With the increased use of cameras in robotic applications, this paper presents quantitative and qualitative assessment of the most prominent monocular tracking and mapping algorithms in literature with a particular focus on natural environments. This paper is unique in both context and methodology since it quantifies the performance of the state-of-the-art in Visual Simultaneous Localization and Mapping methods in the specific context where images mostly include vegetation. Finally, we elaborate on the limitations of these algorithms and the challenges that they did not address or consider when working in the natural environment.