Bioclimatic and vegetation mapping of a topographically complex oceanic island applying different interpolation techniques

Garzón-Machado, Víctor; Otto, Rüdiger; Aguilar, Marcelino J. del Arco

doi:10.1007/s00484-013-0670-y

Cited by 29 publications

(42 citation statements)

References 41 publications

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“…To account for topographic complexity we calculated mean values, ranges and standard deviations of the 1600 pixels within each 1 × 1 km cell for elevation, aspect and slope. Climate data were sourced from meteorological stations operated by the State Agencia Española de Meteorología and interpolated using multiple linear regression analysis followed by spatial interpolation of the regression residuals for EH and LP (see Garzón‐Machado et al ., ) and, for TFE, using co‐kriging.…”

Section: Methodsmentioning

confidence: 99%

Transferring and implementing the general dynamic model of oceanic island biogeography at the scale of island fragments: the roles of geological age and topography in plant diversification in the Canaries

Otto

Whittaker

Gaisberg³

et al. 2016

Journal of Biogeography

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Aim The general dynamic model (GDM) of oceanic island biogeography integrates rates of immigration, speciation and extinction in relation to a humped trajectory of island area, species carrying capacity and topographic complexity through time, based on a simplified island ontogeny. In practice, many islands have more complex ontogenies, featuring surfaces of varying age. Here, we extend the GDM to apply at a local scale within islands, and test the predictions analytically within individual islands. Location El Hierro, La Palma and Tenerife (Canary Islands).Methods Following the GDM logic, we derive predictions for the distributions and richness of single island endemics (SIEs) across island landscapes of different age. We test these predictions by means of generalized linear models and binominal tests using gridded species occurrence data for vascular plant SIE species and a set of climatic, topographic and terrain age variables. We also examined phylogenetic divergence times for a subset of endemic lineages.Results Geological age, in interaction with slope, and topographic variables, best explained SIE richness at the landscape scale. About 70% of SIEs had ranges strongly biased to, or largely restricted to old terrain. Available phylogenetic divergence times of SIEs of radiated plant lineages suggested an origin on the older parts of the islands. Metrics of anthropogenic disturbance and habitat availability were unrelated to the observed SIE pattern.Main conclusions Our findings support the hypothesis that SIEs have evolved and accumulated on older and topographically complex terrain, while colonization processes predominate on the youngest parts. These results imply that evolutionary processes shape species distributions at the landscape scale within islands. This opens the perspective of extending the GDM framework to understand processes at a local scale within individual islands.

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Section: Methodsmentioning

confidence: 99%

Transferring and implementing the general dynamic model of oceanic island biogeography at the scale of island fragments: the roles of geological age and topography in plant diversification in the Canaries

Otto

Whittaker

Gaisberg³

et al. 2016

Journal of Biogeography

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“…The DEM is based on remotely sensed images from the Shuttle Radar Topography Mission (SRTM, 30 arc-seconds resolution) created and released by the U.S. Geological Survey (USGS) and the National Geospatial-Intelligence Agency (NGA) (Danielson and Gesch, 2011). Due to its desirable properties, cokriging is frequently used to interpolate climate variables and indices (e.g., Aznar et al, 2013; Garzon-Machado et al, 2014). We compared our cokriging results with a gridded layer of the ETCCDI climate change indices of coarse resolution available through the HadEX2 data set (Donat et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

Amplification or suppression: Social networks and the climate change—migration association in rural Mexico

Nawrotzki

Riosmena

Hunter

et al. 2015

Global Environmental Change

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Increasing rates of climate migration may be of economic and national concern to sending and destination countries. It has been argued that social networks – the ties connecting an origin and destination – may operate as “migration corridors” with the potential to strongly facilitate climate change-related migration. This study investigates whether social networks at the household and community levels amplify or suppress the impact of climate change on international migration from rural Mexico. A novel set of 15 climate change indices was generated based on daily temperature and precipitation data for 214 weather stations across Mexico. Employing geostatistical interpolation techniques, the climate change values were linked to 68 rural municipalities for which sociodemographic data and detailed migration histories were available from the Mexican Migration Project. Multi-level discrete-time event-history models were used to investigate the effect of climate change on international migration between 1986 and 1999. At the household level, the effect of social networks was approximated by comparing the first to the last move, assuming that through the first move a household establishes internal social capital. At the community level, the impact of social capital was explored through interactions with a measure of the proportion of adults with migration experience. The results show that rather than amplifying, social capital may suppress the sensitivity of migration to climate triggers, suggesting that social networks could facilitate climate change adaptation in place.

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“…The mild subtropical Atlantic climate of the island is strongly modified by the complex topography (Garzón-Machado, Otto, & del Arco Aguilar, 2014). With high constancy, trade wind conditions transport moisture from the north-east.…”

Section: Study Areamentioning

confidence: 99%

An island view of endemic rarity—Environmental drivers and consequences for nature conservation

Irl

Schweiger

Medina

et al. 2017

Diversity and Distributions

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Aim: Rarity-an important measure for conservation biogeography-can vary over many orders of magnitude. However, it is unclear which regional-scale abiotic conditions drive processes affecting rarity of endemic species on islands. To support conservation efforts, we (1) assess the main abiotic drivers of endemic rarity, (2) determine how well existing protected areas (PAs) coincide with hotspots of endemic rarity and (3) introduce and evaluate a new hypervolume-based rarity estimator. Location: La Palma (Canary Islands). Methods:We recorded all present endemic vascular plant species in 1,212 plots covering the entire island. We calculated endemic rarity (corrected range-rarity richness for endemics) using a rarity estimation approach based on kernel density estimations (hypervolume approach). We performed a sensitivity analysis based on multiple linear regressions and relative importance estimations of environmental drivers to estimate the performance of the hypervolume-based rarity estimation compared to standard methods (occurrence frequency, convex hulls, alpha hulls).Results: Climate variables (mean annual temperature, climatic rarity, precipitation variability) best explained archipelago endemic (AE) and single-island endemic (SIE) rarity.Existing PAs covered the majority of AE and SIE rarity, especially national and natural parks as well as the Natura 2000 sites. In our study system, hypervolumes performed better than standard measures of range size.Main conclusion: Both AE and SIE rarity on La Palma show a clear spatial pattern, with hotspots of endemic rarity found at high elevations and in rare climates, presumably owing to geographical and climatic constraints and possibly anthropogenic pressure (e.g., land use, introduced herbivores, fire). Areas of high rarity estimates coincide with the distribution and extent of PAs on La Palma, especially since the recent addition of the Natura 2000 sites. The hypervolume approach is a promising tool to estimate species range sizes, and can be applied on all scales where point/plot data are available.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.

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Bioclimatic and vegetation mapping of a topographically complex oceanic island applying different interpolation techniques

Cited by 29 publications

References 41 publications

Transferring and implementing the general dynamic model of oceanic island biogeography at the scale of island fragments: the roles of geological age and topography in plant diversification in the Canaries

Transferring and implementing the general dynamic model of oceanic island biogeography at the scale of island fragments: the roles of geological age and topography in plant diversification in the Canaries

Amplification or suppression: Social networks and the climate change—migration association in rural Mexico

An island view of endemic rarity—Environmental drivers and consequences for nature conservation

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