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    Predicting fundamental climate niches of forest trees

    Species climate niche models (CNMs) have been widely used for assessing climate change impact, developing conservation strategies and guiding assisted migration for adaptation to future climates. However, the CNMs built based on species occurrence data only reflect the species’ realized niche, which can overestimate the potential loss of suitable habitat of existing forests and underestimate the potential of assisted migration to mitigate climate c…

    Species climate niche models (CNMs) have been widely used for assessing climate change impact, developing conservation strategies and guiding assisted migration for adaptation to future climates. However, the CNMs built based on species occurrence data only reflect the species’ realized niche, which can overestimate the potential loss of suitable habitat of existing forests and underestimate the potential of assisted migration to mitigate climate change. In this study, we explored building a fundamental climate niche model using widely available species occurrence data with two important forest tree species, lodgepole pine (Pinus contorta Dougl. ex Loud.) and Douglas-fir (Pseudotsuga menziesii Franco.), which were introduced to many countries worldwide. We first compared and optimized three individual modeling techniques and their ensemble by adjusting the ratio of presence to absence (p/a) observations using an innovative approach to predict the realized climate niche of the two species. We then extended the realized climate niches to their fundamental niches by determining a new cut-off threshold based on species occurrence data beyond the native distributions. We found that the ensemble model comprising Random Forest and Maxent had the best performance and identified a common cut-off threshold of 0.3 for predicting the fundamental climate niches of the two species, which is likely applicable to other species. We then predicted the fundamental climate niches of the two species under current and future cli…

    ScienceDirect

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    Most existing climate niche models predict species realized niche.

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    A fundamental climate niche model was developed based on forest occurrence data.

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    A novel method for climate niche model optimization was devised.

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    This modeling approach is likely applicable to other species.

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    Projected fundamental niches can improve conservation and assisted migrati…

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    Ecological niche models

    Species distribution models

    Random forest

    Maxent

    Climate change impact

    Assisted migration

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    Rapid anthropogenic climate change is expected to result in a mismatch between the climate that trees are adapted to and the climate that they will experience in the future (Aitken et al., 2008). Mismatches between experienced and optimal climates can compromise forest ecosystems’ health and productivity, reducing their capacity to provide ecological, economic, and social services (Malhi et al., 2020). Climate niche models (CNMs) (also known as species distribution models (SDMs), bioclimatic envelope models, or ecological niche models (ENMs)) have been widely used to predict suitable habitats for forest tree species and forest populations for the current and projected future climates (Araújo and Peterson, 2012), assess the impact of climate change and develop climate change adaptation and conservation strategies, including assisted migration (Pedlar et al., 2012).

    Hutchinson (1957) defined a species’ fundamental niche as the full range of biotic and abiotic environmental conditions within which a species can survive, grow and regenerate. He also distinguished the fundamental niche from a species’ realized niche, which is a portion of its fundamental niche limited by physical, biological, and historical factors such as competition, dispersal limits, and human disturbance (Pearson and Dawson, 2003). Booth et al. (1988) was the first paper to relate Hutchinson’s (1957) niche concept to CNM. The first …

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    2.1. Species occurrence data

    Species occurrence data of lodgepole pine and Douglas-fir from within and beyond their native distributions were obtained from various data sources (Table 1). Observations of presence and absence within species’ native ranges were used for model building, climate variable selection, and model performance evaluation, while global observations of occurrence were used for model validation and determining the optimal cut-off threshold for predicting the fundamental climate niche. Table 1. Numbers of presence, absence, and pseudo-absence observations for lodgepole pine and Douglas-fir by the data source for each data type. Notes: ePlotBC represents BC ecological plots; FIA represents USDA Forest Service’s Forest Inventory and Analysis database; ESIS represents Ecological Site Information System database; GBIF represents Global Biodiversity Information Facility.

    2.2. Climate data

    Climate variables for presence and absence points were generated from ClimateNA (Wang et al., 2016). For model building, values of all 66 annual and seasonal climate variables (full list in Section S1) were generated for the spec…

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