Aims Human-induced pressures such as deforestation cause anthropogenic range contractions (ARCs). Such contractions present dynamic distributions that may engender data misrepresentations within species distribution models. The temporal bias of occurrence data-where occurrences represent distributions before (past bias) or after (recent bias) ARCs-underpins these data misrepresentations. Occurrence-habitat mismatching results when occurrences sampled before contractions are modelled with contemporary anthropogenic variables; niche truncation results when occurrences sampled after contractions are modelled without anthropogenic variables. Our understanding of their independent and interactive effects on model performance remains incomplete but is vital for developing good modelling protocols. Through a virtual ecologist approach, we demonstrate how these data misrepresentations manifest and investigate their effects on model performance. Location Virtual Southeast Asia. Methods Using 100 virtual species, we simulated ARCs with 100-year land-use data and generated temporally biased (past and recent) occurrence datasets. We modelled datasets with and without a contemporary land-use variable (conventional modelling protocols) and with a temporally dynamic land-use variable. We evaluated each model's ability to predict historical and contemporary distributions. Results Greater ARC resulted in greater occurrence-habitat mismatching for datasets with past bias and greater niche truncation for datasets with recent bias. Occurrence-habitat mismatching prevented models with the contemporary land-use variable from predicting anthropogenic-related absences, causing overpredictions of contemporary distributions. Although niche truncation caused underpredictions of historical distributions (environmentally suitable habitats), incorporating the contemporary land-use variable resolved these underpredictions, even when mismatching occurred. Models with the temporally dynamic land-use variable consistently outperformed models without. Main conclusions We showed how these data misrepresentations can degrade model performance, undermining their use for empirical research and conservation science. Given the ubiquity of ARCs, these data misrepresentations are likely inherent to most datasets. Therefore, we present a three-step strategy for handling data misrepresentations: maximize the temporal range of anthropogenic predictors, exclude mismatched occurrences and test for residual data misrepresentations.

The study contributes to the studies of land cover change and sustainable development in Kenya. It scrutinizes the land use and land cover change (LULCC) and deforestation; forest ecosystem services and vulnerability of natural and human systems; forest management and land tenure; sustainable land management, development and livelihoods; and woodfuel energy in a Kenya and in Africa. It is a case study from Dakatcha Woodland, an un-protected global hotspot for biodiversity adjacent to the Kenyan coast. The local setting of Dakatcha Woodland; the relation of livelihoods, especially charcoal production, to the land cover change; and the environmental and socio-economic impact of land cover change in the study area, are studied in detail. The possibilities to promote sustainable development, livelihoods and ecosystem services in the area are reflected, too. The main objective of this study is to contribute to the planning of sustainable management of land and forests, and sustainable livelihoods of the local population in Dakatcha Woodland. Environment and its change affect biodiversity and ecosystems, and thus ecosystem services that all human beings rely upon. Weakened ecosystem services deteriorate the possibilities to have good living conditions and livelihoods. Dakatcha Woodland is experiencing both environmental and socio-economical problems due to uncontrolled clearance of hilltop Cynometra-Brachylaena forests for agriculture and for charcoal burning to meet the energy demands of both local population as well as to supply the nearby centres and towns. The main underlaying problems are poverty and lack of alternative income generating activities coupled with weak institutional framework and poor land tenure and management system. Drawing from a holistic research epistemology, the study resolves the study objectives with various methods. Remote sensing (RS) and Geographical Information Systems (GIS) provide means to assess the land cover and thus the change in the state of environment. Combined with socio-economic data collected with methods often used in Development Geography they offer ways to assess the poverty-environment linkages and offer data to land and forest resource management planning. This study contributes to the existing local land cover data by analyzing four SPOT satellite images from 2005/06 and 2011, and by forming a supervised land cover classification for those years, thus scrutinizing also the change in land cover. In-situ observation, household questionnaires (90 households were assessed in October 2010) and semi-structured expert interviews (2 from October 2010 and 3 from April 2011), add to literature review in order to reveal the significance of charcoal production to local livelihoods and environment. It was found that more than half of the 90 assessed households are involved in charcoal production which is higher figure than peer studies have suggested, and that the charcoal network is a complex entity that offers income to many, but bears an negative impact on the environment. It was discovered that, like in Kenya, in Dakatcha Woodland, too, the demand for woodfuel (charcoal and fuelwood) is one of the key drivers of deforestation and land degradation. As such, woodfuel energy is a cross-cutting issue, that ties together forest resources, livelihoods and sustainable development, and demands thus further research. The woodland areas are fragmenting and the relevance of the Important Bird Area (IBA) demarcation should be questioned because it was found that the IBA has lost woodland areas to agriculture and to woody vegetation land cover classes from 2005 to 2011. The land and forest management of Dakatcha Woodland must be planned in accordance with all stakeholders in a sustainable manner, drawing from agroforestry and participatory forest management systems, and keeping environmental factors in mind for the relevance of ecosystem services that the environment offers. Sustainable future for Dakatcha Woodland is possible, but changes are needed today.