Towards a systematics of ecodiversity: The EcoSyst framework

Halvorsen, Rune; Skarpaas, Olav; Bryn, Anders; Bratli, Harald; Erikstad, Lars; Simensen, Trond; Lieungh, Eva

doi:10.1111/geb.13164

Cited by 53 publications

(96 citation statements)

References 104 publications

(167 reference statements)

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“…The practical solution chosen for the 'pilot Nordland project' was to aggregate minor types subjectively into types at a level between minor and major types. This procedure did, however, not comply with the standards of the EcoSyst framework (of which NiN version 2 shall be an implementation; Halvorsen et al 2020). Therefore, in order to construct a system of minor types at the landscape level that may be theoretically well founded and practically useful, the principle adopted at the ecosystem level in NiN version 2 of major type-independent local complex-gradient concepts was not adopted at the landscape level.…”

Section: Forward Selection Among Clg Candidates For a Set Of Orthogonal Clgsmentioning

confidence: 99%

“…In EcoSyst, the unit of compositional turnover of the key characteristic at an ecodiversity level along a complex variable in the key source of variation at this level, is termed the 'ecodiversity distance unit' (EDU; Halvorsen et al 2020). Adapted to the landscape level (landscape-element composition along a CLG), the unit is referred to as the ecodiversity distance unit in landscapes (EDU-L).…”

Section: Estimation Of Landscape Distancementioning

confidence: 99%

“…the compositional difference between OUs placed at the same point along the underlying CLG (INA; Whittaker 1952Whittaker , 1960Whittaker , Økland 1990, can be quantified. At the ecosystem level, the generalisation challenge is resolved by using generalised species-list data to calculate ecodiversity distance units in ecosystems (EDU-E; Halvorsen et al 2020). Such data contain 'smooth' ('noisefree') species abundance data for each candidate ecosystem type, derived from models of species' abundance distributions along local complex environmental gradients.…”

Section: Estimation Of Landscape Distancementioning

confidence: 99%

“…Total landscape-gradient length (LGL), on the corrected PD inequality scale, was calculated by summing up LD values for all intervals 12,23,34,45,56,67 and 78 into which the ONV was divided. Additionally, based on the same reasoning as for the ecosystem level (Halvorsen et al 2016(Halvorsen et al , 2020, we assume that the LEPs represent the centre of gravity in each interval (centre of the interval), i.e. that the underlying gradient extends beyond the centre of gravity of the intervals 1 and 8 by half the LD to the centres of gravity of the neighbouring segments.…”

Section: Estimation Of Landscape Distancementioning

confidence: 99%

“…We use, for the first time, a novel, gradient-based iterative procedure which involves calculation of 'ecodiversity distance', i.e., the extent to which the landscape element composition differs between adjacent candidate types. The current study was conducted as a part of the methodological development of the NiN framework (building on Halvorsen et al 2016), and has been part of the empirical basis for NiN and, subsequently, the theoretical framework of EcoSyst (Halvorsen et al 2020).…”

Section: Contents Introductionmentioning

confidence: 99%

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Gradient analysis of landscape variation in Norway

Simensen

Halvorsen

Erikstad

2020

Preprint

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SUMMARYA multitude of landscape characterisation and mapping methods exist, but few methods take into account that landscapes properties vary in a gradual, continuous manner along multiple directions of variation. In this study, we used gradient analytic methods, rooted in ecological continuum theory, to analyse landscape variation throughout Norway. The aim is to explain differences in landscape properties in the simplest possible way, by identifying ‘complex landscape gradients’ (CLGs), i.e. composite gradients of co-occurring landscape elements and properties.We collected data by stratified sampling of 100 test areas (20×20 km), in which we delineated a total of 3966 observation units (landscape polygons 4–30 km²) based on geomorphological criteria. For each observation unit, 85 landscape variables were recorded. We identified patterns of variation in landscape element composition by parallel use of two multivariate statistical methods, detrended correspondence analysis (DCA) and global nonmetric multidimensional scaling (GNMDS).The analyses revealed that the most important properties explaining differences in total landscape elements composition was location of the landscape relative to the coastline and coarse-scale landform variation. Most landscape elements had distinct optima within specific segments along broad-scale complex-gradients in landscape properties. A tentative landscape-type hierarchy was built by an iterative procedure by which the amount of compositional turnover in landscape-element composition between adjacent types was standardised. Six ‘major landscape types’ were identified based on geomorphological criteria. Within each major type, we identified a unique set of 2–5 important CLGs, representing geo-ecological, bio-ecological, and land use-related landscape variation. Minor landscape types were obtained by combining segments along two or more CLGs.The study shows that geological diversity, biological diversity and human land-use are tightly intertwined at the landscape level of ecological complexity, and that predominantly abiotic processes control and constrain both biotic processes and human land use.

