ForestSim model of impacts of smallholder dynamics: forested landscapes of the Upper Peninsula of Michigan

Many forested landscapes in the United States contain a large number of small private landowners (smallholders). The individual decisions of these smallholders can collectively have a large impact on the structure, composition, and connectivity of forests. While models have been developed to try to understand this large-scale collective impact, few models have incorporated extensive information from individual decision-making. Here we introduce an agent-based model, infused with sociological data from smallholders, overlaid on a GIS layer to represent individual smallholders, and used to simulate the impact of thousands of harvesting decisions. Our preliminary results suggest that certain smallholder characteristics (such as relative smallholder age and education level as well as whether a smallholder is resident or absentee) and information flow among owners can radically impact forests at the landscape scale. While still in its preliminary stages, this modeling approach is likely to demonstrate in detail the consequences of decision-making due to changing smallholder demographics or new policies and programs. This approach can help estimate the effectiveness of programs based on landscape-scale programmatic goals and the impact of new policy initiatives

Critical review of the millennium project in Nepal

“Our Common Future” harmonized development policies around a new sustainable development (SD) paradigm, and experts also emphasize the importance of a democratic and equitable approach to define and achieve sustainable development. However, SD targets and indicators are often defined by a suite of experts or a few stakeholder groups, far removed from on-the-ground conditions. The most common expert-led development framework, the United Nations’ Millennium Development Goals (MDGs), promoted one set of targets and indicators for all developing countries. While progress towards these targets was routinely reported at the national scale, these targets may not reflect context-specific sustainable development. We evaluated the relevance and comprehensiveness of MDG 7 (environmental sustainability) for Nepal. Although Nepal has met most of the MDG 7 (e.g., forest cover, protected areas coverage, water and sanitation), on closer inspection these indicators do not provide adequate context for ensuring that these targets provide the intended levels of development. Simple forest cover and protected area indicators belie the dearth of ecological conservation on the ground, and water and sanitation indicators do not reflect the inequality of access based on poverty and regions. While the Millennium Development Goals align with broad sustainability concerns in Nepal, these indicators do not reveal its true development conditions

Peer influence of non-industrial private forest owners in the Western Upper Peninsula of Michigan

Understanding how non-industrial private forest (NIPF) owners gain and share information regarding the management of their property is very important to policy makers, yet our knowledge regarding how and to what degree this information flows over privately owned landscapes is limited. The work described here seeks to address this shortfall. Widely administered surveys with close-ended questions may not adequately capture this information flow within NIPF owner communities. This study used open-ended questions in interviews of clusters of NIPF owners to determine whether and to what extent owners influence each other directly (through conversations or referrals to sources of advice) or indirectly (through observation of management). We obtained data from thirty-four telephone interviews with owners of NIPF properties in the Western Upper Peninsula of Michigan, and analyzed the data using open coding. Roughly half of the forest owners we interviewed were influenced either directly or indirectly by other members of their NIPF communities. Reasons for owning forests (such as privacy, hunting and nature recreation, and economics) also influenced owners’ management behaviors and goals. This peer-to-peer flow of information (whether direct or indirect) has significant implications for how to distribute management and programmatic information throughout NIPF owner communities, and how amenable these communities may be to cooperative or cross-boundary programs to achieve ecosystem and landscape- scale goals

Use of remote sensing to support forest and wetlands policies in the USA

The use of remote sensing for environmental policy development is now quite common and well-documented, as images from remote sensing platforms are often used to focus attention on emerging environmental issues and spur debate on potential policy solutions. However, its use in policy implementation and evaluation has not been examined in much detail. Here we examine the use of remote sensing to support the implementation and enforcement of policies regarding the conservation of forests and wetlands in the USA. Specifically, we focus on the “Roadless Rule” and “Travel Management Rules” as enforced by the US Department of Agriculture Forest Service on national forests, and the “No Net Loss” policy and Clean Water Act for wetlands on public and private lands, as enforced by the US Environmental Protection Agency and the US Army Corps of Engineers. We discuss several national and regional examples of how remote sensing for forest and wetland conservation has been effectively integrated with policy decisions, along with barriers to further integration. Some of these barriers are financial and technical (such as the lack of data at scales appropriate to policy enforcement), while others are political

Detecting dynamic system regime boundaries with Fisher information: the case of ecosystems

The direct measurement of the resilience (resistance to disturbances) of an ecosystem’s current regime (or “alternative stable state”) remains a key concern for managing human impacts on these ecosystems and their risk of collapse. Approaches which utilize statistics or information theory have demonstrated utility in identifying regime boundaries. Here, we use Fisher information to establish the limits of the resilience of a dynamic regime of a predator–prey system. This is important because previous studies using Fisher information focused on detecting whether a regime change has occurred, whereas here we are interested in determining how much an ecological system can vary its properties without a regime change occurring. We illustrate the theory with simple two species systems. We apply it first to a predator–prey model and then to a 60-year wolf–moose population dataset from Isle Royale National Park in Michigan, USA. We assess the resilience boundaries and the operating range of a system’s parameters without a regime change from entirely new criteria for Fisher information, oriented toward regime stability. The approach allows us to use system measurements to determine the shape and depth of the “cup” as defined by the broader resilience concept

Using an OBCD approach and Landsat TM data to detect harvesting on nonindustrial private property in Upper Michigan

