Browsing by Subject "DEFORESTATION"

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    Changes in evapotranspiration and phenology as consequences of shrub removal in dry forests of central Argentina
    (Ecohydrology, 2015-10-01) Marchesini, VA; Fernández, RJ; Reynolds, JF; Sobrino, JA; Di Bella, CM
    More than half of the dry woodlands (forests and shrublands) of the world are in South America, mainly in Brazil and Argentina, where in the last years intense land use changes have occurred. This study evaluated how the transition from woody-dominated to grass-dominated system affected key ecohydrological variables and biophysical processes over 20000ha of dry forest in central Argentina. We used a simplified surface energy balance model together with moderate-resolution imaging spectroradiometer-normalized difference vegetation index data to analyse changes in above primary productivity, phenology, actual evapotranspiration, albedo and land surface temperature for four complete growing seasons (2004-2009). The removal of woody vegetation decreased aboveground primary productivity by 15-21%, with an effect that lasted at least 4years, shortened the growing season between 1 and 3months and reduced evapotranspiration by as much as 30%. Albedo and land surface temperature increased significantly after the woody to grassland conversion. Our findings highlight the role of woody vegetation in regulating water dynamics and ecosystem phenology and show how changes in vegetative cover can influence regional climatic change. © 2015 John Wiley
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    Convergent evolution in lemur environmental niches
    (Journal of Biogeography, 2020-04-01) Herrera, JP
    Aim: To test the hypothesis that adaptive convergent evolution of climate niches occurred in multiple independent lemur lineages. Location: Madagascar. Taxon: Lemurs. Methods: I collected climate and altitude data from WorldClim and summarized the niches of almost all living lemurs (83 species) into phylogenetically controlled principal components. To test for convergent evolution, I searched for multiple, similar climate optima using multi-peak Ornstein–Uhlenbeck models (surface, l1-ou, bayou). I compared the observed level of climate convergence to that simulated under neutral and single-optimum models. To test if behavioural or morphological traits were related to climate niches, I used phylogenetic regressions with activity pattern, diet, and body size. Results: From an ancestral niche with high rainfall and low seasonality, four lemur lineages independently converged on climate niche optima characterized by high temperatures and low rainfall, supporting adaptive evolution in southwest deciduous and arid habitats. The observed level of convergence was more frequent than expected under Brownian motion and single-optimum simulations, which illustrates that the results are likely not a result of stochastic evolution over long time periods. Nocturnal and cathemeral activity patterns were common among lineages in the arid climate niche. Conclusion: Lemur climate niche evolution demonstrated that convergence explains the distribution of four independent clades in hot, arid environments of southwest Madagascar. The timing of these convergent shifts coincided with the origination of modern arid-adapted plant genera, some of which are important lemur food sources. These communities have high endemicity and are especially threatened by habitat loss. Arid environments are arenas in which convergent evolution is predicted to occur frequently.
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    Estimates and determinants of stocks of deep soil carbon in Gabon, Central Africa
    (Geoderma, 2019-05-01) Wade, AM; Richter, DD; Medjibe, VP; Bacon, AR; Heine, PR; White, LJT; Poulsen, JR
    © 2019 Despite the importance of tropical forest carbon to the global carbon cycle, research on carbon stocks is incomplete in major areas of the tropical world. Nowhere in the tropics is this more the case than in Africa, and especially Central Africa, where carbon stocks are known to be high but a scarcity of data limits understanding of carbon stocks and drivers. In this study, we present the first nation-wide measurements and determinants of soil carbon in Gabon, a nation in Central Africa. We estimated soil carbon to a 2-m depth using a systematic, random design of 59 plots located across Gabon. Soil carbon to a 2-m depth averaged 163 Mg ha −1 with a CV of 61%. These soil carbon stocks accounted for approximately half of the total carbon accumulated in aboveground biomass and soil pools. Nearly a third of soil carbon was stored in the second meter of soil, averaging 58 Mg ha −1 with a CV of 94%. Lithology, soil type, and terrain attributes were found to be significant predictors of cumulative SOC stocks to a 2-m depth. Current protocols of the IPCC are to sample soil carbon from the surface 30 cm, which in this study would underestimate soil carbon by 60% and underestimate ecosystem carbon by 30%. A nonlinear model using a power function predicted cumulative soil carbon stocks in the second meter with an average error of prediction of 3.2 Mg ha −1 (CV = 915%) of measured values. The magnitude and turnover of deep soil carbon in tropical forests needs to be estimated as more countries prioritize carbon accounting and monitoring in response to accelerating land-use change.