Plant invasion correlation with climate anomaly: an Indian retrospect

  • Poonam TripathiEmail author
  • Mukunda Dev Behera
  • Partha Sarathi Roy
Original Paper


Plant invasion is highly responsive to rising temperature, altered precipitation and various anthropogenic disturbances. Therefore, climate anomalies might provide opportunities to identify the relationship of past climate in deriving the distribution of invasive species and to detect their probable future distribution. In this work, we studied the correlation of climate anomaly i.e. temperature and precipitation with an indicative map of plant invasive species (1° grid) of India. The indicative map was generated through the plant data available from the project ‘Biodiversity Characterization at Landscape Level’. Climate anomaly was calculated and represented by average temperature and precipitation using ‘Climate Research Unit’ data for the period of 1901 to 2000. A comparison of local geographically weighted regression (GWR) model and a global ordinary least square regression (OLS) model was carried out for statistical analysis to depict the correlation at 1° spatial grids. Overall, 20,501 records with a total of 9112 unique plots and 161 unique invasive species were recorded in the database that shows a maximum of 15 invasive species in a 0.04 ha nested quadrat. Cumulative analysis showed a maximum of 53 invasive species at 1° grid. Individually, GWR could reveal a significant correlation with invasive species distribution for temperature anomaly (r2 = 0.73, AIC= 2206) and precipitation anomaly (r2 = 0.74, AIC= 2221), while OLS model did not offer a good correlation (r2 < 0.001, AIC > 2400) compared to GWR. Combination of temperature and precipitation anomaly (shared model) showed an improved spatial correlation (r2 > 0.75) using GWR. Variation partitioning revealed the dominant influence (> 0.40 of variation) of temperature anomaly over Deccan Peninsula, Himalaya and North East zone. Influence of precipitation anomaly was more prominent over arid and semi-arid zone explaining > 0.35 of variation. Results revealed the strength of GWR to see the interaction of invasive plant species w.r.t. climate anomalies that explain the influence of spatial variation due to heterogeneity at varying neighbour distances. The significant correlation of invasive species with both the anomalies revealed the affinity of invasive species towards warmer, drier and wet places. This gives an indication that the distribution of invasive species could be triggered by climate anomaly. The use of other predictor variables (i.e. edaphic and anthropogenic) could be an inclusive input in a future perspective.


Climate change Anomaly Invasive species GWR OLS India 



The views and interpretations in this publication are those of the authors and are not necessarily attributable to ICIMOD.

Supplementary material

10531_2019_1711_MOESM1_ESM.docx (125 kb)
Supplementary material 1 (DOCX 124 kb)


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Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  • Poonam Tripathi
    • 1
    • 2
    Email author
  • Mukunda Dev Behera
    • 2
  • Partha Sarathi Roy
    • 3
  1. 1.International Centre for Integrated Mountain DevelopmentKathmanduNepal
  2. 2.Centre for Oceans, Rivers, Atmosphere and Land Sciences (CORAL)Indian Institute of Technology KharagpurKharagpurIndia
  3. 3.System Analysis for Climate Smart Agriculture, Innovation Systems for the Dry LandsICRISATHyderabadIndia

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