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Pilgrim, J. D., Brownlie, S., Ekstrom, J. M. M., Gardner, T., Von Hase, A., Kate, K. T., Savy, C. E., Stephens, R. T. T., Temple, H., Treweek, J., Ussher, G. T., & Ward, G. (2013). A Process for Assessing the Offsetability of Biodiversity Impacts. Conservation Letters, 6, 376-384. https://doi.org/10.1111/conl.12002

has been cited by the following article:

• TITLE: Floristic Composition, Diversity and Structure of the Rainforest in the Mayoko District, Republic of Congo

  AUTHORS: Margaretha W. van Rooyen, Noel van Rooyen, Edmond S. Miabangana, Gilbert Nsongola, Caroline Vasicek Gaugris, Jérôme Y. Gaugris

  KEYWORDS: Congo, Diversity, Evenness, Fisher’s Alpha, Flora, Phytosociology, Species Richness, Structure, Rainforest, Vegetation Dynamics

  JOURNAL NAME: Open Journal of Forestry, Vol.9 No.1, January 21, 2019

  ABSTRACT: Botanically, the Mayoko district is known only through anecdotal descriptions made in the colonial era. The present study was undertaken as part of the prerequisite for a mining feasibility study where a benchmark of the floristic composition, diversity and structure of the vegetation was needed to evaluate potential biodiversity offset areas and to guide species selection for post-mining re-vegetation. The study area comprised approximately 160,000 ha and 235 sample sites were surveyed using the Braun-Blanquet method of phytosociology. Diversity of each plant association was expressed in terms of various diversity parameters. Twelve associations were described and mapped. The associations ranged from highly disturbed and degraded to fairly intact forest associations. A wet to dry gradient and permanently inundated to temporary inundated gradient could also be distinguished. The approach followed here proved remarkably robust in illustrating the complexity in a topographically complex region of the Chaillu Massif. The data provided a high level of insight into the possible dynamics of the rainforest and indications as to possible successional pathways. This information provides a better level of understanding of forest structure and evolution potential than studies limited to trees, remote sensing carbon assessments, or time change series.