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Section: Forward Selection Among Clg Candidates For a Set Of Orthogonal Clgsmentioning

confidence: 99%

Section: Estimation Of Landscape Distancementioning

confidence: 99%

Section: Estimation Of Landscape Distancementioning

confidence: 99%

Section: Estimation Of Landscape Distancementioning

confidence: 99%

Section: Contents Introductionmentioning

confidence: 99%

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Gradient analysis of landscape variation in Norway

Simensen

Halvorsen

Erikstad

2020

Preprint

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Use climatic space‐for‐time substitutions with care: Not only climate, but also local environment affect performance of the key forest species bilberry along elevation gradient

Auestad,

Rydgren,

Halvorsen

et al. 2023

Ecology and Evolution

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An urgent aim of ecology is to understand how key species relate to climatic and environmental variation, to better predict their prospects under future climate change. The abundant dwarf shrub bilberry (Vaccinium myrtillus L.) has caught particular interest due to its uphill expansion into alpine areas. Species' performance under changing climate has been widely studied using the climatic space‐for‐time approach along elevation gradients, but potentially confounding, local environmental variables that vary along elevation gradients have rarely been considered. In this study, performed in 10 sites along an elevation gradient (200–875 m) in W Norway, we recorded species composition and bilberry performance, both vegetative (ramet size and cover) and reproductive (berry and seed production) properties, over one to 4 years. We disentangled effects of local environmental variables and between‐year, climatic variation (precipitation and temperature), and identified shared and unique contributions of these variables by variation partitioning. We found bilberry ramet size, cover and berry production to peak at intermediate elevations, whereas seed production increased upwards. The peaks were less pronounced in extreme (dry or cold) summers than in normal summers. Local environmental variables explained much variation in ramet size and cover, less in berry production, and showed no relation to seed production. Climatic variables explained more of the variation in berry and seed production than in ramet size and cover, with temperature relating to vegetative performance, and precipitation to reproductive performance. Bilberry's clonal growth and effective reproduction probably explain why the species persists in the forest and at the same time invades alpine areas. Our findings raise concerns of the appropriateness of the climatic space‐for‐time approach. We recommend including both climatic and local environmental variables in studies of variation along elevation gradients and conclude that variation partitioning can be a useful supplement to other methods for analysing variation in plant performance.

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Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral‐ and three‐dimensional information from UAV‐based aerial imagery

Mienna

Klanderud

Ørka

et al. 2022

Remote Sens Ecol Conserv

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The alpine treeline ecotone is expected to move upwards in elevation with global warming. Thus, mapping treeline ecotones is crucial in monitoring potential changes. Previous remote sensing studies have focused on the usage of satellites and aircrafts for mapping the treeline ecotone. However, treeline ecotones can be highly heterogenous, and thus the use of imagery with higher spatial resolution should be investigated. We evaluate the potential of using unmanned aerial vehicles (UAVs) for the collection of ultra-high spatial resolution imagery for mapping treeline ecotone land covers. We acquired imagery and field reference data from 32 treeline ecotone sites along a 1100 km latitudinal gradient in Norway (60-69°N). Before classification, we performed a superpixel segmentation of the UAV-derived orthomosaics and assigned land cover classes to segments: rock, water, snow, shadow, wetland, tree-covered area and five classes within the ridge-snowbed gradient. We calculated features providing spectral, textural, three-dimensional vegetation structure, topographical and shape information for the classification. To evaluate the influence of acquisition time during the growing season and geographical variations, we performed four sets of classifications: global, seasonal-based, geographical regional-based and seasonalregional-based. We found no differences in overall accuracy (OA) between the different classifications, and the global model with observations irrespective of data acquisition timing and geographical region had an OA of 73%. When accounting for similarities between closely related classes along the ridgesnowbed gradient, the accuracy increased to 92.6%. We found spectral features related to visible, red-edge and near-infrared bands to be the most important to predict treeline ecotone land cover classes. Our results show that the use of UAVs is efficient in mapping treeline ecotones, and that data can be acquired irrespective of timing within a growing season and geographical region to get accurate land cover maps. This can overcome constraints of a short field-season or low-resolution remote sensing data.

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Towards a systematics of ecodiversity: The EcoSyst framework

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 53 publications

References 104 publications

Gradient analysis of landscape variation in Norway

Gradient analysis of landscape variation in Norway

Use climatic space‐for‐time substitutions with care: Not only climate, but also local environment affect performance of the key forest species bilberry along elevation gradient

Land cover classification of treeline ecotones along a 1100 km latitudinal transect using spectral‐ and three‐dimensional information from UAV‐based aerial imagery

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