Spatial Analysis of Landscapes: Concepts and Statistics

Wagner, Helene H.; Fortin, Marie‐Josée

doi:10.1890/04-0914

Cited by 378 publications

(298 citation statements)

References 79 publications

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“…We also tested a sigmoidal model for both annuals and perennials, which showed a similar pattern and Akaike information criterion value as the linear GLS models. However, we considered linear GLS models as the most appropriate models given the temporal autocorrelation between observations and the spatio-temporal scale at which species dispersal was likely to occur (Wagner and Fortin 2005).…”

Section: Discussionmentioning

confidence: 99%

Annual monitoring reveals rapid upward movement of exotic plants in a montane ecosystem

2015

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There is increasing evidence that invasive species are threating montane ecosystems globally.However, trends in species distribution are difficult to observe directly due to a lack of data with suitable spatio-temporal resolution. Here, we aimed to detect spatio-temporal trends in exotic 1 Kalwij, J.M. et al.plants in a montane ecosystem, and to determine which drivers had a role affecting these trends.Each year, for a period of seven years, we recorded the upper elevational range limit of exotic plant species in road verges along an elevational gradient of 1,500-2,874 m a.s.l. in southern Africa. We fitted repeated-measures ANOVA models to test if upper elevational range limits changed over time. Generalized least squares models showed that exotic richness of annuals increased by 3.9 species per year. Also, the upper elevational range limits of established exotics ascended by 24.5 m/y for annuals (N = 17 species), and by 9.7 m/y for perennials (N = 26).These upward trends were too rapid to be explained by slow-acting drivers such as climatic

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Section: Discussionmentioning

confidence: 99%

Annual monitoring reveals rapid upward movement of exotic plants in a montane ecosystem

2015

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“…Environmental factors are often spatially autocorrelated, and hence it is inherently difficult to separate the effects of space and environment or determine which processes are causing spatial clustering (Wagner and Fortin, 2005;Currie, 2007). For example, methods that rely on clustering of survey data to incorporate spatial context into models are not determining the causal factors that caused those presences to be clustered in the first place.…”

Section: The Advantages and Disadvantages Of Neighbourhood Averagesmentioning

confidence: 99%

A simple post-hoc method to add spatial context to predictive species distribution models

Ashcroft

French

Chisholm

2012

Ecological Modelling

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Methods to incorporate spatial context into species distribution models (SDMs) are underutilised, with predictions usually based only on environmental space and ignoring geographic space. The goals of this study were to demonstrate a relatively simple post-hoc method to include spatial context in SDMs and to quantify the improvement over purely niche-based models. The method involved producing a standard niche-based model using established techniques, such as Maxent, and then calculating the neighbourhood average of the model output in geographic space. In effect, we tested whether the spatially averaged model output was better at predicting species distributions than the raw model output. We demonstrated the method using 32 tree species on the Illawarra Escarpment and found the area under the receiver operating characteristic curve (AUC) increased by a mean of 0.021 using this method. The improvements were largest for eucalypts, which have poor dispersal ability and clustered distributions. Improvements were smaller for moist rainforest species, which were restricted to small areas with sufficient shelter from hot, dry northwesterly winds. We conclude that it is relatively easy to add spatial context into species distribution models using this post-hoc method, and the resulting models are better for predicting species' distributions. AbstractMethods to incorporate spatial context into species distribution models (SDMs) are underutilised, with predictions usually based only on environmental space and ignoring geographic space. The goals of this study were to demonstrate a relatively simple post-hoc method to include spatial context in SDMs and to quantify the improvement over purely niche-based models. The method involved producing a standard niche-based model using established techniques, such as Maxent, and then calculating the neighbourhood average of the model output in geographic space. In effect, we tested whether the spatially averaged model output was better at predicting species distributions than the raw model output. We demonstrated the method using 32 tree species on the Illawarra Escarpment and found the area under the receiver operating characteristic curve (AUC) increased by a mean of 0.021 using this method. The improvements were largest for eucalypts, which have poor dispersal ability and clustered distributions. Improvements were smaller for moist rainforest species, which were restricted to small areas with sufficient shelter from hot, dry northwesterly winds. We conclude that it is relatively easy to add spatial context into species distribution models using this post-hoc method, and the resulting models are better for predicting species' distributions.

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“…Turner et al, 2001;Wagner and Fortin, 2005). The first relates to island-biogeography (MacArthur and Wilson, 1967) and metapopulation theory (Hanski and Gilpin, 1997), the second to niche theory (Hutchinson, 1957) and community ecology (e.g.…”

Section: Interplay Between Ecology and Hydrologymentioning

confidence: 99%

Pattern, process, and function in landscape ecology and catchment hydrology – how can quantitative landscape ecology support predictions in ungauged basins?

Schröder

2006

Hydrol. Earth Syst. Sci.

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Abstract. The understanding of landscape controls on the natural variability of hydrologic processes is an important research question of the PUB (Predictions in Ungauged Basins) initiative. Quantitative landscape ecology, which aims at understanding the relationships of patterns and processes in dynamic heterogeneous landscapes, may greatly contribute to this research effort by assisting the coupling of ecological and hydrological models.The present paper reviews the currently emerging rapprochement between ecological and hydrological research. It points out some common concepts and future research needs in both areas in terms of pattern, process and function analysis and modelling. Focusing on riverine as well as semi-arid landscapes, the interrelations between ecological and hydrological processes are illustrated. Three complementary examples show how both disciplines can provide valuable information for each other. I close with some visions about promising (landscape) ecological concepts that may help advancing one of the most challenging tasks in catchment hydrology: Predictions in ungauged basins.

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Spatial Analysis of Landscapes: Concepts and Statistics

Cited by 378 publications

References 79 publications

Annual monitoring reveals rapid upward movement of exotic plants in a montane ecosystem

Annual monitoring reveals rapid upward movement of exotic plants in a montane ecosystem

A simple post-hoc method to add spatial context to predictive species distribution models

Pattern, process, and function in landscape ecology and catchment hydrology – how can quantitative landscape ecology support predictions in ungauged basins?

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