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Riddell EA, Burger IJ, Tyner-Swanson TL, Biggerstaff J, Muñoz MM, Levy O, Porter CK. Parameterizing mechanistic niche models in biophysical ecology: a review of empirical approaches. J Exp Biol 2023; 226:jeb245543. [PMID: 37955347 DOI: 10.1242/jeb.245543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2023]
Abstract
Mechanistic niche models are computational tools developed using biophysical principles to address grand challenges in ecology and evolution, such as the mechanisms that shape the fundamental niche and the adaptive significance of traits. Here, we review the empirical basis of mechanistic niche models in biophysical ecology, which are used to answer a broad array of questions in ecology, evolution and global change biology. We describe the experiments and observations that are frequently used to parameterize these models and how these empirical data are then incorporated into mechanistic niche models to predict performance, growth, survival and reproduction. We focus on the physiological, behavioral and morphological traits that are frequently measured and then integrated into these models. We also review the empirical approaches used to incorporate evolutionary processes, phenotypic plasticity and biotic interactions. We discuss the importance of validation experiments and observations in verifying underlying assumptions and complex processes. Despite the reliance of mechanistic niche models on biophysical theory, empirical data have and will continue to play an essential role in their development and implementation.
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Affiliation(s)
- Eric A Riddell
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Isabella J Burger
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
- Department of Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tamara L Tyner-Swanson
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Justin Biggerstaff
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
| | - Martha M Muñoz
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06511, USA
| | - Ofir Levy
- Faculty of Life Sciences, School of Zoology, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Cody K Porter
- Department of Ecology, Evolution, and Organismal Biology, Iowa State University, Ames, IA 50011, USA
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Cosentino F, Seamark ECJ, Van Cakenberghe V, Maiorano L. Not only climate: The importance of biotic interactions in shaping species distributions at macro scales. Ecol Evol 2023; 13:e9855. [PMID: 36960236 PMCID: PMC10027549 DOI: 10.1002/ece3.9855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Revised: 01/30/2023] [Accepted: 02/08/2023] [Indexed: 03/22/2023] Open
Abstract
Abiotic factors are usually considered key drivers of species distribution at macro scales, while biotic interactions are mostly used at local scales. A few studies have explored the role of biotic interactions at macro scales, but all considered a limited number of species and obligate interactions. We examine the role of biotic interactions in large-scale SDMs by testing two main hypotheses: (1) biotic factors in SDMs can have an important role at continental scale; (2) the inclusion of biotic factors in large-scale SDMs is important also for generalist species. We used a maximum entropy algorithm to model the distribution of 177 bat species in Africa calibrating two SDMs for each species: one considering only abiotic variables (noBIO-SDMs) and the other (BIO-SDMs) including also biotic variables (trophic resource richness). We focused the interpretation of our results on variable importance and response curves. For each species, we also compared the potential distribution measuring the percentage of change between the two models in each pixel of the study area. All models gave AUC >0.7, with values on average higher in BIO-SDMs compared to noBIO-SDMs. Trophic resources showed an importance overall higher level than all abiotic predictors in most of the species (~68%), including generalist species. Response curves were highly interpretable in all models, confirming the ecological reliability of our models. Model comparison between the two models showed a change in potential distribution for more than 80% of the species, particularly in tropical forests and shrublands. Our results highlight the importance of considering biotic interactions in SDMs at macro scales. We demonstrated that a generic biotic proxy can be important for modeling species distribution when species-specific data are not available, but we envision that a multi-scale analysis combined with a better knowledge of the species might provide a better understanding of the role of biotic interactions.
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Affiliation(s)
- Francesca Cosentino
- Department of Biology and Biotechnologies “Charles Darwin”Sapienza University of RomeItaly
| | | | - Victor Van Cakenberghe
- AfricanBats NPCCenturionRepublic of South Africa
- FunMorph Lab, Department of BiologyUniversity of AntwerpAntwerpBelgium
| | - Luigi Maiorano
- Department of Biology and Biotechnologies “Charles Darwin”Sapienza University of RomeItaly
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Sutton LJ, Anderson DL, Franco M, McClure CJW, Miranda EBP, Vargas FH, Vargas González JDJ, Puschendorf R. Prey resources are equally important as climatic conditions for predicting the distribution of a broad‐ranged apex predator. DIVERS DISTRIB 2023. [DOI: 10.1111/ddi.13684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/14/2023] Open
Affiliation(s)
- Luke J. Sutton
- School of Biological and Marine Sciences University of Plymouth Plymouth UK
- The Peregrine Fund Boise Idaho USA
| | | | - Miguel Franco
- School of Biological and Marine Sciences University of Plymouth Plymouth UK
| | | | | | | | | | - Robert Puschendorf
- School of Biological and Marine Sciences University of Plymouth Plymouth UK
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Douglas EJ, Hewitt J, Lohrer AM, Stephenson F. Changing intra‐ and interspecific interactions across sedimentary and environmental stress gradients. Ecosphere 2023. [DOI: 10.1002/ecs2.4373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Affiliation(s)
- Emily J. Douglas
- National Institute of Water & Atmospheric Research Hamilton New Zealand
| | - Judi Hewitt
- National Institute of Water & Atmospheric Research Hamilton New Zealand
- Department of Statistics University of Auckland Auckland New Zealand
| | - Andrew M. Lohrer
- National Institute of Water & Atmospheric Research Hamilton New Zealand
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