Evaluating complementary networks of restoration plantings for landscape‐scale occurrence of temporally dynamic species

Multibillion dollar investments in land restoration make it critical that conservation goals are achieved cost‐effectively. Approaches developed for systematic conservation planning offer opportunities to evaluate landscape‐scale, temporally dynamic biodiversity outcomes from restoration and improve on traditional approaches that focus on the most species‐rich plantings. We investigated whether it is possible to apply a complementarity‐based approach to evaluate the extent to which an existing network of restoration plantings meets representation targets. Using a case study of woodland birds of conservation concern in southeastern Australia, we compared complementarity‐based selections of plantings based on temporally dynamic species occurrences with selections based on static species occurrences and selections based on ranking plantings by species richness. The dynamic complementarity approach, which incorporated species occurrences over 5 years, resulted in higher species occurrences and proportion of targets met compared with the static complementarity approach, in which species occurrences were taken at a single point in time. For equivalent cost, the dynamic complementarity approach also always resulted in higher average minimum percent occurrence of species maintained through time and a higher proportion of the bird community meeting representation targets compared with the species‐richness approach. Plantings selected under the complementarity approaches represented the full range of planting attributes, whereas those selected under the species‐richness approach were larger in size. Our results suggest that future restoration policy should not attempt to achieve all conservation goals within individual plantings, but should instead capitalize on restoration opportunities as they arise to achieve collective value of multiple plantings across the landscape. Networks of restoration plantings with complementary attributes of age, size, vegetation structure, and landscape context lead to considerably better outcomes than conventional restoration objectives of site‐scale species richness and are crucial for allocating restoration investment wisely to reach desired conservation goals.     

Assessing Risk to Birds from Industrial Wind Energy Development via Paired Resource Selection Models

When wildlife habitat overlaps with industrial development animals may be harmed. Because wildlife and people select resources to maximize biological fitness and economic return, respectively, we estimated risk, the probability of eagles encountering and being affected by turbines, by overlaying models of resource selection for each entity. This conceptual framework can be applied across multiple spatial scales to understand and mitigate impacts of industry on wildlife. We estimated risk to Golden Eagles (Aquila chrysaetos) from wind energy development in 3 topographically distinct regions of the central Appalachian Mountains of Pennsylvania (United States) based on models of resource selection of wind facilities (n = 43) and of northbound migrating eagles (n = 30). Risk to eagles from wind energy was greatest in the Ridge and Valley region; all 24 eagles that passed through that region used the highest risk landscapes at least once during low altitude flight. In contrast, only half of the birds that entered the Allegheny Plateau region used highest risk landscapes and none did in the Allegheny Mountains. Likewise, in the Allegheny Mountains, the majority of wind turbines (56%) were situated in poor eagle habitat; thus, risk to eagles is lower there than in the Ridge and Valley, where only 1% of turbines are in poor eagle habitat. Risk within individual facilities was extremely variable; on average, facilities had 11% (SD 23; range = 0–100%) of turbines in highest risk landscapes and 26% (SD 30; range = 0–85%) of turbines in the lowest risk landscapes. Our results provide a mechanism for relocating high‐risk turbines, and they show the feasibility of this novel and highly adaptable framework for managing risk of harm to wildlife from industrial development. Evaluación del Riesgo para las Aves por el Desarrollo de Energía Eólica Industrial Mediante Modelos de Selección de Recursos Pareados.     

Place‐based and data‐rich citizen science as a precursor for conservation action

Environmental education strategies have customarily placed substantial focus on enhancing ecological knowledge and literacy with the hope that, upon discovering relevant facts and concepts, participants will be better equipped to process and dissect environmental issues and, therefore, make more informed decisions. The assumption is that informed citizens will become active citizens––enthusiastically lobbying for, and participating in, conservation‐oriented action. We surveyed and interviewed and used performance data from 432 participants in the Coastal Observation and Seabird Survey Team (COASST), a scientifically rigorous citizen science program, to explore measurable change in and links between understanding and action. We found that participation in rigorous citizen science was associated with significant increases in participant knowledge and skills; a greater connection to place and, secondarily, to community; and an increasing awareness of the relative impact of anthropogenic activities on local ecosystems specifically through increasing scientific understanding of the ecosystem and factors affecting it. Our results suggest that a place‐based, data‐rich experience linked explicitly to local, regional, and global issues can lead to measurable change in individual and collective action, expressed in our case study principally through participation in citizen science and community action and communication of program results to personal acquaintances and elected officials. We propose the following tenets of conservation literacy based on emergent themes and the connections between them explicit in our data: place‐based learning creates personal meaning making; individual experience nested within collective (i.e., program‐wide) experience facilitates an understanding of the ecosystem process and function at local and regional scales; and science‐based meaning making creates informed concern (i.e., the ability to discern both natural and anthropogenic forcing), which allows individuals to develop a personalized prioritization schema and engage in conservation action.     

