Terrestrial trophic dynamics in the Canadian Arctic

Krebs, Charles J.; Danell, Kjell; Angerbjörn, Anders; Agrell, Jep; Berteaux, Dominique; Bråthen, Kari Anne; Danell, Öje; Erlinge, Sam; Fedorov, Vadim B.; Fredga, Karl; Hjältén, Joakim; Högstedt, Göran; Jónsdóttir, Ingibjörg S.; Kenney, Alice J.; Kjellén, Nils; Nordin, Torgny; Roininen, Heikki; Svensson, Mikael; Tannerfeldt, Magnus; Wiklund, Christer

doi:10.1139/z03-061

Cited by 71 publications

(74 citation statements)

References 42 publications

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“…) is fundamental to an arctic tundra ecosystem's functions and services, such as food for wildlife and feedback to climate [1]- [3]. Arctic temperatures have increased at almost twice the global average rate in the past 100 years and are predicted to continue at a higher rate than the rest of the planet [4] [5].…”

Section: Introductionmentioning

confidence: 99%

Decoupling between Plant Productivity and Growing Season Length under a Warming Climate in Canada’s Arctic

Zorn¹,

White²,

Olthof³

et al. 2016

AJCC

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Given the short duration of growing season in the Arctic, a strong correlation between plant productivity and growing season length (GSL) is conventionally assumed. Will this assumption hold true under a warming climate? In this study, we addressed the question by investigating the relationship between net primary productivity of leaves (NPPleaf) and GSL for various tundra ecosystems. We quantified NPPleaf and GSL using long-term satellite data and field measurements. Our results indicated that the relationship was not significant (i.e., decoupled) for 44% to 64% of tundra classes in the southern Canadian Arctic, but significant for all classes in the northern Canadian Arctic. To better understand the causes of the decoupling, we further decomposed the relationship into two components: the correspondence of interannual variations and the agreement of longterm trends. We found that the longer the mean GSL for a tundra class, the poorer the correspondence between their interannual variations. Soil moisture limitation further decoupled the relationship by deteriorating the agreement of long-term trends. Consequently, the decoupling between NPPleaf and GSL would be more likely to occur under a warming climate if the tundra class had a mean GSL > 116 (or 123) days with a dry (or moist) soil moisture regime.

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Section: Introductionmentioning

confidence: 99%

Decoupling between Plant Productivity and Growing Season Length under a Warming Climate in Canada’s Arctic

Zorn¹,

White²,

Olthof³

et al. 2016

AJCC

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“…one of the most commonly observed and potentially most useful ecosystem variables for seasonal and longterm ground monitoring is percent plant cover (bliss et al, 1984;Kennedy et al, 2001;Krebs et al, 2003;bonham and Clark, 2005;Chen et al, 2009b). As shown by Chen et al (2009b), other key ecosystem variables such as aboveground biomass, foliage biomass, and leaf area index (lAi) can be reliably measured in the Arctic using percent plant cover and mean height, not only at the plot-total level, but also at the levels of plant species or function groups.…”

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confidence: 99%

“…two methods are commonly used: visual estimate (ve) and point frame (PF) (bliss et al, 1984;Kennedy et al, 2001;Krebs et al, 2003;bean and henry 2003;bonham and Clark, 2005;Chen et al, 2009b). the ve method is quick and widely used.…”

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confidence: 99%

“…however, most such studies produced only general categories, such as vegetation and non-vegetation (laliberte et al, 2007). Since wildlife species usually differentiate between vegetation types in their diets (Krebs et al, 2003), categorizing percent plant cover at a more detailed level (e.g., by functional types or species groups, Chen et al, 2009b) (Definiens, 2003), several studies have measured percent cover for vegetation categories on digital photographs, with promising results (booth et al, 2005, 2006aluscier et al, 2006;laliberte et al, 2007;Booth and Cox, 2008). However, classification error resulting from spectral separation methods (vegMeasure, erDAS imagine [erDAS, 2010], eCognition) can cause confusion among like-colored species.…”

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confidence: 99%

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Digital Photograph Analysis for Measuring Percent Plant Cover in the Arctic

