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Berlin Brandenburg

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  • 1
    Language: English
    In: African Invertebrates, Dec 2011, Vol.52(2), pp.1-14
    Description: The Arge mirabilipes group of the Afrotropical Region is revised. The previously known species Arge mirabilipes Pasteels, 1955, A. tibialis Pasteels, 1963 and A. intermedia Pasteels, 1963 from South Africa, are redescribed. Two additional species from Namibia and Kenya are described: Arge kungveldensis sp. n. and A. taitaensis sp. n. The species of this group are characterized by the medially slightly widened hind tibia, a very short hind basitarsomere, and the sawsheath is broadly and obtusely pincer-shaped apically. According to these characters, Arge tibialis (= A. bisignata Konow, 1907) and A. intermedia are removed from this group. A. tibialis is synonymised under A. bisignata. A key to the three valid species is provided. The genitalia of all species are illustrated, and geographic distribution and taxonomic relationships are discussed.
    Keywords: Hymenoptera ; Symphyta ; Argidae ; Arginae ; Arge ; Sawflies ; New Species ; Afrotropical Region ; Namibia ; Kenya ; South Africa
    ISSN: 16815556
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  • 2
    In: Forest Science, October 2014, Vol.60(5), pp.851-861
    Description: The analysis of phylogenetic relationships among co-occurring tree species offers insights into the ecological organization of forest communities from an evolutionary perspective and, when employed regionally across thousands of plots, can assist in forest health assessment. Phylogenetic clustering of species, when species are more closely related than expected by chance, suggests a process of evolutionary niche conservatism. Because such communities share much evolutionary history and an affinity for similar environmental conditions, they may be particularly susceptible to threats such as insects and diseases and shifting climate conditions. Meanwhile, a pattern of phylogenetic evenness, in which the species are less closely related than by chance, may indicate competitive exclusion or interspecies facilitation. The ecological integrity of such communities may be less at risk because they may encompass a wider variety of evolutionary adaptations. Using a network of more than 100,000 forest inventory plots across the conterminous United States, we tested whether community phylogenetic structure was significantly clustered or even at multiple scales. Clustering predominated across most of the study area, indicating the widespread significance of evolutionary niche conservatism, except in areas of the west. Phylogenetic structure varied along environmental gradients, suggesting that clustering predominates in more favorable locations and evenness predominates in areas with harsher environments. These results have implications for broad-scale forest health monitoring.
    Keywords: Forest Community
    ISSN: 0309-0566
    ISSN: 0015749X
    E-ISSN: 19383738
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  • 3
    Language: English
    In: Palaeogeography, Palaeoclimatology, Palaeoecology, 2011, Vol.308(3), pp.362-372
    Description: Recent studies suggest a marked expansion of glacial ice across much of Gondwana beginning in the earliest Permian. Because expansion of glacial ice results in a lowering of sea level, the imprint of ice expansion should be evident worldwide as significant exposure event, hiatuses, or other evidence for sea level drop at or near the Pennsylvanian–Permian boundary. This literature review investigates the signature of an Early Permian expansion of Gondwanan ice through examination of stratigraphic records from eight carbonate-dominated, palaeotropical regions across Pangaea. Tropical carbonate environments are used because most form in tectonically quiescent regions and are sensitive indicators of eustatic change. Correlation between stratigraphic sections is achieved using the most current biostratigraphic and absolute time constraints available. All studied sections show a sequence boundary or basinward shift in facies at or near the Pennsylvanian–Permian boundary, supporting the hypothesis of a significant expansion of glacial ice and global eustatic lowstand beginning in the Early Permian. By contrast, a series of mid-Sakmarian–Kungurian transgression events in the palaeotropics are interpreted to reflect the asynchronous deglaciation of Gondwana. The stratigraphic framework developed herein will allow for better correlations among stratigraphic records from Gondwana and northern Pangaea, which will ultimately improve the understanding of how carbonate systems respond to global icehouse conditions, such as during the late Palaeozoic. ► We examine global stratigraphic data from the late Palaeozoic. ► Data suggests a sequence boundary at the Pennsylvanian–Permian boundary. ► Our data suggests an expansion of glacial ice beginning in the Early Permian.
    Keywords: Pennsylvanian ; Permian ; Carbonates ; Eustasy ; Late Palaeozoic ; Geology
    ISSN: 0031-0182
    E-ISSN: 1872-616X
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  • 4
    Language: English
    In: Forest Ecology and Management, 01 February 2011, Vol.261(3), pp.473-479
    Description: ▶ An outbreak in the previous year is the strongest predictor of SPB infestation. ▶ Climate variables are more important than landscape variables. ▶ Extreme temperature and precipitation increase infestation likelihood. ▶ Driving factors for individual infestations operate below the county level. The southern pine beetle ( , SPB) is the major insect pest of pine species in the southeastern United States. It attains outbreak population levels sufficient to mass attack host pines across the landscape at scales ranging from a single forest stand to interstate epidemics. This county level analysis selected and examined the best climatic and landscape variables for predicting infestations at regional scales. The analysis showed that, for a given county, the most important factor in predicting outbreaks was that the county was classified as in outbreak status in the previous year. Other important factors included minimum winter temperature and the greatest difference between the average of daily minimums and a subsequent low temperature point, precipitation history either seasonally in the previous year or difference from average over the previous 2 years, the synchronizing effect of seasonal temperatures on beetle populations and the relative percentage of total forest area composed of host species. The statistical models showed that climatic variables are stronger indicators of outbreak likelihood than landscape structure and cover variables. Average climatic conditions were more likely to lead to outbreaks than extreme conditions, supporting the notion of coupling between a native insect and its native host. Still, some extreme events (i.e., periods of very low temperature or very high precipitation) did precede beetle infestation. This analysis suggested that there are predisposing and inciting factors at the large scale but the driving factors leading to individual infestations operate at smaller scales.
