Models Show Pawpaw Distribution with Climate Change

Abstract

The pawpaw (Asimina triloba [L.] Dunal) is a deciduous tree notable for its large edible fruit. Native to the eastern US and Canada, it has earned attention as a horticultural commodity and focus of scientific inquiry. However, few studies have modeled its potential future distribution under climate change. This study predicted the current and future potential distribution for pawpaw in North America and globally, with a focus on understanding future climatic suitability for fruit cultivation. This study first modeled suitability via the Maximum Entropy (MaxEnt) method by relating climate predictors with different datasets on pawpaw distribution, including nursery locations growing pawpaw. It also trained a boosted regression tree (BRT) model to estimate where sufficient heat accumulation for fruit ripening would occur. The models were applied to two future times (2041–2060 and 2081–2100), four emissions scenarios (SSP126, SSP245, SSP370, and SSP585), and climate projections from three climate models. Using nursery locations, the MaxEnt model yielded a mean area-under-the-curve statistic of 0.978 (standard deviation = 0.009) using 10-fold cross-validation, indicating strong predictive performance. The model suggested optimal conditions for pawpaw at these values: -4 °C for minimum temperature of coldest month, 26 °C for maximum temperature of warmest month, 88 cm for annual precipitation, and 0 % for precipitation seasonality. Models suggested shifting suitable climate conditions and accompanying increases in heat accumulation for fruit ripening. Northern America, Eastern Europe, and Northern Europe were predicted to have higher and increasing suitability; Western Europe, Southern Europe, and Eastern Asia were predicted to have higher but decreasing suitability. Little uncertainty existed due to collinearity shift or dissimilarity between current and future climate, but more uncertainty existed when predictions were based on differing climate model projections. This study provides insight into the pawpaw's potential response to climate change, and guidance on future locations for cultivation.

Main research questions

1. What are the ideal temperature and precipitation conditions for cultivating pawpaw trees?
2. How will the geographic distribution of suitable climate for pawpaw shift under future climate change scenarios?

What was already known?

Previous studies have modeled the geographic distribution of suitable climate for pawpaw in North America both presently and under future climate change scenarios.

What the research adds to the discussion?

This study extends previous work by modeling the geographic distribution of suitable climate for pawpaw globally (not just North America), in order to find regions globally that are suitable or will be suitable for cultivating the tree.

Novel methodology

Tulowiecki developed models that correlated the presence of pawpaw nurseries with climate variables, then used these modeled relationships as the basis to make predictions under different climate change scenarios.

Implications for society

Suitable climate for pawpaw will shift poleward. There are climatically-analogous regions (i.e. regions with climate similar to eastern North America, where pawpaw grows naturally) that would support the cultivation of pawpaw, that will also experience shifts in suitability for pawpaw. Temperate regions such as northern regions in eastern North America, eastern Europe, northern Europe, portions of northeast Asia, southeastern Australia, and New Zealand, may possess climates that persistently favor growing pawpaw.

Implications for research

It may motivate further investigations into the suitability of global regions for pawpaw cultivation. This study focused on climate conditions, but future work may also seek to investigate the suitability of different soil conditions for growing pawpaw.

Additional information

This study was co-authored by a SUNY Geneseo student, Naomi LaDuke '24. Portions of class assignments in biogeography and GIS courses were utilized in this research.