Cost and efficiency of cutting lianas in a lowland liana forest in Bolivia

Liana cutting is a commonly suggested silvicultural practice aimed at reducing the negative impacts of lianas on timber production, but few experimental studies have been conducted to evaluate the cost and efficiency of this practice. In this study, we estimated the cost of cutting lianas in 12 plots of 0.25 ha each in a densely liana-infested forest of lowland Bolivia, and evaluated the efficiency of this silvicultural treatment in terms of the proportion of lianas missed, the density of resprouting liana stumps, and the number of liana-infested trees after two years of an experimental liana treatment. The cost of cutting lianas in this forest by locally hired laborers was 23.6 (SE = 2.48) person-hours/ha. Considering local cost of labor and the U.S.–Bolivian currency exchange rate at the time of the study, this figure translates to ca $15/ha. Liana density decreased from 2471 (SE = 104.3) to 130 (SE = 24.2) liana stems ≥2 cm/ha immediately after cutting, because 5.5 percent of lianas were left uncut (missed). Slender lianas were missed more often than lianas with large-diameter stems. Liana species that grow 2–3 m before they start to twine were also frequently missed. Twenty-two percent of liana stumps ≥2 cm sprouted after cutting. Liana stumps with larger diameters sprouted more than stumps with smaller diameters. Most liana stumps produced only two sprouts. Two years after cutting, 78 percent of trees had no living lianas in their crowns, in contrast to only 13 percent liana-free trees in the control plots. Sixty-four percent of trees still had hanging dead lianas two years after cutting, but only 23 percent of trees were reinvaded by lianas using dead liana stems as trellises. Liana cutting can efficiently reduce the number of lianas in liana-infested forests, and the effects of cutting lianas last for at least two years; however, the treatment is expensive. Thus, we recommend that it is better to view liana cutting as a preventive activity to avoid liana infestation, rather than as a corrective measure after poor management. Liana cutting can be easily conducted along with other reduced-impact logging practices

Driving forces of tropical deforestation: The role of remote sensing and spatial models

Remote sensing technologies are increasingly used to monitor landscape change in many parts of the world. While the availability of extensive and timely imagery from various satellite sensors can aid in identifying the rates and patterns of deforestation, modelling techniques can evaluate the socioeconomic and biophysical forces driving deforestation processes. This paper briefly reviews some emerging spatial methodologies aimed at identifying driving forces of land use change and applies one such methodology to understand deforestation in Mexico. Satellite image classification, change analysis and econometric modelling are used to identify the rates, hotspots and drivers of deforestation in a case study of the southern Yucatán peninsular region, an enumerated global hotspot of biodiversity and tropical deforestation. In particular, the relative roles of biophysical and socioeconomic factors in driving regional deforestation rates are evaluated. Such methodological approaches can be applied to other regions of the forested tropics and contribute insights to conservation planning and policy. © 2006 Department of Geography, National University of Singapore and Blackwell Publishing Asia Pty Ltd

Liana diversity and the future of tropical forests

Lianas contribute substantially to the total species richness of tropical forests, accounting for up to a quarter of the woody plant diversity. However, liana diversity is intrinsically linked with forest condition and consequently is altered by human-induced forest modifications. Multiple environmental drivers including forest fragmentation, logging and climate change are impacting tropical forests; the extent and degree of their effects will likely define future global liana diversity