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© 2019 The Authors Cellular Automata (CA) land-use models are widely used for understanding processes of land-use change. However, calibration of these models is a knowledge-intensive and time-consuming process. Although calibration of common driving factors such as accessibility (A), or suitability (S) is a relatively straightforward task, calibrating the neighbourhood dynamics (N), which controls the key model behaviour, is often very challenging. Here, building on the SIMLANDER modelling framework, we develop an automatic rule detection (ARD) procedure to automate the calibration of N. To demonstrate the performance of the tool, we simulated 15 years of urban growth in Ahvaz, Iran (2000–2015) using a wide range of different rule-sets. We evaluated calibration goodness-of-fit for each rule-set against a reference map by means of cross-comparison of multiple metrics using a ranking procedure. The ARD procedure can be implemented in two ways: 1) by random sampling of the parameter space, a user-defined number of times, or 2) through a stepwise “grid search” approach for a user-defined number of rule combinations. Both approaches were found to produce successful rule combinations according to the goodness-of-fit metrics applied. Grid search performed slightly better, but at the cost of a fivefold increase in computation time. The ARD approach facilitates model calibration by allowing rapid identification of the optimum ruleset from a wide range of possible parameter settings, while the ranking procedure facilitates comparison of simulations using multiple metrics. The approach we present also helps to improve simulation accuracy with respect to manual calibration methods, and increases understanding of neighbourhood dynamics for the urban area studied. To encourage repeatability and transparency, our approach uses only open data and Free-and-Open Source Software (RStudio environment) and we provide our ARD scripts as supplementary material

Experiences with nature through visits to protected areas provide important cultural ecosystem services that have the potential to strengthen pro-environmental attitudes and behavior. Understanding accessibility to protected areas and likely preferences for enjoying the benefits of nature visits are key factors in identifying ways to reduce inequality in access and inform the planning and management for future protected areas. We develop, at a regional scale, a novel social media database of visits to public protected areas in part of the Chilean biodiversity hotspot using geotagged photographs and assess the inequality of access using the home locations of the visitors and socio-economic data. We find that 20 of the population of the region make 87 of the visits to protected areas. The larger, more biodiverse protected areas were the most visited and provided most cultural ecosystem services. Wealthier people tend to travel further to visit protected areas while people with lower incomes tend to visit protected areas that are closer to home. By providing information on the current spatial flows of people to protected areas, we demonstrate the need to expand the protected area network, especially in lower income areas, to reduce inequality in access to the benefits from cultural ecosystem services provided by nature to people. © 2018 Elsevier B.V.

Policy-driven shifts from net deforestation to forest expansion are being stimulated by increasing social preferences for forest ecosystem services. However, policy uncertainty can disrupt or reverse the positive effects of forest transitions. For instance, if the loss of remnant (primary) forest continues, the ecological benefits of net forest gains may be small. We investigated how peak periods of uncertainty in forest conservation policy affected forest transition outcomes in Queensland, Australia, as well as a globally-relevant biodiversity hotspot in the state, the Brigalow Belt South (BBS) bioregion. Political, socioeconomic, and biophysical factors associated with net forest cover change and remnant forest loss from 1991 to 2014 were identified through spatial longitudinal analysis. This informed a Bayesian structural causal impact assessment of command-and-control regulation and policy uncertainty on remnant and non-remnant forest cover. The results indicate that forest cover was negatively influenced by increasing temperatures, food prices, and policy uncertainty, and positively influenced by strengthening regulation. Regulation during 2007–2014 avoided 68,620 ± 19,214 km2of deforestation (with 18,969 ± 10,340 km2of this in remnant forests) throughout Queensland, but was ineffective on remnant forests in the BBS. For state-wide remnant forests, perverse effects from policy uncertainty (e.g. pre-emptive deforestation) were strong enough to negate regulatory impacts. This study reveals a cautionary tale for conservation policy: despite strict environmental regulations, forest transition can be delayed (or reversed) when political inconsistency or instability provoke unintended reactions from landholders.

Understanding potential future influence of environmental, economic, and social drivers on land-use and sustainability is critical for guiding strategic decisions that can help nations adapt to change, anticipate opportunities, and cope with surprises. Using the Land-Use Trade-Offs (LUTO) model, we undertook a comprehensive, detailed, integrated, and quantitative scenario analysis of land-use and sustainability for Australia’s agricultural land from 2013–2050, under interacting global change and domestic policies, and considering key uncertainties. We assessed land use competition between multiple land-uses and assessed the sustainability of economic returns and ecosystem services at high spatial (1.1 km grid cells) and temporal (annual) resolution. We found substantial potential for land-use transition from agriculture to carbon plantings, environmental plantings, and biofuels cropping under certain scenarios, with impacts on the sustainability of economic returns and ecosystem services including food/fibre production, emissions abatement, water resource use, biodiversity services, and energy production. However, the type, magnitude, timing, and location of land-use responses and their impacts were highly dependent on scenario parameter assumptions including global outlook and emissions abatement effort, domestic land-use policy settings, land-use change adoption behaviour, productivity growth, and capacity constraints. With strong global abatement incentives complemented by biodiversity-focussed domestic land-use policy, land-use responses can substantially increase and diversify economic returns to land and produce a much wider range of ecosystem services such as emissions abatement, biodiversity, and energy, without major impacts on agricultural production. However, better governance is needed for managing potentially significant water resource impacts. The results have wide-ranging implications for land-use and sustainability policy and governance a

