Using summed individual species models and state-of-the-art modelling techniques to identify threatened plant species hotspots

Parviainen, Miia; Marmion, Mathieu; Luoto, Miska; Thuiller, Wilfried; Heikkinen, Risto K.

doi:10.1016/j.biocon.2009.05.030

Cited by 49 publications

(38 citation statements)

References 58 publications

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“…[83], [84]) or regional [85]–[87] scales. Such studies provide important insights and preservation of diversity concentrations, but it is increasingly argued that longer-term planning needs to take into account the impacts of climate change on the diversity hotspots [31] and species-based conservation activities [14].…”

Section: Discussionmentioning

confidence: 99%

Climate Change, Northern Birds of Conservation Concern and Matching the Hotspots of Habitat Suitability with the Reserve Network

et al. 2013

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National reserve networks are one of the most important means of species conservation, but their efficiency may be diminished due to the projected climatic changes. Using bioclimatic envelope models and spatial data on habitats and conservation areas, we studied how efficient the reserve network will be in preserving 100 forest, mire, marshland, and alpine bird species of conservation concern in Finland in 2051–2080 under three different climate scenarios. The occurrences of the studied bird species were related to the amount of habitat preferred by each species in the different boreal zones. We employed a novel integrated habitat suitability index that takes into account both the species’ probability of occurrence from the bioclimatic models and the availability of suitable habitat. Using this suitability index, the distribution of the topmost 5% suitability squares (“hotspots”) in the four bird species groups in the period 1971–2000 and under the three scenarios were compared with the location of reserves with the highest amounts of the four habitats to study the efficiency of the network. In species of mires, marshlands, and Arctic mountains, a high proportion of protected habitat was included in the 5% hotspots in the scenarios in 2051–2080, showing that protected areas cover a high proportion of occurrences of bird species. In contrast, in forests in the southern and middle boreal zones, only a small proportion of the protected habitat was included in the 5% hotspots, indicating that the efficiency of the protected area network will be insufficient for forest birds in the future. In the northern boreal zone, the efficiency of the reserve network in forests was highly dependent on the strength of climate change varying between the scenarios. Overall, there is no single solution to preserving biodiversity in a changing climate, but several future pathways should be considered.

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Section: Discussionmentioning

confidence: 99%

Climate Change, Northern Birds of Conservation Concern and Matching the Hotspots of Habitat Suitability with the Reserve Network

et al. 2013

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“…Empirical modelling of SR can be used to overcome this limitation, for example by identifying hotspots of SR (Gioia & Pigott, 2000;Lehmann et al, 2002;Luoto et al, 2004;Parviainen et al, 2009). However, information on SR is often incomplete, with large areas being devoid of such data.…”

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Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches

Dubuis

Pottier

Rion

et al. 2011

Diversity and Distributions

215

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Aim This study compares the direct, macroecological approach (MEM) for modelling species richness (SR) with the more recent approach of stacking predictions from individual species distributions (S‐SDM). We implemented both approaches on the same dataset and discuss their respective theoretical assumptions, strengths and drawbacks. We also tested how both approaches performed in reproducing observed patterns of SR along an elevational gradient. Location Two study areas in the Alps of Switzerland. Methods We implemented MEM by relating the species counts to environmental predictors with statistical models, assuming a Poisson distribution. S‐SDM was implemented by modelling each species distribution individually and then stacking the obtained prediction maps in three different ways – summing binary predictions, summing random draws of binomial trials and summing predicted probabilities – to obtain a final species count. Results The direct MEM approach yields nearly unbiased predictions centred around the observed mean values, but with a lower correlation between predictions and observations, than that achieved by the S‐SDM approaches. This method also cannot provide any information on species identity and, thus, community composition. It does, however, accurately reproduce the hump‐shaped pattern of SR observed along the elevational gradient. The S‐SDM approach summing binary maps can predict individual species and thus communities, but tends to overpredict SR. The two other S‐SDM approaches – the summed binomial trials based on predicted probabilities and summed predicted probabilities – do not overpredict richness, but they predict many competing end points of assembly or they lose the individual species predictions, respectively. Furthermore, all S‐SDM approaches fail to appropriately reproduce the observed hump‐shaped patterns of SR along the elevational gradient. Main conclusions Macroecological approach and S‐SDM have complementary strengths. We suggest that both could be used in combination to obtain better SR predictions by following the suggestion of constraining S‐SDM by MEM predictions.

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“…Thus, predictive models of single‐species geographical distributions and species richness provide an attractive alternative to using incomplete or spatially biased survey data as a basis for conservation planning (Parviainen et al. ).…”

Section: Introductionmentioning

confidence: 99%

Predicting vascular plant richness patterns in Catalonia (NE Spain) using species distribution models

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2012

Applied Vegetation Science

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Question Given the current state of knowledge on plant species richness in Catalonia, how can we improve definition of sampled species richness patterns? We propose a concrete methodology that will highlight the most speciose areas and those areas that are insufficiently sampled. Location Catalonia, covering 31 980 km2 in northeast Spain. Methods This study provides a quantitative assessment of plant richness using sampling units of 10 km × 10 km (n = 319). Generalized linear models (GLM), multivariate adaptive regression splines (MARS) and a maximum entropy model (Maxent) were used for all plant species contained in the Catalonia Database of Biodiversity (Banc de Dades de Biodiversitat de Catalunya, BDBC). The projected presence/absence maps were combined to create species richness maps based on distribution models for 2738 species. Results The modelling techniques were highly correlated, and we did not distinguish any differences in projections of geographic patterns of species richness among the modelling algorithms. However, MARS and Maxent achieved the best prediction success, whereas GLM tended to over‐predict species number per quadrat. The MARS map gave the highest predictive performance based on both Kappa and the true skill statistic, and for the two components of disagreement (quantity and allocation disagreement). We were able to identify one previously known region of high diversity, the Pyrenees, and two additional areas, the coastal range and the pre‐coastal mountain range. Conclusions We obtain improved distribution patterns for plant species in Catalonia over the previously sampled patterns, and, most importantly, we provide an estimate of the number of species present in those areas where sampling data are incomplete, with an expected 300 species. The model‐predicted richness maps presented here can be used to detect zones with low and high species richness and to develop strategies for either restoring or protecting landscape biodiversity as part of national conservation plans.

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Using summed individual species models and state-of-the-art modelling techniques to identify threatened plant species hotspots

Cited by 49 publications

References 58 publications

Climate Change, Northern Birds of Conservation Concern and Matching the Hotspots of Habitat Suitability with the Reserve Network

Climate Change, Northern Birds of Conservation Concern and Matching the Hotspots of Habitat Suitability with the Reserve Network

Predicting spatial patterns of plant species richness: a comparison of direct macroecological and species stacking modelling approaches

Predicting vascular plant richness patterns in Catalonia (NE Spain) using species distribution models

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