Defining the Impact of Non‐Native Species

Non‐native species cause changes in the ecosystems to which they are introduced. These changes, or some of them, are usually termed impacts; they can be manifold and potentially damaging to ecosystems and biodiversity. However, the impacts of most non‐native species are poorly understood, and a synthesis of available information is being hindered because authors often do not clearly define impact. We argue that explicitly defining the impact of non‐native species will promote progress toward a better understanding of the implications of changes to biodiversity and ecosystems caused by non‐native species; help disentangle which aspects of scientific debates about non‐native species are due to disparate definitions and which represent true scientific discord; and improve communication between scientists from different research disciplines and between scientists, managers, and policy makers. For these reasons and based on examples from the literature, we devised seven key questions that fall into 4 categories: directionality, classification and measurement, ecological or socio‐economic changes, and scale. These questions should help in formulating clear and practical definitions of impact to suit specific scientific, stakeholder, or legislative contexts. Definiendo el Impacto de las Especies No‐Nativas     

The value of virtual conferencing for ecology and conservation

The objectives of conservation science and dissemination of its research create a paradox: Conservation is about preserving the environment, yet scientists spread this message at conferences with heavy carbon footprints. Ecology and conservation science depend on global knowledge exchange—getting the best science to the places it is most needed. However, conference attendance from developed countries typically outweighs that from developing countries that are biodiversity and conservation hotspots. If any branch of science should be trying to maximize participation while minimizing carbon emissions, it is conservation. Virtual conferencing is common in other disciplines, such as education and humanities, but it is surprisingly underused in ecology and conservation. Adopting virtual conferencing entails a number of challenges, including logistics and unified acceptance, which we argue can be overcome through planning and technology. We examined 4 conference models: a pure‐virtual model and 3 hybrid hub‐and‐node models, where hubs stream content to local nodes. These models collectively aim to mitigate the logistical and administrative challenges of global knowledge transfer. Embracing virtual conferencing addresses 2 essential prerequisites of modern conferences: lowering carbon emissions and increasing accessibility for remote, time‐ and resource‐poor researchers, particularly those from developing countries.     

Motivations for Conserving Urban Biodiversity

Abstract: In a time of increasing urbanization, the fundamental value of conserving urban biodiversity remains controversial. How much of a fixed budget should be spent on conservation in urban versus nonurban landscapes? The answer should depend on the goals that drive our conservation actions, yet proponents of urban conservation often fail to specify the motivation for protecting urban biodiversity. This is an important shortcoming on several fronts, including a missed opportunity to make a stronger appeal to those who believe conservation biology should focus exclusively on more natural, wilder landscapes. We argue that urban areas do offer an important venue for conservation biology, but that we must become better at choosing and articulating our goals. We explored seven possible motivations for urban biodiversity conservation: preserving local biodiversity, creating stepping stones to nonurban habitat, understanding and facilitating responses to environmental change, conducting environmental education, providing ecosystem services, fulfilling ethical responsibilities, and improving human well‐being. To attain all these goals, challenges must be faced that are common to the urban environment, such as localized pollution, disruption of ecosystem structure, and limited availability of land. There are, however, also challenges specific only to particular goals, meaning that different goals will require different approaches and actions. This highlights the importance of specifying the motivations behind urban biodiversity conservation. If the goals are unknown, progress cannot be assessed.     

An Adaptive‐Management Framework for Optimal Control of Hiking Near Golden Eagle Nests in Denali National Park

Abstract: Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive‐management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.     

