The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Slope, aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland
Open accessAbstract
Abstract The slope and aspect of a vegetated surface strongly affects the amount of solar radiation intercepted by that surface. Solar radiation is the dominant component of the surface energy balance and influences ecologically critical factors of microclimate, including near-surface temperatures, evaporative demand and soil moisture content. It also determines the exposure of vegetation to photosynthetically active and ultra-violet wavelengths. Spatial variation in slope and aspect is therefore a key determinant of vegetation pattern, species distribution and ecosystem processes in many environments. Slope and aspect angle may vary considerably over distances of a few metres, and fine-scale species’ distribution patterns frequently follow these topographic patterns. The availability of suitable microclimate at such scales may be critical for the response of species distributions to climatic change at much larger spatial scales. However, quantifying the relevant microclimatic gradients is not straightforward, as the potential variation in solar radiation flux under clear-sky conditions is modified by local and regional variations in cloud cover, and interacts with long-wave radiation exchange, local meteorology and surface characteristics. We tested simple models of near-surface temperature and potential evapotranspiration driven by meteorological data with the incoming solar radiation flux adjusted for topography against measurements of temperature and soil moisture at two chalk grassland field sites in contrasting regional climates of the United Kingdom. We then estimated the cumulative distribution function of three key ecological variables (monthly temperature sums above 5 and 30 °C, plus potential evapotranspiration) across areas of complex topography at each site using two separate approaches: a spatially explicit and a spatially implicit method. The spatially explicit method uses digital elevation models of the sites to calculate the solar radiation at each grid cell and hence determines the spatial distribution of environmental variables. The second, less computationally intensive, method uses estimated statistical distributions of slope and aspect within the field sites to calculate the proportion of the surface area of each site predicted to exceed a given threshold of temperature sum or potential evapotranspiration. The spatially implicit model reproduces the range of the explicit model reasonably well but is limited by the parameterisation of slope and aspect, underlining the importance of variation in topography in determining the microclimatic conditions of a site.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Predictive habitat distribution models in ecology
Guisan, A., & Zimmermann, N. E. (2000) · Ecological Modelling · doi:10.1016/s0304-3800(00)00354-9 · Cited by 7,359
Natural evaporation from open water, bare soil and grass
Penman, H. L. (1948) · Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences · doi:10.1098/rspa.1948.0037 · Cited by 7,307
Oke, T. R. (2002) · Routledge eBooks · doi:10.4324/9780203407219 · Cited by 5,219
Larcher, W. (1980) · Springer eBooks · doi:10.1007/978-3-642-96545-6 · Cited by 3,038
Geiger, R., Aron, R. H., & Todhunter, P. (1995) · Vieweg+Teubner eBooks · doi:10.1007/978-3-322-86582-3 · Cited by 2,104
Equations for potential annual direct incident radiation and heat load
McCune, B., & Keon, D. (2002) · Journal of Vegetation Science · doi:10.1111/j.1654-1103.2002.tb02087.x · Cited by 1,183
Barry, R. G. (2013) · Routledge eBooks · doi:10.4324/9780203416020 · Cited by 1,094
Ecological and evolutionary processes at expanding range margins
Thomas, C. D., Bodsworth, E. J., Wilson, R. J., Simmons, A. D., Davies, Z. G., Musche, M., & Conradt, L. (2001) · Nature · doi:10.1038/35079066 · Cited by 937
Cryptic northern refugia and the origins of the modern biota
Stewart, J. R., & Lister, A. M. (2001) · Trends in Ecology & Evolution · doi:10.1016/s0169-5347(01)02338-2 · Cited by 922
Pigott, C. D., Ratcliffe, D. A., Malloch, A. J. C., Birks, H. J. B., & Proctor, M. C. F. (2000) · Cambridge University Press eBooks · doi:10.1017/cbo9780511541834 · Cited by 852
Cited by
Quantifying Climate and Catchment Control on Hydrological Drought in the Continental United States
Konapala, G., & Mishra, A. (2020) · Water Resources Research · doi:10.1029/2018wr024620 · Cited by 168
Land-surface parameters for spatial predictive mapping and modeling
Maxwell, A. E., & Shobe, C. M. (2022) · Earth-Science Reviews · doi:10.1016/j.earscirev.2022.103944 · Cited by 105
Thomas, J., Joseph, S., Thrivikramji, K. P., & Arunkumar, K. S. (2014) · Geoscience Frontiers · doi:10.1016/j.gsf.2013.12.008 · Cited by 67
Metadata
- Authors
- Bennie, J., Huntley, B., Wiltshire, A., Hill, M. O., & Baxter, R.
- Venue
- Ecological Modelling
- Publisher
- Elsevier BV
- Published
- 2008-08
- Volume
- 216
- Issue
- 1
- Pages
- 47-59
- ISSN
- 0304-3800 (ISSN-L)
- OpenAlex
- W2022319455
- Cited by
- 580
- References
- 33
- FWCI
- 11.26
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Slope, aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland. https://app.cochat.ai/papers/10.1016/j.ecolmodel.2008.04.010
- The paper
- Bennie, J., Huntley, B., Wiltshire, A., Hill, M. O., & Baxter, R. (2008). Slope, aspect and climate: Spatially explicit and implicit models of topographic microclimate in chalk grassland. Ecological Modelling. https://doi.org/10.1016/j.ecolmodel.2008.04.010
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.