Inform Management Decisions Research Articles

Community-specific “desired” states for seagrasses through cycles of loss and recovery

Seagrass habitats provide critical ecosystem services, yet there is ongoing concern over mounting pressures and continuing degradation. Defining a desired state for these habitats is a key step in implementing appropriate management but is often difficult given the challenges of available data and an evaluation of where to set benchmarks. We use more than 20 years of historical seagrass biomass data (1995–2018) for the diverse seagrass communities of Australia's Great Barrier Reef World Heritage Area (GBRWHA) to develop desired state benchmarks. Desired state for seagrass biomass was estimated for 25 of 36 previously defined seagrass communities with the remainder having insufficient data. Desired state varied by more than one order of magnitude between community types and was influenced by the mix of species in the communities and the range of environmental conditions. We identify a historical, decadal-scale cycle of decline with recovery to desired state in coastal intertidal communities. In contrast a number of the estuary and coastal subtidal communities have not recovered to desired state biomass. Understanding a historical context is critically important for setting benchmarks and making informed management decisions on the present state of seagrass in the GBRWHA. The approach we have developed is scalable for monitoring, management and assessment of pressures for other management areas and for other jurisdictions. Our results guide conservation planning through prioritization of the at-risk seagrass communities that are continuing to fall below their desired state.

Development and Structural Organization of Mexico’s Mangrove Monitoring System (SMMM) as a Foundation for Conservation and Restoration Initiatives: A Hierarchical Approach

Mangroves provide ecosystem services worth billions of dollars worldwide. Although countries with extensive mangrove areas implemented management and conservation programs since the 1980s, the global area is still decreasing. To recuperate this lost area, both restoration and rehabilitation (R/R) projects have been implemented but with limited success, especially at spatial scales needed to restore functional properties. Monitoring mangroves at different spatial scales in the long term (decades) is critical to detect potential threats and select cost-effective management criteria and performance measures to improve R/R program success. Here, we analyze the origin, development, implementation, and outcomes of a country-level mangrove monitoring system in the Neotropics covering >9000 km2 over 15 years. The Mexico’s Mangrove Monitoring System (SMMM) considers a spatiotemporal hierarchical approach as a conceptual framework where remote sensing is a key component. We analyze the role of the SMMM’s remote sensing products as a “hub” of multi- and interdisciplinary ecological and social-ecological studies to develop national priorities and inform local and regional mangrove management decisions. We propose that the SMMM products, outcomes, and lessons learned can be used as a blueprint in other developing countries where cost-effective R/R projects are planned as part of mangrove protection, conservation, and management programs.

Spatial and temporal variations of microplastic concentrations in Portland's freshwater ecosystems

While microplastics are a pollutant of growing concern in various environmental compartments, less is known regarding the sources and delivery pathways of microplastics in urban rivers. We investigated the relationship between microplastic concentrations and various spatiotemporal factors (e.g., land use, arterial road length, water velocity, precipitation) in two watersheds along an urban-rural gradient in the Portland metropolitan area. Samples were collected in August, September, and February and were analyzed for total microplastic count and type. Nonparametric statistics were used to evaluate potential relationships with the explanatory variables, derived at both the subwatershed and near stream scales. In August, microplastic concentrations were significantly higher than in February. August concentrations also negatively correlated with flow rate, suggesting that lower flow rates may have facilitated the accumulation of microplastics. Smaller size microplastic particles (< 100 μm) were found more in August than September and February, while larger size particles were more dominant in February than the other months. Microplastic concentrations were positively related to 24-h antecedent precipitation in February. Negative correlations existed between wet season microplastic concentrations and agricultural lands at the near stream level. The results indicate that near stream variables may more strongly influence the presence and abundance of microplastics in Portland's waterways than subwatershed-scale variables. Fragments were the most commonly observed microplastic morphology, with a dominance of gray particles and the polymer polyethylene. The findings of this study can inform management decisions regarding microplastic waste and identify hotspots of microplastic pollution that may benefit from remediation.

A protocol for screening potentially invasive non-native species using Weed Risk Assessment-type decision-support tools

There is increasing use worldwide of electronic decision-support tools to identify potentially invasive non-native species so as to inform policy and management decisions aimed at preventing or mitigating the environmental and socio-economic impacts of biological invasions. This study reviews the analytical approaches used to calibrate scores generated by the Weed Risk Assessment and subsequent adaptations thereof and provides a protocol for: (i) the identification of the assessor(s) who will carry out the screenings; (ii) the definition of the risk assessment area; (iii) the criteria for selection of the species for screening; and (iv) the a priori categorisation of the species into invasive or non-invasive necessary to compute the thresholds by which to distinguish between high-risk and medium-risk non-native species. This analytical approach represents an evidence-based and statistically robust means with which to inform decision-makers and stakeholders about policy and management of potentially invasive species and is expected to serve as a general reference of forthcoming screening applications of Weed Risk Assessment-type toolkits.

Life in the slow lane: field metabolic rate and prey consumption rate of the Greenland shark (Somniosus microcephalus) modelled using archival biologgers.

