Energy profiles of an agricultural frontier: the American Great Plains, 1860–2000

Regional Environmental Change - Agro-ecosystem energy profiles reveal energy flows into, within, and out of US Great Plains farm communities across 140 years. This study evaluates external...     

A Modeling System to Assess Land Cover Land Use Change Effects on SAV Habitat in the Mobile Bay Estuary

Estuarine ecosystems are largely influenced by watersheds directly connected to them. In the Mobile Bay, Alabama watersheds we examined the effect of land cover and land use (LCLU) changes on discharge rate, water properties, and submerged aquatic vegetation, including freshwater macrophytes and seagrasses, throughout the estuary. LCLU scenarios from 1948, 1992, 2001, and 2030 were used to influence watershed and hydrodynamic models and evaluate the impact of LCLU change on shallow aquatic ecosystems. Overall, our modeling results found that LCLU changes increased freshwater flows into Mobile Bay altering temperature, salinity, and total suspended sediments (TSS). Increased urban land uses coupled with decreased agricultural/pasture lands reduced TSS in the water column. However, increased urbanization or agricultural/pasture land coupled with decreased forest land resulted in higher TSS concentrations. Higher sediment loads were usually strongly correlated with higher TSS levels, except in areas where a large extent of wetlands retained sediment discharged during rainfall events. The modeling results indicated improved water clarity in the shallow aquatic regions of Mississippi Sound and degraded water clarity in the Wolf Bay estuary. This integrated modeling approach will provide new knowledge and tools for coastal resource managers to manage shallow aquatic habitats that provide critical ecosystem services.     

Effects of productivity on biodiversity in forest ecosystems across the United States and China

In the global campaign against biodiversity loss in forest ecosystems, land managers need to know the status of forest biodiversity, but practical guidelines for conserving biodiversity in forest management are lacking. A major obstacle is the incomplete understanding of the relationship between site primary productivity and plant diversity, due to insufficient ecosystem‐wide data, especially for taxonomically and structurally diverse forest ecosystems. We investigated the effects of site productivity (the site's inherent capacity to grow timber) on tree species richness across 19 types of forest ecosystems in North America and China through 3 ground‐sourced forest inventory data sets (U.S. Forest Inventory and Analysis, Cooperative Alaska Forest Inventory, and Chinese Forest Management Planning Inventory). All forest types conformed to a consistent and highly significant (P < 0.001) hump‐shaped unimodal relationship, of which the generalized coefficients of determination averaged 20.5% over all the forest types. That is, tree species richness first increased as productivity increased at a progressively slower rate, and, after reaching a maximum, richness started to decline. Our consistent findings suggest that forests of high productivity would sustain few species because they consist mostly of flat homogeneous areas lacking an environmental gradient along which a diversity of species with different habitats can coexist. The consistency of the productivity–biodiversity relationship among the 3 data sets we examined makes it possible to quantify the expected tree species richness that a forest stand is capable of sustaining, and a comparison between the actual species richness and the sustainable values can be useful in prioritizing conservation efforts.     

Toward reassessing data‐deficient species

One in 6 species (13,465 species) on the International Union for Conservation of Nature (IUCN) Red List is classified as data deficient due to lack of information on their taxonomy, population status, or impact of threats. Despite the chance that many are at high risk of extinction, data‐deficient species are typically excluded from global and local conservation priorities, as well as funding schemes. The number of data‐deficient species will greatly increase as the IUCN Red List becomes more inclusive of poorly known and speciose groups. A strategic approach is urgently needed to enhance the conservation value of data‐deficient assessments. To develop this, we reviewed 2879 data‐deficient assessments in 6 animal groups and identified 8 main justifications for assigning data‐deficient status (type series, few records, old records, uncertain provenance, uncertain population status or distribution, uncertain threats, taxonomic uncertainty, and new species). Assigning a consistent set of justification tags (i.e., consistent assignment to assessment justifications) to species classified as data deficient is a simple way to achieve more strategic assessments. Such tags would clarify the causes of data deficiency; facilitate the prediction of extinction risk; facilitate comparisons of data deficiency among taxonomic groups; and help prioritize species for reassessment. With renewed efforts, it could be straightforward to prevent thousands of data‐deficient species slipping unnoticed toward extinction.     

Exploring the risks and benefits of flexibility in biodiversity offset location in a case study of migratory shorebirds

Biodiversity offsets aim to counterbalance the residual impacts of development on species and ecosystems. Guidance documents explicitly recommend that biodiversity offset actions be located close to the location of impact because of higher potential for similar ecological conditions, but allowing greater spatial flexibility has been proposed. We examined the circumstances under which offsets distant from the impact location could be more likely to achieve no net loss or provide better ecological outcomes than offsets close to the impact area. We applied a graphical model for migratory shorebirds in the East Asian–Australasian Flyway as a case study to explore the problems that arise when incorporating spatial flexibility into offset planning. Spatially flexible offsets may alleviate impacts more effectively than local offsets; however, the risks involved can be substantial. For our case study, there were inadequate data to make robust conclusions about the effectiveness and equivalence of distant habitat-based offsets for migratory shorebirds. Decisions around offset placement should be driven by the potential to achieve equivalent ecological outcomes; however, when considering more distant offsets, there is a need to evaluate the likely increased risks alongside the potential benefits. Although spatially flexible offsets have the potential to provide more cost-effective biodiversity outcomes and more cobenefits, our case study showed the difficulty of demonstrating these benefits in practice and the potential risks that need to be considered to ensure effective offset placement.     