Land sparing and land sharing are contrasting strategies often aimed at improving both agricultural production and biodiversity conservation in multifunctional landscapes. These strategies are embodied in land management policies at local to international scales, commonly in conjunction with other land-use policies. Evaluation of these strategies at a landscape scale, for multiple ecosystem service benefits, and multiple elements of biodiversity has not previously been attempted. We simulated the effects of applying land sharing and land sparing strategies to the agricultural zones designated by four future land-use scenarios (reflecting both current land-use and prospective land-use plans) in the Ex-Mega Rice Project region of Central Kalimantan, Indonesia. We assessed impacts of each strategy on biodiversity, agricultural production, and other ecosystem service benefits at a landscape scale. We examined whether it was possible to achieve predetermined targets that reflect the aspirations and entitlements of diverse stakeholder groups. We found that the prospective land-use plans for the region would deliver considerably more benefit than the current land-use allocations, and while not all targets can be achieved, additional progress could be made with reasonable and realistic levels of land sharing or sparing. We found that species and forest types sensitive to agricultural disturbance could benefit most if land in agricultural zones was spared and prioritised for conservation. Conversely, land sharing strategies favoured the more widespread and common species, particularly if the area of wildlife-friendly agriculture is increased. However, the effectiveness of agricultural-focused land management strategies is inherently limited by the extent of agricultural zones. While agricultural land sparing and sharing strategies can deliver some gains in target achievement for multiple ecosystem services, we find that they have a limited effect over the benefits achieved b

Numerous assessments have quantified, mapped, and valued the services provided by ecosystems that are important for human wellbeing. However, much of the literature does not clarify how the information gathered in such assessments could be used to inform decisions that will impact ecosystem services. We propose that the process of making management decisions for ecosystem services comprises five core steps: identification of the problem and its social-ecological context; specification of objectives and associated performance measures; defining alternative management actions and evaluating the consequences of these actions; assessment of trade-offs and prioritization of alternative management actions; and making management decisions. We synthesize the degree to which the peer-reviewed ecosystem services literature has captured these steps. For the ecosystem service paradigm to gain traction in science and policy arenas, future ecosystem service assessments should have clearly articulated objectives, seek to evaluate the consequences of alternative management actions, and facilitate closer engagement between scientists and stakeholders.

Carbon stocks and emissions are quantified using many different measures and metrics, and these differ in their surrogacy, measurement, and incentive value. To evaluate potential policy impacts of using different carbon measures, we modeled and mapped carbon in above-ground and below-ground stocks, as well as fluxes related to sequestration, oxidation and combustion in the Ex Mega Rice Project Area in Central Kalimantan, Indonesia. We identify significant financial and carbon emission mitigation consequences of proxy choice in relation to the achievement of national emissions reduction targets. We find that measures of above-ground biomass carbon stock have both high measurement and incentive value, but low surrogacy for potential emissions or the potential for emissions reductions. The inclusion of below-ground carbon increased stocks and flows by an order of magnitude, highlighting the importance of protecting and managing soil carbon and peat. Carbon loss and potential emissions reduction is highest in the areas of deep peat, which supports the use of deep peat as a legislative metric. Divergence in patterns across sub-regions and through time further emphasizes the importance of proxy choice and highlights the need to carefully consider the objectives of the application to which the measure of carbon will be applied.

European colonization precipitated the first industrial transformation of Australian landscapes. We review the evolution of the environmental and societal setting of Australian landscapes since this first industrial transformation, the emergence of drivers precipitating a second industrial transformation, and what it will take to adapt. In concert with climate change and growing societal expectations of environmental stewardship, we identify six emerging economies for ecosystem services - carbon, water, food, energy, amenity and mining - which will exert transformational pressure on land use and management. The requirements for transformational adaptation - to thrive within environmental limits - include: fostering new partnerships between government, science, the private sector, and local communities to support local adaptation; identifying critical environmental limits and rationalizing environmental laws; establishing innovative social processes and adaptive governance; and developing innovative, well-supported market-based and community-based incentives.