Chen¹,

Chen²,

Leblanc³

et al. 2010

ARCTIC

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AbStrACt. long-term satellite remote sensing data, when properly calibrated and validated against ground monitoring, could provide valuable data sets for assessing climate change impacts on ecosystems, wildlife, and other important aspects of life in the Arctic. Percent plant cover is ideal for seasonal and long-term ground monitoring because it can be observed non-destructively and is closely related to other key ecosystem variables, such as biomass and leaf area index (lAi). Accurately measuring percent plant cover in the Arctic, however, has been a challenge. Advances in digital photography and imageprocessing techniques have provided the potential to measure vegetation cover accurately. in this paper we report an adapted method for quantifying percent plant cover based on plot digital photograph classification (PDPC). In this digital image analysis, the red, green, and blue image channels and the intensity, hue, and saturation image channels were used together to ensure more accurate cover measurement and labeling of plant species. We evaluated the accuracy of the PDPC method and two other techniques, visual estimate and digital grid overlay, by testing against artificial plots with known percent cover, by comparing with destructively measured lAi, and by comparing results of the three methods. our evaluation indicates that the PDPC method is the most accurate. In addition, PDPC has the advantages of being objective, quick in the field, and suitable for measuring percent plant cover in the Arctic at the level of functional types or species groups.Key words: percent plant cover, Arctic, visual estimate, digital photograph, image classification, LAI rÉSuMÉ. lorsqu'elles sont bien calibrées et qu'elles sont validées contre le dépistage terrestre, les données résultant de la télédétection satellitaire à long terme pourraient fournir d'importants ensembles de données en vue de l'évaluation des incidences du changement climatique sur les écosystèmes, la faune et d'autres aspects-clés de la vie dans l'Arctique. le pourcentage de couverture végétale est idéal pour le dépistage saisonnier et le dépistage terrestre à long terme parce qu'il peut être observé sans qu'il n'y ait de destruction et parce qu'il est étroitement lié à d'autres variables-clés se rapportant aux écosystèmes, comme la biomasse et l'indice de surface foliaire (iSF). toutefois, dans l'Arctique, la mesure exacte du pourcentage de couverture végétale représente un défi. Les progrès réalisés dans les domaines de la photographie numérique et des techniques de traitement d'images fournissent la possibilité de mesurer la couverture végétale avec précision. Dans cette communication, nous faisons état d'une méthode adaptée permettant de quantifier le pourcentage de couverture végétale en fonction de la classification de photographies numériques de parcelles. Dans le cadre de l'analyse d'images numériques, les canaux rouges, verts et bleus des images ainsi que les canaux d'intensité, de tonalité et de saturation des images ont été utilisés pour donner lieu ...

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“…A second model (Ecosim) simulates changes in the initial balanced steady-state of the food web (the Ecopath model) with altered exploitation rates, species interactions, environmental changes, or a combination of factors. Ecopath and Ecosim models have been used to examine links among producers, consumers, and harvesters in marine, freshwater, and terrestrial ecosystems (.150 publications; e.g., Krebs et al 2003;Christensen and Walters 2004). Explicit details of the modeling approach are published elsewhere (Walters et al 1997;Christensen et al 2000;Kitchell et al 2000;Christensen and Walters 2004).…”

Section: Methodsmentioning

confidence: 99%

Modeling Management Scenarios and the Effects of an Introduced Apex Predator on a Coastal Riverine Fish Community

2007

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Abstract.-The flathead catfish Pylodictis olivaris, a carnivorous fish species native to most of the central interior basin of North America, has been introduced into at least 13 U.S. states and 1 Canadian province. Concurrent declines in abundance of native fishes have been reported in aquatic systems where flathead catfish have been introduced. To evaluate the potential impact of this invasive species on the native fish community we developed an ecosystem simulation model (including flathead catfish) based on empirical data collected from a North Carolina coastal river. The model results suggest that flathead catfish suppress native fish community biomass by 5-50% through both predatory and competitive interactions. However, our model suggests these reductions could be mitigated through sustained exploitation of flathead catfish by recreational or commercial fishers at rates equivalent to those for native flathead catfish populations (annual exploitation ¼ 6-25%). These findings demonstrate the potential for using directed harvest of an invasive species to assist in restoring native communities.

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Terrestrial trophic dynamics in the Canadian Arctic

Cited by 71 publications

References 42 publications

Decoupling between Plant Productivity and Growing Season Length under a Warming Climate in Canada’s Arctic

Decoupling between Plant Productivity and Growing Season Length under a Warming Climate in Canada’s Arctic

Digital Photograph Analysis for Measuring Percent Plant Cover in the Arctic

Modeling Management Scenarios and the Effects of an Introduced Apex Predator on a Coastal Riverine Fish Community

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