of the variation in tree growth and supports a concept of community coexistence similar to Hutchinson's n-dimensional hypervolume and not a low-dimensional niche model or neutral model

Comparison of CT and PET-CT based planning of radiation therapy in locally advanced pancreatic carcinoma

Abstract Background To compare computed tomography (CT) with co-registered positron emission tomography-computed tomography (PET-CT) as the basis for delineating gross tumor volume (GTV) in unresectable, locally advanced pancreatic carcinoma (LAPC). Methods Fourteen patients with unresectable LAPC had both CT and PET images acquired. For each patient, two three-dimensional conformal plans were made using the CT and PET-CT fusion data sets. We analyzed differences in treatment plans and doses of radiation to primary tumors and critical organs. Results Changes in GTV delineation were necessary in 5 patients based on PET-CT information. In these patients, the average increase in GTV was 29.7%, due to the incorporation of additional lymph node metastases and extension of the primary tumor beyond that defined by CT. For all patients, the GTVCT versus GTVPET-CT was 92.5 ± 32.3 cm3 versus 104.5 ± 32.6 cm3 (p = 0.009). Toxicity analysis revealed no clinically significant differences between two plans with regard to doses to critical organs. Conclusion Co-registration of PET and CT information in unresectable LAPC may improve the delineation of GTV and theoretically reduce the likelihood of geographic misses.</p

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Early prediction of treatment response to high-dose salvage chemotherapy in patients with relapsed germ cell cancer using [18F]FDG PET

To assess the ability of [18F]fluorodeoxyglucose positron emission tomography for the early prediction of response in patients with relapsed metastatic germ cell tumours undergoing salvage high-dose chemotherapy. The role of positron emission tomography was compared with established means of tumour response assessment such as CT scans/MRI and serum tumour marker changes. In addition, positron emission tomography was compared with a current prognostic score which differentiates three prognostic groups with failure-free survival rates ranging from 5–50%. [18F]fluorodeoxyglucose uptake of metastases from germ cell tumours as well as CT scans and serum tumour marker were acquired after 2–3 cycles of induction chemotherapy but before the start of high-dose chemotherapy and CT scans/serum tumour marker were compared with the baseline examinations in 23 patients with relapsed germ cell tumours. To evaluate the validity of early response prediction by positron emission tomography, radiological monitoring and serum tumour marker decline, histopathologic response after resection of residual masses and/or the clinical course over 6 months after the end of treatment (relapse vs freedom of progression) were used. Overall, 10 patients (43%) achieved a marker-negative partial remission, three (13%) a marker-positive partial remission, five (22%) a disease stabilization and five (22%) progressed during treatment. Nine patients (39%) remained progression-free over 6 months following treatment, whereas 14 (61%) progressed. The outcome of high-dose chemotherapy was correctly predicted by positron emission tomography/CT scan/serum tumour marker in 91/59/48%. Eight patients with a favourably predicted outcome by CT scans plus serum tumour marker but a positive positron emission tomography prior to high-dose chemotherapy, failed treatment. This results in the following sensitivities/specificities for the prediction of failure of high-dose chemotherapy: positron emission tomography 100/78%; radiological monitoring 43/78%; serum tumour marker 15/100%. The positive and negative predictive values of positron emission tomography were 88 and 100%, respectively. As compared with the prognostic score, positron emission tomography was correctly positive in all patients of the three risk groups who failed treatment. In addition, a negative positron emission tomography correctly predicted a favourable outcome in the good and intermediate group. [18F]fluorodeoxyglucose positron emission tomography imaging can be used to assess response to chemotherapy in patients with relapsed germ cell tumours early in the course of treatment and may help to identify patients most likely to achieve a favourable response to subsequent high-dose chemotherapy. In patients with response to induction chemotherapy according to CT scans or serum tumour marker evaluation, positron emission tomography seems to add information to detect patients with an overall unfavourable outcome. It may also be a valuable addition to the prognostic model particularly in the good and intermediate group for further selection of patients who will profit from high-dose chemotherapy

