Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2022
Authors
Philipp Lehmann Tea Ammunet Madeleine Barton Andrea Battisti Sanford D. Eigenbrode Jane Uhd Jepsen Gregor Kalinkat Seppo Neuvonen Pekka Niemelä John s. Terblanche Bjørn Økland Christer BjörkmanAbstract
Although it is well known that insects are sensitive to temperature, how they will be affected by ongoing global warming remains uncertain because these responses are multifaceted and ecologically complex. We reviewed the effects of climate warming on 31 globally important phytophagous insect pests to determine whether general trends in their responses to warming were detectable. We included four response categories (range expansion, life history, population dynamics, and trophic interactions) in this assessment (Figure 1). For the majority of these species, we identified at least one response to warming that affects the severity of the threat they pose as pests. Among these insect species, 41% showed responses expected to lead to increased pest damage, whereas only 4% exhibited responses consistent with reduced effects; notably, most of these species (55%) demonstrated mixed responses. This means that the severity of a given insect pest may both increase and decrease with ongoing climate warming. Overall, our analysis indicated that anticipating the effects of climate warming on phytophagous insect pests is far from straightforward. Rather, efforts to mitigate the undesirable effects of warming on insect pests must include a better understanding of how individual species will respond, and the complex ecological mechanisms underlying their responses. Although not the focus of our review, the main conclusions we reach also should hold true for biological control agents and there is indeed evidence for phenological mismatch and other climate-change-related effects on biological control of varying magnitude among systems. At least some natural control agents seem to respond more positively to climate warming than their herbivore prey, and as such, one might expect better biological control in certain systems. One potential reason for these differences is that while both control agents and herbivores are affected physiologically by changing climate drivers, by for instance increasing development rate, the control agents in addition are affected behaviourally and, for instance, can increase foraging or searching rate. In addition, and specifically in relation to biological control, it is often crucial to achieve high synchronization between control agent and prey, which can be complicated by different response rates to winter temperature. This is something that has been observed with the chestnut gall wasp Dryocosmus kuriphilus (Hymenoptera: Cynipidae) and its parasitoid Proceedings of ISBCA 6 – D.C. Weber, T.D. Gariepy, and W.R. Morrison III, eds. (2022) page 3.19 Torymus sinensis (Hymenoptera: Torymidae) over the last years, as the gall wasp depends largely on the budbreak of the host plant while the parasitoid relies mainly on the air temperature for spring emergence. Figure 1. Four major categories of responses to climate warming. (a) Range changes include range expansions or shifts (latitudinal and/or altitudinal). (b) Life-history changes primarily consist of alterations to biological timing events or the number of annual generations. (c) Population dynamics reflect population size, and damage is expected to increase whenever temperature limits performance, but if threshold temperatures are reached, control and related feedback mechanisms may be triggered. Tpresent reflects current temperatures over a time period (e.g., a year or a day), whereas Tfuture reflects future temperatures over the same period. (d) Trophic interactions reflect temperature responses of organisms and trophic groups (plants = dashed green line, herbivores = solid red line, predators = dashed blue line). Because vital rates (i.e. rates of important life-history traits, such as growth, dispersal, and reproduction) may vary, climate warming could strongly affect trophic relationships. This is of direct consequence for the planning and efficiency of biological control programs.
Authors
Bjørn Arild Hatteland May Bente Brurberg Rosemarie Tedeschi Wolfgang Jarausch Barbara Jarausch Dag-Ragnar BlystadAbstract
No abstract has been registered
Authors
Bjørn Arild Hatteland Sandra Kaasen Vestheim Jørund Johansen Silje Maria Midthjell Høydal Stein Joar Hegland Joseph Chipperfield Markus A. K. Sydenham Anders NielsenAbstract
No abstract has been registered
Abstract
Weeds may reduce crop yields significantly if managed improperly. However, excessive herbicide use increases risk of unwanted effects on ecosystems, humans and herbicide resistance development. Weed harrowing is a traditional method to manage weeds mechanically in organic cereals but could also be used in conventional production. The weed control efficacy of weed harrowing can be adjusted by e.g. the angle of the tines. Due to its broadcast nature (both crop and weed plants are disturbed), weed harrowing may have relatively poor selectivity (i.e. small ratio between weed control and crop injury). To improve selectivity, a sensor-based model which takes into account the intra-field variation in weediness and “soil density” in the upper soil layer (draft force of tines), is proposed. The suggested model is a non-linear regression model with three parameters and was based on five field trials in spring barley in SE Norway. The model predicts the optimal weed harrowing intensity (in terms of the tine angle) from the estimated total weed cover and SD per sub-field management unit, as well as a pre-set biological weed threshold (defined as the acceptable total weed cover left untreated). Weed cover and SD were estimated with RGB images (analysed with custom-made machine vision) and an electronic load cell, respectively. With current parameter values, the model should be valid for precision weed harrowing in spring barley in SE Norway. The next step is to test the model, and if successful, adjust it to more cereal species. Weeds may reduce crop yields significantly if managed improperly. However, excessive herbicide use increases risk of unwanted effects on ecosystems, humans and herbicide resistance development. Weed harrowing is a traditional method to manage weeds mechanically in organic cereals but could also be used in conventional production. The weed control efficacy of weed harrowing can be adjusted by e.g. the angle of the tines. Due to its broadcast nature (both crop and weed plants are disturbed), weed harrowing may have relatively poor selectivity (i.e. small ratio between weed control and crop injury). To improve selectivity, a sensor-based model which takes into account the intra-field variation in weediness and “soil density” in the upper soil layer (draft force of tines), is proposed. The suggested model is a non-linear regression model with three parameters and was based on five field trials in spring barley in SE Norway. The model predicts the optimal weed harrowing intensity (in terms of the tine angle) from the estimated total weed cover and SD per sub-field management unit, as well as a pre-set biological weed threshold (defined as the acceptable total weed cover left untreated). Weed cover and SD were estimated with RGB images (analysed with custom-made machine vision) and an electronic load cell, respectively. With current parameter values, the model should be valid for precision weed harrowing in spring barley in SE Norway. The next step is to test the model, and if successful, adjust it to more cereal species.