Mapping Change in Human Pressure Globally on Land and within Protected Areas

It is widely accepted that the main driver of the observed decline in biological diversity is increasing human pressure on Earth's ecosystems. However, the spatial patterns of change in human pressure and their relation to conservation efforts are less well known. We developed a spatially and temporally explicit map of global change in human pressure over 2 decades between 1990 and 2010 at a resolution of 10 km². We evaluated 22 spatial data sets representing different components of human pressure and used them to compile a temporal human pressure index (THPI) based on 3 data sets: human population density, land transformation, and electrical power infrastructure. We investigated how the THPI within protected areas was correlated to International Union for Conservation of Nature (IUCN) management categories and the human development index (HDI) and how the THPI was correlated to cumulative pressure on the basis of the original human footprint index. Since the early 1990s, human pressure increased 64% of the terrestrial areas; the largest increases were in Southeast Asia. Protected areas also exhibited overall increases in human pressure, the degree of which varied with location and IUCN management category. Only wilderness areas and natural monuments (management categories Ib and III) exhibited decreases in pressure. Protected areas not assigned any category exhibited the greatest increases. High HDI values correlated with greater reductions in pressure across protected areas, while increasing age of the protected area correlated with increases in pressure. Our analysis is an initial step toward mapping changes in human pressure on the natural world over time. That only 3 data sets could be included in our spatio‐temporal global pressure map highlights the challenge to measuring pressure changes over time. Mapeo del Cambio en la Presión Humana Global en Tierra y Dentro de Áreas Protegidas     

Large-sample-size assessment of socioeconomic predictors of community-level resource management occurrence

Community-level resource management efforts are cornerstones in ensuring sustainable use of natural resources. Yet, understanding how community characteristics influence management practices remains contested. With a sample size of ≥725 communities, we assessed the effects of key community (i.e., socioeconomic) characteristics (human population size and density, market integration, and modernization) on the probability of occurrence of fisheries management practices, including gear, species, and spatial restrictions. The study was based in Solomon Islands, a Pacific Island country with a population that is highly dependent on coastal fisheries. People primarily dwell in small communities adjacent to the coastline dispersed across 6 island provinces and numerous smaller islands. We used nationally collected data in binomial logistic regression models to examine the likelihood of management occurrence, given socioeconomic context of communities. In contrast to prevailing views, we identified a positive and statistically significant association between both human population size and market integration and all 3 management practices. Human population density, however, had a statistically significant negative association and modernization a varied and limited association with occurrence of all management practices. Our method offers a way to remotely predict the occurrence of resource management practices based on key socioeconomic characteristics. It could be used to improve understanding of why some communities conduct natural resource management activities when statistical patterns suggest they are not likely to and thus improve understanding of how some communities of people beat the odds despite limited market access and high population density.     

Improving protected area effectiveness through consideration of different human-pressure baselines

Previous assessments of the effectiveness of protected areas (PAs) focused primarily on changes in human pressure over time and did not consider the different human-pressure baselines of PAs, thereby potentially over- or underestimating PA effectiveness. We developed a framework that considers both human-pressure baseline and change in human pressure over time and assessed the effectiveness of 338 PAs in China from 2010 to 2020. The initial state of human pressure on PAs was taken as the baseline, and changes in human pressure index (HPI) were further analyzed under different baselines. We used the random forest models to identify the management measures that most improved effectiveness in resisting human pressure for the PAs with different baselines. Finally, the relationships between the changes in the HPI and the changes in natural ecosystems in PAs were analyzed with different baselines. Of PAs with low HPI baselines, medium HPI baselines, and high HPI baselines, 76.92% (n=150), 11.11% (n=12), and 22.86% (n=8) , respectively, showed positive effects in resisting human pressure. Overall, ignoring human-pressure baselines somewhat underestimated the positive effects of PAs, especially for those with low initial human pressure. For PAs with different initial human pressures, different management measures should be taken to improve effectiveness and reduce threats to natural ecosystems. We believe our framework is useful for assessing the effectiveness of PAs globally, and we recommend it be included in the Convention on Biological Diversity Post-2020 Strategy.     

Effects of spatial autocorrelation and sampling design on estimates of protected area effectiveness

Estimating the effectiveness of protected areas (PAs) in reducing deforestation is useful to support decisions on whether to invest in better management of areas already protected or to create new ones. Statistical matching is commonly used to assess this effectiveness, but spatial autocorrelation and regional differences in protection effectiveness are frequently overlooked. Using Colombia as a case study, we employed statistical matching to account for confounding factors in park location and accounted for for spatial autocorrelation to determine statistical significance. We compared the performance of different matching procedures—ways of generating matching pairs at different scales—in estimating PA effectiveness. Differences in matching procedures affected covariate similarity between matched pairs (balance) and estimates of PA effectiveness in reducing deforestation. Independent matching yielded the greatest balance. On average 95% of variables in each region were balanced with independent matching, whereas 33% of variables were balanced when using the method that performed worst. The best estimates suggested that average deforestation inside protected areas in Colombia was 40% lower than in matched sites. Protection significantly reduced deforestation, but PA effectiveness differed among regions. Protected areas in Caribe were the most effective, whereas those in Orinoco and Pacific were least effective. Our results demonstrate that accounting for spatial autocorrelation and using independent matching for each subset of data is needed to infer the effectiveness of protection in reducing deforestation. Not accounting for spatial autocorrelation can distort the assessment of protection effectiveness, increasing type I and II errors and inflating effect size. Our method allowed improved estimates of protection effectiveness across scales and under different conditions and can be applied to other regions to effectively assess PA performance.     