Enhancing Avifauna in Commercial Plantations

Abstract:  The occurrence of fauna in commercial plantations is often associated with structural complexity. Through a meta-analysis, we tested whether the structural complexity of plantations could enhance bird species assemblages and whether bird assemblages respond differently depending on taxonomic affiliation, body size, and diet. Our analyses included 167 case studies in 31 countries in which bird assemblages in forests and plantations were compared and 42 case studies in 14 countries in which bird assemblages in plantations of different structural complexity were compared. Species richness, but not abundance, was higher in forests than in plantations. Both species richness and abundance were significantly higher in complex than in structurally simple plantations. Taxonomic representation and body size did not differ between forest and plantations, except that there were fewer insectivorous birds in plantations than in forests. In the comparison of simple versus complex plantations, abundance of all taxonomic and dietary groups was higher in complex plantations. Body size did not affect bird species richness or abundance. Independent of the type of plantation, bird richness and abundance were greater in structurally complex plantations. Enhancing the structural complexity of plantations may mitigate their impact and offer habitat for some native species.     

Predicting species distributions from samples collected along roadsides

Predictive models of species distributions are typically developed with data collected along roads. Roadside sampling may provide a biased (nonrandom) sample; however, it is currently unknown whether roadside sampling limits the accuracy of predictions generated by species distribution models. We tested whether roadside sampling affects the accuracy of predictions generated by species distribution models by using a prospective sampling strategy designed specifically to address this issue. We built models from roadside data and validated model predictions at paired locations on unpaved roads and 200 m away from roads (off road), spatially and temporally independent from the data used for model building. We predicted species distributions of 15 bird species on the basis of point-count data from a landbird monitoring program in Montana and Idaho (U.S.A.). We used hierarchical occupancy models to account for imperfect detection. We expected predictions of species distributions derived from roadside-sampling data would be less accurate when validated with data from off-road sampling than when it was validated with data from roadside sampling and that model accuracy would be differentially affected by whether species were generalists, associated with edges, or associated with interior forest. Model performance measures (kappa, area under the curve of a receiver operating characteristic plot, and true skill statistic) did not differ between model predictions of roadside and off-road distributions of species. Furthermore, performance measures did not differ among edge, generalist, and interior species, despite a difference in vegetation structure along roadsides and off road and that 2 of the 15 species were more likely to occur along roadsides. If the range of environmental gradients is surveyed in roadside-sampling efforts, our results suggest that surveys along unpaved roads can be a valuable, unbiased source of information for species distribution models.     

Applying habitat and population-density models to land-cover time series to inform IUCN Red List assessments

The IUCN (International Union for Conservation of Nature) Red List categories and criteria are the most widely used framework for assessing the relative extinction risk of species. The criteria are based on quantitative thresholds relating to the size, trends, and structure of species’ distributions and populations. However, data on these parameters are sparse and uncertain for many species and unavailable for others, potentially leading to their misclassification or classification as data deficient. We devised an approach that combines data on land-cover change, species-specific habitat preferences, population abundance, and dispersal distance to estimate key parameters (extent of occurrence, maximum area of occupancy, population size and trend, and degree of fragmentation) and hence predict IUCN Red List categories for species. We applied our approach to nonpelagic birds and terrestrial mammals globally (∼15,000 species). The predicted categories were fairly consistent with published IUCN Red List assessments, but more optimistic overall. We predicted 4.2% of species (467 birds and 143 mammals) to be more threatened than currently assessed and 20.2% of data deficient species (10 birds and 114 mammals) to be at risk of extinction. Incorporating the habitat fragmentation subcriterion reduced these predictions 1.5–2.3% and 6.4–14.9% (depending on the quantitative definition of fragmentation) for threatened and data deficient species, respectively, highlighting the need for improved guidance for IUCN Red List assessors on the application of this aspect of the IUCN Red List criteria. Our approach complements traditional methods of estimating parameters for IUCN Red List assessments. Furthermore, it readily provides an early-warning system to identify species potentially warranting changes in their extinction-risk category based on periodic updates of land-cover information. Given our method relies on optimistic assumptions about species distribution and abundance, all species predicted to be more at risk than currently evaluated should be prioritized for reassessment.     

