Assessing land suitability and spatial variability in lucerne yields across New Zealand

Autor: Edmar Teixeira, Jing Guo, Jian Liu, Rogerio Cichota, Hamish Brown, Abha Sood, Xiumei Yang, David Hannaway, Derrick Moot
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: European Journal of Agronomy, 148
European Journal of Agronomy 148 (2023)
ISSN: 1161-0301
DOI: 10.1016/j.eja.2023.126853
Popis: Lucerne (Medicago sativa L.) is a widely grown perennial legume worldwide which can provide high biomass and protein yields, biological N fixation, deep soil water extraction and a range of ecosystems services relevant to current and future agricultural systems. The potential to expand lucerne beyond its current cultivated areas in New Zealand, and its potential productivity across the country's contrasting climate zones, are currently unknown. To gain such insights, we estimated land suitability and spatial distribution of lucerne above-ground biomass across New Zealand lands considering contrasting growth conditions (rain-fed or irrigated for different soils types) and two simulation methods of different complexity (process- and GIS-based approaches). This aimed to assess yield-estimate spatial patterns and sensitivity to model selection for a wide range of combinations of water supply (i.e. irrigation and soil water storage) across New Zealand climate zones. For example, highly suitable areas for lucerne cultivation, were estimated in ∼21 thousand km2 when considering the exclusion of steep slopes, poor soil drainage and excess annual rainfall. The two crop-yield models were applied in response to 30 years of daily historical (1971–2000) weather data downscaled at 5 km resolution on suitable areas. Simulated average lucerne yields ranged from ∼4.5–28 t dry matter/ha per year. Simulations showed a distinct spatial pattern of yield decline from north to south, mainly in response to decreasing temperatures. Temporally, water limited yields were up to 4-fold more variable than under irrigation, depending on the degree of drought stress across different years. Results also unveiled systematic spatial patterns of model uncertainty quantified as yield sensitivity to model selection. For instance, simulated yields were most sensitive to model selection (6–31% of total variability, Ti) within high abiotic-stress environments (e.g. low temperature and limited water supply). Overall, soil type selection accounted for most of yield variability (58–78% Ti), being particularly important in warmer environments with variable seasonal rainfall regimes (e.g. northern regions). As expected, water supply (i.e. rain-fed or irrigated systems) was relatively more impactful on yield (8–20% Ti) for limited rainfall areas, where crops are most drought prone (e.g. east coast and central southern regions). Long-term regional scale comparisons of annual lucerne yield, between 30-year simulated distributions and point-based observations from the AgYields database, helped identify hotspots of yield overestimation. Such insights are useful to guide future research on high yield gap areas (e.g. southern colder and drier locations) and highlight key areas for model improvement (e.g. representation of multiple biotic stresses). Overall, our results provide a first gridded-model assessment of lucerne suitability and yield at national scale and quantify the share of variability explained by key climatic, management and methodological components in spatial analysis studies. These insights can inform future modelling efforts and support agricultural planning that considers the expansion of lucerne and other perennial legumes.
Databáze: OpenAIRE
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