Assessment of Management to Mitigate Anthropogenic Effects on Large Whales

United States and Canadian governments have responded to legal requirements to reduce human‐induced whale mortality via vessel strikes and entanglement in fishing gear by implementing a suite of regulatory actions. We analyzed the spatial and temporal patterns of mortality of large whales in the Northwest Atlantic (23.5°N to 48.0°N), 1970 through 2009, in the context of management changes. We used a multinomial logistic model fitted by maximum likelihood to detect trends in cause‐specific mortalities with time. We compared the number of human‐caused mortalities with U.S. federally established levels of potential biological removal (i.e., species‐specific sustainable human‐caused mortality). From 1970 through 2009, 1762 mortalities (all known) and serious injuries (likely fatal) involved 8 species of large whales. We determined cause of death for 43% of all mortalities; of those, 67% (502) resulted from human interactions. Entanglement in fishing gear was the primary cause of death across all species (n = 323), followed by natural causes (n = 248) and vessel strikes (n = 171). Established sustainable levels of mortality were consistently exceeded in 2 species by up to 650%. Probabilities of entanglement and vessel‐strike mortality increased significantly from 1990 through 2009. There was no significant change in the local intensity of all or vessel‐strike mortalities before and after 2003, the year after which numerous mitigation efforts were enacted. So far, regulatory efforts have not reduced the lethal effects of human activities to large whales on a population‐range basis, although we do not exclude the possibility of success of targeted measures for specific local habitats that were not within the resolution of our analyses. It is unclear how shortfalls in management design or compliance relate to our findings. Analyses such as the one we conducted are crucial in critically evaluating wildlife‐management decisions. The results of these analyses can provide managers with direction for modifying regulated measures and can be applied globally to mortality‐driven conservation issues. Evaluación del Manejo para Mitigar Efectos Antropogénicos sobre Ballenas Mayores     

Coupling urban 3-D information and circuit theory to advance the development of urban ecological networks

Ongoing, rapid urban growth accompanied by habitat fragmentation and loss challenges biodiversity conservation and leads to decreases in ecosystem services. Application of the concept of ecological networks in the preservation and restoration of connections among isolated patches of natural areas is a powerful conservation strategy. However, previous approaches often failed to objectively consider the impacts of complex 3-D city environments on ecological niches. We used airborne lidar-derived information on the 3-D structure of the built environment and vegetation and detailed land use and cover data to characterize habitat quality, niche diversity, and human disturbance and to predict habitat connectivity among 38 identified habitat core areas (HCAs) in Nanjing, China. We used circuit theory and Linkage Mapper to create a landscape resistance layer, simulate habitat connectivity, and identify and prioritize important corridors. We mapped 64 links by using current flow centrality to evaluate each HCA's contribution and the links that facilitate intact connectivity. Values were highest for HCA links located in the west, south, and northeast of the study area, where natural forests with complex 3-D structures predominate. Two smaller HCA areas had high centrality scores relative to their extents, which means they could act as important stepping stones in connectivity planning. The mapped pinch-point regions had narrow and fragile links among the HCAs, suggesting they require special protection. The barriers with the highest impact scores were mainly located at the HCA connections to Purple Mountain and, based on these high scores, are more likely to indicate important locations that can be restored to improve potential connections. Our novel framework allowed us to sufficiently convey spatially explicit information to identify targets for habitat restoration and potential pathways for species movement and dispersal. Such information is critical for assessing existing or potential habitats and corridors and developing strategic plans to balance habitat conservation and other land uses based on scientifically informed connectivity planning and implementation.