    Keywords: Classification and Regression Tree ; Insect Infestation ; Logistic Regression ; Dendroctonus Frontalis ; Pinus Taeda ; Forestry ; Biology
    ISSN: 0378-1127
    E-ISSN: 1872-7042
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  • 5
    Language: English
    In: Journal of Environmental Management, Nov 15, 2013, Vol.129, p.173(10)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jenvman.2013.07.013 Byline: Denys Yemshanov, Frank H. Koch, Mark J. Ducey, Marty Siltanen, Kirsty Wilson, Klaus Koehler Abstract: Long-distance introductions of alien species are often driven by socioeconomic factors, such that conventional "biological" invasion models may not be capable of estimating spread fully and reliably. In this study, we demonstrate a new technique for assessing and reconstructing human-mediated pathways of alien forest species entries to major settlements in Canada via commercial road transportation and domestic trade. We undertook our analysis in three steps. First, we used existing data on movement of commodities associated with bark- and wood-boring forest pests to build a probabilistic model of how the organisms may be moved from one location to another through a transportation network. We then used this model to generate multiple sets of predictions of species arrival rates at every location in the transportation network, and to identify the locations with the highest likelihood of new incursions. Finally, we evaluated the sensitivity of the species arrival rates to uncertainty in key model assumptions by testing the impact of additive and multiplicative errors (by respectively adding a uniform random variate or symmetric variation bounds to the arrival rate values) on the probabilities of pest transmission from one location to another, as well as the impact of the removal of one or more nodes and all connecting links to other nodes from the underlying transportation network. Overall, the identification of potential pest arrival hotspots is moderately robust to uncertainties in key modeling assumptions. Large urban areas and major border crossings that have the highest predicted species arrival rates have the lowest sensitivities to uncertainty in the pest transmission potential and to random changes in the structure of the transportation network. The roadside survey data appears to be sufficient to delineate major hubs and hotspots where pests are likely to arrive from other locations in the network via commercial truck transport. However, "pass-through" locations with few incoming and outgoing routes can be identified with lower precision. The arrival rates of alien forest pests appear to be highly sensitive to additive errors. Surprisingly, the impact of random changes in the structure of the transportation network was relatively low. Author Affiliation: (a) Natural Resources Canada, Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen Street East, Sault Ste. Marie, ON P6A 2E5, Canada (b) USDA Forest Service, Southern Research Station, Eastern Forest Environmental Threat Assessment Center, 3041 Cornwallis Road, Research Triangle Park, NC 27709, USA (c) University of New Hampshire, Department of Natural Resources and the Environment, 114 James Hall, Durham, NH 03824, USA (d) Canadian Food Inspection Agency, 59 Camelot Drive, Ottawa, ON K1A 0Y9, Canada Article History: Received 10 September 2012; Revised 24 May 2013; Accepted 15 July 2013
    ISSN: 0301-4797
    Source: Cengage Learning, Inc.
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  • 6
    In: Risk Analysis, September 2013, Vol.33(9), pp.1694-1709
    Description: Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that typically require prior knowledge of the risk components’ importance. Such information is often nonexistent for many invasive pests. This study proposes a new approach for building integrated risk maps using the principle of a multiattribute efficient frontier and analyzing the partial order of elements of a risk map as distributed in multidimensional criteria space. The integrated risks are estimated as subsequent multiattribute frontiers in dimensions of individual risk criteria. We demonstrate the approach with the example of Fabricius, a high‐risk pest that may threaten North American oak forests in the near future. Drawing on U.S. and Canadian data, we compare the performance of the multiattribute ranking against a multicriteria linear weighted averaging technique in the presence of uncertainties, using the concept of robustness from info‐gap decision theory. The results show major geographic hotspots where the consideration of tradeoffs between multiple risk components changes integrated risk rankings. Both methods delineate similar geographical regions of high and low risks. Overall, aggregation based on a delineation of multiattribute efficient frontiers can be a useful tool to prioritize risks for anticipated invasive pests, which usually have an extremely poor prior knowledge base.
