Open Access

Nsikan-George Emana

• As a cognitively-mediated response, autonomous adaptation at farm-gate levels constitutes reactionary actions by farmers against climate impacts. These actions are shaped by interacting factors such as household characteristics, livelihood scope and resources. It is driven by the goal of adapting cultivated farmlands to climate and for sustaining crop yields. Thus, interest in balancing adaptation goals with protection of vegetation conditions is less of a priority. Lack of research interest in understanding the gap between objectives of reactionary adaptation and protection of surface conditions (vegetation canopies) is a gap in research. In many studies, farm-gate level adaptation is described as a set of zero-feedback actions in response to climate impacts. This perception conceals the stress and impact-engendering attribute of reactionary adaptation. Inspired towards addressing this conceptual gap; this study investigates impact of farmers’ reactionary adaptation on vegetation cover in Keffi, Nasarawa, Nigeria. A twenty-year time-series NDVI and rainfall datasets are linearly regressed to examine the extent of NDVI-rainfall sensitivity. A weak linear relationship between NDVI and rainfall in Keffi for the period, 1999-2018 is observed. At a regression slope of 0.001, R squared, R2=0.129 (implying that only about 13% of the variability in NDVI in Keffi are explained by rainfall amount) and a bivariate regression coefficient, r=0.359; statistical evidence shows that rainfall amount are not significant predictors of NDVI in Keffi. In investigating the possible interference of non-rainfall factors on vegetation productivity (NDVI) in Keffi; a residual trend (RESTREND) analysis was carried out. Regression of residuals from NDVI-Rainfall linear regression produced a R=0.192 with a negative and downwards slope. The downward character of the RESTREND slope is suggestive of non-rainfall factors contained in the residuals. In validating the RESTREND analysis, a comparative analysis between observed and predicted NDVI derived from a reference NDVI value of 0.46 was carried out. The NDVI value of 0.46, is empirically assumed to be average NDVI value expected at a minimum rainfall amount of 850mm/year reported in tropical Savanna ecosystems. Using this empirical relationship, NDVI values were predicted for Keffi. Even at higher rainfall amounts≈1340mm/year, amounts were unable to produce corresponding higher NDVI values; rather a more plausible correlation between reference-derived predicted NDVI values and rainfall was obtained. A further analysis with predicted NDVI values, based on 1999 NDVI value in Keffi returned higher NDVI units than observed NDVI values. This strengthens the attribution of the possible interference of rainfall-NDVI sensitivity by non-rainfall factors like human activities on vegetation productivity. Surface soil analysis to exclude potential impacts of soil nutrients and moisture deficiency on vegetation productivity, showed that soil had insignificant effect on vegetation dynamics. Further inferential analysis, using the inter-annual NDVI and the reclassified bi-decadal NDVI maps showed that spatial vegetation distribution in Keffi were driven by farmers inter-annual rotational cultivation footprints than rainfall variability. With a three-class categorization, “gain, loss and significant loss”, the spatial distribution of vegetation in Keffi between (1999-2008) and (2009-2018) was assessed. Temporal condition (stressed and healthy) across the three classes supports the attribution of farmers’ reactionary adaptation and cultivation practices on the dynamic spatial vegetation distribution. Between 1999 -2018, an increase in areas with significant vegetation loss (42%), so with a decrease of -25% in areas with healthy vegetation was observed. The character of vegetation cover across the two decadal time slices, reflects landuse intensity and unsustainable farming practices. Preferences for modification of cultivation practices and changes in seed by farmers exerts positive feedbacks on vegetation cover. Higher statistical measures, 38.4% (yearly cropping) and 44% (shifting cultivation with less fallow periods) were observed in the chi-square analysis. These measures were higher than 2.0% relating to shifting cultivation with more fallow periods. While 11.6% farmers noted cultural practices as reasons for preferred cultivation methods, 48.4% farmers attributed climate as reason behind cultivation modification. This was higher than 24.4% who linked issues of tenure rights to cultivation practices. With preferences for yield- breaching strategies, the non-receding cultivation and shorter fallow practices in Keffi triggers feedback on vegetation dynamics. Evidence from this study shows that the NDVI-rainfall functional sensitivity in Keffi is plausibly dampened by effects of reactionary farm-gate level adaptation practices.