Forest dynamics influence climate, biodiversity, and livelihoods at multiple scales, yet current resource policy addressing these dynamics is ineffective without reliable land use land cover change data. The collective impact of harvest decisions by many small forest owners can be substantial at the landscape scale, yet monitoring harvests and regrowth in these forests is challenging. Remote sensing is an obvious route to detect and monitor small-scale land use dynamics over large areas. Using an annual series of Landsat-5 Thematic Mapper (TM) images and a GIS shapefile of property boundaries, we identified units where harvests occurred from 2005 to 2011 using an Object-Based Change Detection (OBCD) approach. Percent of basal area harvested was verified using stand-level harvest data. Our method detected all harvests above 20% basal area removal in all forest types (northern hardwoods, mixed deciduous/coniferous, coniferous), on properties as small as 10 acres (0.4 ha; approximately four Landsat pixels). Our results had a resolution of about 10% basal area (that is, a selective harvest removal of 30% could be distinguished from one of 40%). Our method can be automated and used to measure annual harvest rates and intensities for large areas of the United States, providing critical information on land use transition

Information and entropy theory for the sustainability of coupled human and natural systems

For coupled human and natural systems (CHANS), sustainability can be defined operationally as a feasible, desirable set of flows (material, currency, information, energy, individuals, etc.) that can be maintained despite internal changes and changes in the environment. Sustainable development can be defined as the process by which CHANS can be moved toward sustainability. Specific indicators that give insight into the structure and behavior of feedbacks in CHANS are of particular interest because they would aid in the sustainable management of these systems through an understanding of the structures that govern system behavior. However, the use of specific feedbacks as monitoring tools is rare, possibly because of uncertainties regarding the nature of their dynamics and the diversity of types of feedbacks encountered in these systems. An information theory perspective may help to rectify this situation, as evidenced by recent research in sustainability science that supports the use of unit-free measures such as Shannon entropy and Fisher information to aggregate disparate indicators. These measures have been used for spatial and temporal datasets to monitor progress toward sustainability targets. Here, we provide a review of information theory and a theoretical framework for studying the dynamics of feedbacks in CHANS. We propose a combination of information-based indices that might productively inform our sustainability goals, particularly when related to key feedbacks in CHANS

The hydrologic role of urban green space in mitigating flooding (Luohe, China)

Even if urban catchments are adequately drained by sewer infrastructures, flooding hotspots develop where ongoing development and poor coordination among utilities conspire with land use and land cover, drainage, and rainfall. We combined spatially explicit land use/land cover data from Luohe City (central China) with soil hydrology (as measured, green space hydraulic conductivity), topography, and observed chronic flooding to analyze the relationships between spatial patterns in pervious surface and flooding. When compared to spatial–structural metrics of land use/cover where flooding was commonly observed, we found that some areas expected to remain dry (given soil and elevation characteristics) still experienced localized flooding, indicating hotspots with overwhelmed sewer infrastructure and a lack of pervious surfaces to effectively infiltrate and drain rainfall. Next, we used curve numbers to represent the composite hydrology of different land use/covers within both chronic flooding and dry (non-flooding) circles of 750 m diameter, and local design storms to determine the anticipated average proportion of runoff. We found that dry circles were more permeable (curve number (mean ± std. error) = 74 ± 2, n = 25) than wetter, flooded circles (curve number = 87 ± 1). Given design storm forcing (20, 50, 100 years’ recurrence interval, and maximum anticipated storm depths), dry points would produce runoff of 26 to 35 percent rainfall, and wet points of 52 to 61 percent of applied rainfall. However, we estimate by simulation that runoff reduction benefits would decline once infiltration-excess (Hortonian) runoff mechanisms activate for storms with precipitation rates in excess of an average of 21 mm/h, contingent on antecedent moisture conditions. Our spatial metrics indicate that larger amounts and patches of dispersed green space mitigate flooding risk, while aggregating buildings (roofs) and green space into larger, separate areas exacerbates risk

Sustainability for shrinking cities

Shrinking cities are widespread throughout the world despite the rapidly increasing global urban population. These cities are attempting to transition to sustainable trajectories to improve the health and well-being of urban residents, to build their capacity to adapt to changing conditions and to cope with major events. The dynamics of shrinking cities are different than the dynamics of growing cities, and therefore intentional research and planning around creating sustainable cities is needed for shrinking cities. We propose research that can be applied to shrinking cities by identifying parallel challenges in growing cities and translating urban research and planning that is specific to each city’s dynamics. In addition, we offer applications of panarchy concepts to this problem. The contributions to this Special Issue take on this forward-looking planning task through drawing lessons for urban sustainability from shrinking cities, or translating general lessons from urban research to the context of shrinking cities

Assessing the ecosystem services of various types of urban green spaces based on i-Tree eco

Urban green spaces play a crucial role in maintaining urban ecosystem sustainability by providing numerous ecosystem services. How to quantify and evaluate the ecological benefits and services of urban green spaces remains a hot topic currently, while the evaluation is barely applied or implemented in urban design and planning. In this study, super-high-resolution aerial images were used to acquire the spatial distribution of urban green spaces; a modified pre-stratified random sampling method was applied to obtain the vegetation information of the four types of urban green spaces in Luohe, a common plain city in China; and i-Tree Eco model was further used to assess the vegetation structure and various ecosystem services including air quality improvement, rainfall interception, carbon storage, and sequestration provided by four types of urban green spaces. The modeling results reveal that there were about 1,006,251 trees in this area. In 2013, all the trees in these green spaces could store about 54,329 t of carbon, sequester about 4973 t of gross carbon, remove 92 t of air pollutants, and avoid 122,637 m3 of runoff. The study illustrates an innovative method to reveal different types of urban green spaces with distinct ecosystem service productivity capacity to better understand their various roles in regulating the urban environment. The results could be used to assist urban planners and policymakers to optimize urban green space structure and composition to maximize ecosystem services provision