    Keywords: Agrilus Biguttatus ; Multiattribute Efficient Frontier ; Multicriteria Aggregation ; Nondominant Set ; Pest Risk Mapping ; Robustness To Uncertainty
    ISSN: 0272-4332
    E-ISSN: 1539-6924
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  • 7
    Language: English
    In: Forest Ecology and Management, 15 November 2016, Vol.380, pp.346-358
    Description: Efforts to monitor the broad-scale impacts of drought on forests often come up short. Drought is a direct stressor of forests as well as a driver of secondary disturbance agents, making a full accounting of drought impacts challenging. General impacts can be inferred from moisture deficits quantified using precipitation and temperature measurements. However, derived meteorological indices may not meaningfully capture drought impacts because drought responses can differ substantially among species, sites and regions. Meteorology-based approaches also require the characterization of current moisture conditions relative to some specified time and place, but defining baseline conditions over large, ecologically diverse regions can be as difficult as quantifying the moisture deficit itself. In contrast, remote sensing approaches attempt to observe immediate, secondary, and longer-term changes in vegetation response, yet they too are no panacea. Remote sensing methods integrate responses across entire mixed-vegetation pixels and rarely distinguish the effects of drought on a single species, nor can they disentangle drought effects from those caused by various other disturbance agents. Establishment of suitable baselines from remote sensing may be even more challenging than with meteorological data. Here we review broad-scale drought monitoring methods, and suggest that an integrated data-mining approach may hold the most promise for enhancing our ability to resolve drought impacts on forests. A big-data approach that integrates meteorological and remotely sensed data streams, together with other datasets such as vegetation type, wildfire occurrence and pest activity, can clarify direct drought effects while filtering indirect drought effects and consequences. This strategy leverages the strengths of meteorology-based and remote sensing approaches with the aid of ancillary data, such that they complement each other and lead toward a better understanding of drought impacts.
    Keywords: Drought Impacts ; Forests ; Drought Indices ; Remote Sensing ; Big Data ; Monitoring ; Forestry ; Biology
    ISSN: 0378-1127
    E-ISSN: 1872-7042
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  • 8
    Language: English
    In: PLoS ONE, 01 January 2014, Vol.9(5), p.e96895
    Description: BACKGROUND: There is absence of specific biomarkers and an incomplete understanding of the pathophysiology of exudative age-related macular degeneration (AMD). METHODS AND FINDINGS: Eighty-eight vitreous samples (73 from patients with treatment naïve AMD and 15 control samples from patients with idiopathic floaters) were analyzed with capillary electrophoresis coupled to mass spectrometry in this retrospective case series to define potential candidate protein markers of AMD. Nineteen proteins were found to be upregulated in vitreous of AMD patients. Most of the proteins were plasma derived and involved in biological (ion) transport, acute phase inflammatory reaction, and blood coagulation. A number of proteins have not been previously associated to AMD including alpha-1-antitrypsin, fibrinogen alpha chain and prostaglandin H2-D isomerase. Alpha-1-antitrypsin was validated in vitreous of an independent set of AMD patients using Western blot analysis. Further systems biology analysis of the data indicated that the observed proteomic changes may reflect upregulation of immune response and complement activity. CONCLUSIONS: Proteome analysis of vitreous samples from patients with AMD, which underwent an intravitreal combination therapy including a core vitrectomy, steroids and bevacizumab, revealed apparent AMD-specific proteomic changes. The identified AMD-associated proteins provide some insight into the pathophysiological changes associated with AMD.
    Keywords: Sciences (General)
    E-ISSN: 1932-6203
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  • 9
    Language: English
    In: Journal of Environmental Management, 2010, Vol.91(12), pp.2535-2546
    Description: Integrated pest risk maps and their underlying assessments provide broad guidance for establishing surveillance programs for invasive species, but they rarely account for knowledge gaps regarding the pest of interest or how these can be reduced. In this study we demonstrate how the somewhat competing notions of robustness to uncertainty and potential knowledge gains could be used in prioritizing large-scale surveillance activities. We illustrate this approach with the example of an invasive pest recently detected in North America, Fabricius. First, we formulate existing knowledge about the pest into a stochastic model and use the model to estimate the expected utility of surveillance efforts across the landscape. The expected utility accounts for the distribution, abundance and susceptibility of the host resource as well as the value of timely detections. Next, we make use of the info-gap decision theory framework to explore two alternative pest surveillance strategies. The first strategy aims for timely, certain detections and attempts to maximize the robustness to uncertainty about behavior; the second strategy aims to maximize the potential knowledge gain about the pest via unanticipated (i.e., opportune) detections. The results include a set of spatial outputs for each strategy that can be used independently to prioritize surveillance efforts. However, we demonstrate an alternative approach in which these outputs are combined via the Pareto ranking technique into a single priority map that outlines the survey regions with the best trade-offs between both surveillance strategies.
    Keywords: Info-Gap ; Sirex Noctilio ; Robustness ; Opportuneness ; Invasion Model ; Spatial Simulation ; Pareto Frontier ; Multi-Criteria Ranking ; Environmental Sciences ; Economics
    ISSN: 0301-4797
    E-ISSN: 1095-8630
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  • 10
    Language: English
    In: Risk analysis, 2010, Vol.30(2), pp.261-276
    Description: In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk-ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest. ; Includes references ; p. 261-276.
    Keywords: Sirex Noctilio ; Survey Network ; Robustness To Uncertainty ; Info-Gap ; Decision Theory
    ISSN: 0272-4332
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