Abstract
Landscape indicators, when combined with information about environmental conditions (such as habitat
potential, biodiversity, carbon and nutrient cycling, and erosion) and socioeconomic forces, can
provide insights about changing ecosystem services. They also provide information about opportunities
for improving natural resources management. Landscape indicators rely on data regarding land cover,
land management and land functionality. Challenges in using landscape indicators to assess change and
effects include (1) measures of land management and attributes that are reliable, robust and consistent
for all areas on the Earth do not exist, and thus land cover is more frequently utilized; (2) multiple types of
land cover and management are often found within a single landscape and are constantly changing, which
complicates measurement and interpretation; and (3) while causal analysis is essential for understanding
and interpreting changes in indicator values, the interactions among multiple causes and effects over
time make accurate attribution among many drivers of change particularly difficult. Because of the complexity,
sheer number of variables, and limitations of empirical data on land changes, models are often
used to illustrate and estimate values for landscape indicators, and those models have several problems.
Recommendations to improve our ability to assess the effects of changes in land management include
refinement of questions to be more consistent with available information and the development of data
sets based on systematic measurement over time of spatially explicit land qualities such as carbon and
nutrient stocks, water and soil quality, net primary productivity, habitat and biodiversity. Well-defined
and consistent land-classification systems that are capable of tracking changes in these and other qualities
that matter to society need to be developed and deployed. Because landscapes are so dynamic, it is crucial
to develop ways for the scientific community to work together to collect data and develop tools that will
enable better analysis of causes and effects and to develop robust management recommendations that
will increases land’s capacity to meet societal needs in a changing world.