Road traffic and nearby grassland bird patterns in a suburbanizing landscape

An extensive road system with rapidly increasing traffic produces diverse ecological effects that cover a large land area. Our objective was to evaluate the effect of roads with different traffic volumes on surrounding avian distributions, and its importance relative to other variables. Grassland bird data (5 years) for 84 open patches in an outer suburban/rural landscape near Boston were analyzed relative to: distance from roads with 3000–8000 to >30,000 vehicles/day; open-habitat patch size; area of quality microhabitat within a patch; adjacent land use; and distance to other open patches. Grassland bird presence and regular breeding correlated significantly with both distance from road and habitat patch size. Distance to nearest other open patch, irrespective of size, was not significant. Similarly, except for one species, adjacent land use, in this case built area, was not significant. A light traffic volume of 3000–8000 vehicles/day (local collector street here) had no significant effect on grassland bird distribution. For moderate traffic of 8000–15,000 (through street), there was no effect on bird presence although regular breeding was reduced for 400 m from a road. For heavier traffic of 15,000–30,000 (two-lane highway), both bird presence and breeding were decreased for 700 m. For a heavy traffic volume of ≥30,000 vehicles/day (multilane highway), bird presence and breeding were reduced for 1200 m from a road. The results suggest that avian studies and long-term surveys near busy roads may be strongly affected by traffic volume or changes in volume. We conclude that road ecology, especially the effects extending outward >100 m from roads with traffic, is a sine qua non for effective land-use and transportation policy.     

Bioassessment of silvicultural impacts in streams and wetlands of the Eastern United States

Bioassessment is a useful tool to determine the impact of logging practices on the biological integrity of streams and wetlands. Measuring biota directly has an intuitive appeal for impact assessment, and biota can be superior indicators to physical or chemical characteristics because they can reflect cumulative impacts over time. Logging can affect stream and wetland biota by increasing sedimentation rates, altering hydrologic, thermal, and chemical regimes, and changing the base of food webs. Biotic impacts of logging on streams compared to wetlands probably differ, and in this paper we review some of those differences. In streams, invertebrates, fishes, amphibians, algae, and macrophytes have been used as indicators of logging impacts. In wetlands, bioassessment is just beginning to be used, and plants and birds are the most promising indicator taxa. Various best management practices (BMPs) have been developed to reduce the impacts of logging on stream and wetland biota, and we review quantitative studies that have evaluated the efficacy of some of these techniques in streams and wetlands in the eastern United States. Remarkably few studies that address the overall efficacy of BMPs in limiting biotic changes in streams and wetlands after BMP implementation have been published in scientific journals, although some work exists in reports or is unpublished. We review these works, and compile conclusions about BMP efficacy for biota from this body of research.     

Importance of landscape heterogeneity to wood storks in Florida Everglades

Declines in populations of and reproductive success of wood storks and other wading birds have occurred in the Florida Everglades over the past several decades. These declines have been concurrent with major changes in the Everglades’ landscape characteristics. Among the plausible hypotheses that relate to landscape change are the following: (1) general loss of habitat; (2) heavy loss of specific habitat, namely, short-hydroperiod wetlands that provide high prey availability early in the breeding season; and (3) an increase in frequency of major drying out of the central slough areas, which can affect prey availability late in the breeding season. These three hypotheses were compared using an individual-based model of wood stork (Mycteria americana) reproduction. This model simulated the behavior and energetics of each individual wood stork in a breeding colony on 15-min time intervals. Changes in water depth and prey availability occurred on daily time steps. Simulation results showed a threshold response in reproductive success to reduction of wetland heterogeneity. Model comparisons in which (1) only short-hydroperiod wetlands were removed and (2) wetlands of both long and short hydroperiods were removed showed that, for the same loss of total area, the specific habitat removal caused a much greater reduction in wood stork reproduction, indicating hypothesis 2 may be a more likely explanation than hypothesis 1. Reduction of initial prey availability in the central slough areas (simulating frequent drying; hypothesis 3) reduced fledging success by an average of more than 90% in the model.     

某万亩果园野生动物生态环境现状及改善措施研究

为了初步了解万亩果园湿地生态公园的野生动物种类及分布情况,采用线路调查为主,点面结合的方法对园内的野生动物展开调查.调查结果显示:该园中野生动物以鸟类为主,共有5目19科32种,且以雀形目为主.从食性来看,食虫鸟类最多,占万亩果园鸟类总数的53.1％.从居留型来看,鸟类以留鸟居多,共有28种,占总种数的87.5％.通过分析生态环境现状影响野生动物栖息的原因,提出了增加植被配置、设立相对封闭区域和加强农药使用管理的改善措施.