Transdisciplinarity – An Option for Applied Landscape Ecology in Complex and Uncertain Contexts.

Applied landscape ecology is considered to have a limited impact on decision-making. To improve the effectiveness of research, above all, closer cooperation between researchers and nonacademic actors is needed. We argue that a suitable research approach in this context is transdisciplinarity (td). We refer to td as interdisciplinary research that takes place in a complex environment-society context with a strong involvement of non-academic actors during the entire research process. A brief synthesis of a case study focusing on ‘Off-site Effects of Soil Erosion on the Swiss Plateau’ illustrates a promising application of a td approach.

Why evolutionary biologists should get seriously involved in ecological monitoring and applied biodiversity assessment programs

While ecological monitoring and biodiversity assessment programs are widely implemented and relatively well developed to survey and monitor the structure and dynamics of populations and communities in many ecosystems, quantitative assessment and monitoring of genetic and phenotypic diversity that is important to understand evolutionary dynamics is only rarely integrated. As a consequence, monitoring programs often fail to detect changes in these key components of biodiversity until after major loss of diversity has occurred. The extensive efforts in ecological monitoring have generated large data sets of unique value to macro-scale and long-term ecological research, but the insights gained from such data sets could be multiplied by the inclusion of evolutionary biological approaches. We argue that the lack of process-based evolutionary thinking in ecological monitoring means a significant loss of opportunity for research and conservation. Assessment of genetic and phenotypic variation within and between species needs to be fully integrated to safeguard biodiversity and the ecological and evolutionary dynamics in natural ecosystems. We illustrate our case with examples from fishes and conclude with examples of ongoing monitoring programs and provide suggestions on how to improve future quantitative diversity surveys.