Incorporating low-resolution historic species location data decreases performance of distribution models

Developing robust species distribution models is important as model outputs are increasingly being incorporated into conservation policy and management decisions. A largely overlooked component of model assessment and refinement is whether to include historic species occurrence data in distribution models to increase the data sample size. Data of different temporal provenance often differ in spatial accuracy and precision. We test the effect of inclusion of historic coarse-resolution occurrence data on distribution model outputs for 187 species of birds in Australian tropical savannas. Models using only recent (after 1990), fine-resolution data had significantly higher model performance scores measured with area under the receiver operating characteristic curve (AUC) than models incorporating both fine- and coarse-resolution data. The drop in AUC score is positively correlated with the total area predicted to be suitable for the species (R² = 0.163-0.187, depending on the environmental predictors in the model), as coarser data generally leads to greater predicted areas. The remaining unexplained variation is likely to be due to the covariate errors resulting from resolution mismatch between species records and environmental predictors. We conclude that decisions regarding data use in species distribution models must be conscious of the variation in predictions that mixed-scale datasets might cause.     

Defending the scientific integrity of conservation‐policy processes

Government agencies faced with politically controversial decisions often discount or ignore scientific information, whether from agency staff or nongovernmental scientists. Recent developments in scientific integrity (the ability to perform, use, communicate, and publish science free from censorship or political interference) in Canada, Australia, and the United States demonstrate a similar trajectory. A perceived increase in scientific‐integrity abuses provokes concerted pressure by the scientific community, leading to efforts to improve scientific‐integrity protections under a new administration. However, protections are often inconsistently applied and are at risk of reversal under administrations publicly hostile to evidence‐based policy. We compared recent challenges to scientific integrity to determine what aspects of scientific input into conservation policy are most at risk of political distortion and what can be done to strengthen safeguards against such abuses. To ensure the integrity of outbound communications from government scientists to the public, we suggest governments strengthen scientific integrity policies, include scientists’ right to speak freely in collective‐bargaining agreements, guarantee public access to scientific information, and strengthen agency culture supporting scientific integrity. To ensure the transparency and integrity with which information from nongovernmental scientists (e.g., submitted comments or formal policy reviews) informs the policy process, we suggest governments broaden the scope of independent reviews, ensure greater diversity of expert input and transparency regarding conflicts of interest, require a substantive response to input from agencies, and engage proactively with scientific societies. For their part, scientists and scientific societies have a responsibility to engage with the public to affirm that science is a crucial resource for developing evidence‐based policy and regulations in the public interest.     

How Green is Too Green? Public Opinion of What Constitutes Undesirable Algae Levels in Streams1

Abstract: A public opinion survey was carried out in Montana to ascertain if the public identifies a level of benthic (bottom‐attached) river and stream algae that is undesirable for recreation. The survey had two parts; an On‐River survey and a By‐Mail survey. The On‐River survey was conducted via 44 trips randomly scheduled throughout the state during which recreators were interviewed in‐person at the stream. Selection of stream segments and survey dates/times was based on known, statewide recreational use patterns. By‐Mail survey forms were sent to 2,000 individuals randomly selected from Montana’s Centralized Voter File (CVF) available from the Montana Secretary of State. The CVF was current through 2004 and represented over 85% of the state’s eligible voting population. In both surveys, eight randomly ordered photographs depicting varying levels of stream benthic algae were presented, and participants were asked if the algae level shown was desirable or undesirable for recreation. Survey form design, selection of photographs, and pretesting followed acceptable protocols that limited unintentional bias through survey execution. There were 433 returned forms (389 complete) for the By‐Mail survey, while the On‐River survey documented 563 interviews. In both surveys, as benthic algal chlorophyll a (Chl a) levels increased, desirability for recreation decreased. (Other measures of benthic algae biomass are presented as well.) For the public majority, mean benthic Chl a levels ≥200 mg/m² were determined to be undesirable for recreation, whereas mean levels ≤150 mg Chl a/m² were found to be desirable. Error rates were within the survey’s statistical design criteria (≤5%). The largest potential error source was nonresponse in the By‐Mail survey; however, the population represented by nonrespondents would have to exhibit profoundly different perceptions of river and stream algae to meaningfully alter the results. Results support earlier work in the literature suggesting 150 mg Chl a/m² represents a benthic algae nuisance threshold.