Soil pH mediates the balance between stochastic and deterministic assembly of bacteria

Little is known about the factors affecting the relative influences of stochastic and deterministic processes that govern the assembly of microbial communities in successional soils. Here, we conducted a meta-analysis of bacterial communities using six different successional soil datasets distributed across different regions. Different relationships between pH and successional age across these datasets allowed us to separate the influences of successional age (i.e., time) from soil pH. We found that extreme acidic or alkaline pH conditions lead to assembly of phylogenetically more clustered bacterial communities through deterministic processes, whereas pH conditions close to neutral lead to phylogenetically less clustered bacterial communities with more stochasticity. We suggest that the influence of pH, rather than successional age, is the main driving force in producing trends in phylogenetic assembly of bacteria, and that pH also influences the relative balance of stochastic and deterministic processes along successional soils. Given that pH had a much stronger association with community assembly than did successional age, we evaluated whether the inferred influence of pH was maintained when studying globally distributed samples collected without regard for successional age. This dataset confirmed the strong influence of pH, suggesting that the influence of soil pH on community assembly processes occurs globally. Extreme pH conditions likely exert more stringent limits on survival and fitness, imposing strong selective pressures through ecological and evolutionary time. Taken together, these findings suggest that the degree to which stochastic vs. deterministic processes shape soil bacterial community assembly is a consequence of soil pH rather than successional age

Contribution of spatially explicit models to climate change adaptation and mitigation plans for a priority forest habitat

Climate change will impact forest ecosystems, their biodiversity and the livelihoods they sustain. Several adaptation and mitigation strategies to counteract climate change impacts have been proposed for these ecosystems. However, effective implementation of such strategies requires a clear understanding of how climate change will influence the future distribution of forest ecosystems. This study uses maximum entropy modelling (MaxEnt) to predict environmentally suitable areas for cork oak (Quercus suber) woodlands, a socio-economically important forest ecosystem protected by the European Union Habitats Directive. Specifically, we use two climate change scenarios to predict changes in environmental suitability across the entire geographical range of the cork oak and in areas where stands were recently established. Up to 40 % of current environmentally suitable areas for cork oak may be lost by 2070, mainly in northern Africa and southern Iberian Peninsula. Almost 90 % of new cork oak stands are predicted to lose suitability by the end of the century, but future plantations can take advantage of increasing suitability in northern Iberian Peninsula and France. The predicted impacts cross-country borders, showing that a multinational strategy, will be required for cork oak woodland adaptation to climate change. Such a strategy must be regionally adjusted, featuring the protection of refugia sites in southern areas and stimulating sustainable forest management in areas that will keep long-term suitability. Afforestation efforts should also be promoted but must consider environmental suitability and land competition issues

High-level classification of the Fungi and a tool for evolutionary ecological analyses

High-throughput sequencing studies generate vast amounts of taxonomic data. Evolutionary ecological hypotheses of the recovered taxa and Species Hypotheses are difficult to test due to problems with alignments and the lack of a phylogenetic backbone. We propose an updated phylum-and class-level fungal classification accounting for monophyly and divergence time so that the main taxonomic ranks are more informative. Based on phylogenies and divergence time estimates, we adopt phylum rank to Aphelidiomycota, Basidiobolomycota, Calcarisporiellomycota, Glomeromycota, Entomophthoromycota, Entorrhizomycota, Kickxellomycota, Monoblepharomycota, Mortierellomycota and Olpidiomycota. We accept nine subkingdoms to accommodate these 18 phyla. We consider the kingdom Nucleariae (phyla Nuclearida and Fonticulida) as a sister group to the Fungi. We also introduce a perl script and a newick-formatted classification backbone for assigning Species Hypotheses into a hierarchical taxonomic framework, using this or any other classification system. We provide an example of testing evolutionary ecological hypotheses based on a global soil fungal data set.Peer reviewe