Abstract
Precision weeding or site-specific weed management (SSWM) take into account the spatial distribution of weeds within fields to avoid unnecessary herbicide use or intensive soil disturbance (and hence energy consumption). The objective of this study was to evaluate a novel machine vision algorithm, called the ‘AI algorithm’ (referring to Artificial Intelligence), intended for post-emergence SSWM in cereals. Our conclusion is that the AI algorithm should be suitable for patch spraying with selective herbicides in small-grain cereals at early growth stages (about two leaves to early tillering). If the intended use is precision weed harrowing, in which also post-harrow images can be used to control the weed harrow intensity, the AI algorithm should be improved by including such images in the training data. Another future goal is to make the algorithm able to distinguish weed species of special interest, for example cleavers (Galium aparine L.).
Abstract
No abstract has been registered
Abstract
No abstract has been registered
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No abstract has been registered
Abstract
Invasive species are leading causes of biodiversity loss and economic damage. Prevention and management of invasions requires risk assessments based on ecological knowledge for species of potential concern. Interactions between introduced species and heterospecifics in the recipient community may affect the likelihood of establishment through biotic resistance and facilitation and are therefore important predictors of invasion risk. Experimentally exposing one species to another to observe their interactions is not always safe or practical, and containment facilities offer artificial environments which may limit the number of species and the types of interactions that may be tested. To predict biotic resistance and facilitation in a more natural setting, we deployed traps with pheromone lures in the field to mimic the presence of two potentially invasive spruce bark beetles, the European Ips typographus (tested in eastern Canada), and the North American Dendroctonus rufipennis (tested in Norway). We identified and counted possible predators, competitors, and facilitators that were captured in the traps. In eastern Canada, possible predators and competitors responded strongly to I. typographus lures, suggesting the potential for considerable biotic resistance. In Norway, D. rufipennis lures prompted little response by predators or competitors, suggesting that D. rufipennis may experience reduced biotic resistance in Europe. Dendroctonus rufipennis was also attracted to I. typographus pheromone, which may encourage facilitation between these species through cooperative mass attack on trees. Our findings will inform invasive-species risk assessments for I. typographus and D. rufipennis and highlight useful methods for predicting interactions between species that rely heavily on semiochemical communication.
Abstract
The estimated global production of raspberry from year 2016 to 2020 averaged 846,515 tons. The most common cultivated Rubus spp. is European red raspberry (Rubus idaeus L. subsp. idaeus). Often cultivated for its high nutritional value, the red raspberry (Rubus idaeus) is susceptible to multiple viruses that lead to yield loss. These viruses are transmitted through different mechanisms, of which one is invertebrate vectors. Aphids and nematodes are known to be vectors of specific raspberry viruses. However, there are still other potential raspberry virus vectors that are not well-studied. This review aimed to provide an overview of studies related to this topic. All the known invertebrates feeding on raspberry were summarized. Eight species of aphids and seven species of plant-parasitic nematodes were the only proven raspberry virus vectors. In addition, the eriophyid mite, Phyllocoptes gracilis, has been suggested as the natural vector of raspberry leaf blotch virus based on the current available evidence. Interactions between vector and non-vector herbivore may promote the spread of raspberry viruses. As a conclusion, there are still multiple aspects of this topic that require further studies to get a better understanding of the interactions among the viral pathogens, invertebrate vectors, and non-vectors in the raspberry agroecosystem. Eventually, this will assist in development of better pest management strategies.