Field metabolic rate (FMR) is a holistic measure of metabolism representing the routine energy utilization of a species living within a specific ecological context, thus providing insight into its ecology, fitness and resilience to environmental stressors. For animals that cannot be easily observed in the wild, FMR can also be used in concert with dietary data to quantitatively assess their role as consumers, improving understanding of the trophic linkages that structure food webs and allowing for informed management decisions. Here, we modelled the FMR of Greenland sharks (Somniosus microcephalus) equipped with biologger packages or pop-up archival satellite tags (PSATs) in two coastal inlets of Baffin Island (Nunavut) using metabolic scaling relationships for mass, temperature and activity. We estimated that Greenland sharks had an overall mean (±s.d.) FMR of 21.67±2.30 mg O2 h-1 kg-0.84 (n=30; 1-4 day accelerometer package deployments) while residing inside these cold-water fjord systems in the late summer, and 25.48±0.47 mg O2 h-1 kg-0.84 (n=6; PSATs) over an entire year. When considering prey consumption rate, an average shark in these systems (224 kg) requires a maintenance ration of 61-193 g of fish or marine mammal prey daily. As Greenland sharks are a lethargic polar species, these low FMR estimates, and corresponding prey consumption estimates, suggest they require very little energy to sustain themselves under natural conditions. These data provide the first characterization of the energetics and consumer role of this vulnerable and understudied species in the wild, which is essential given growing pressures from climate change and expanding commercial fisheries in the Arctic.

Strategy lessons from a new clinical trial in psoriatic arthritis.

Treatment guidelines for psoriatic arthritis are limited by a paucity of strategy studies to inform management decisions as well as an absence of consensus on treatment goals. Few studies providing quality data exist to guide advanced therapy (eg, changes in treatment regimen and the use of combination regimens) among individuals for whom initial treatment has been unsuccessful. Clinical management of individuals with psoriatic arthritis is complicated by different treatment guidelines proposed by the American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR).

Интегральная оценка результативности предоставления государственных услуг

The article provides a comprehensive analysis of key indicators characterizing the effectiveness of the provision of public services in the field of promoting employment in the Krasnodar Territory. The used methodological approach to the calculation of the integral indicator made it possible to increase the validity, transparency and verifiability of the assessment results, which is a serious contribution to the formation of a sustainable platform for making informed management decisions by the public administration sector.

Deriving moderate spatial resolution leaf area index estimates from coarser spatial resolution satellite products

Leaf Area Index (LAI) is a key parameter used to characterize vegetation biophysical properties and plays an important regulatory role in terrestrial-atmospheric exchanges. Subsequently, LAI is often a critical data input to various evapotranspiration, hydrological and climatic models. While LAI data can generally be easily obtained, it is seldom available at spatio-temporal scales that can be used to guide and inform management decisions for localised applications. To this end, we propose a methodology to acquire moderate resolution LAI (LAIMR) estimates from freely available satellite-earth observation data sets and data processing platforms. Fifteen sites distributed within the KwaZulu-Natal and Mpumalanga provinces of South Africa were selected as study areas. Coarse spatial resolution MODIS LAI and vegetation index (VI) products were acquired for each of these sites to establish the LAI-VI relationship which was then used to develop machine learning-based models (MLBMs) to estimate LAIMR using VIs derived from Landsat or Sentinel-2 data. During the validation and testing phases of the study, LAI estimates were compared against the corresponding MODIS LAI product values. The results of these investigations demonstrated that MLBMs performed satisfactorily across the majority of the study sites, producing correlation coefficients ranging from 0.62 to 0.97 and 0.29–0.84 for the validation and testing phases, respectively. The poorer performance of the MLBMs when using VIs derived from Landsat or Sentinel-2 data can be largely attributed to inherent limitations associated with the proposed methodology, such as i) the lack of moderate-high spatial resolution LAI records that could be used for training and testing purposes and ii) saturation effects associated with the use of VIs. Notwithstanding these limitations, the proposed methodology has been shown to be flexible and robust and can be a useful approach to acquire LAIMR estimates with fairly reasonable accuracy in data limited circumstances.

Sampling Methods and Survey Designs for Larval Lampreys

AbstractKnowledge of the biology, distribution, and abundance of lampreys (Petromyzontiformes) is critical to inform conservation actions for native species and to inform control measures for the invasive Sea Lamprey Petromyzon marinus of the Laurentian Great Lakes. Lampreys have complex life cycles that include a freshwater larval stage in which they burrow into substrates consisting of fine sediment and organic matter. The larval stage is frequently targeted in research and monitoring; given this interest, a review of survey designs and methods is needed. Our review identified 12 different sampling methods for larval lampreys and focused on one common method—backpack electrofishing in wadeable habitats. Our review also identified eight research and monitoring questions that have been addressed for larval lampreys in field studies, including distribution, species identification, life stage occurrence, abundance, length frequency, habitat use, residence and movement phenology, and species status. Each question provides unique information and poses distinct challenges to data acquisition and interpretation. The objectives guide decisions about study design and scope of inference. The scope of inference is determined by the size, spatial distribution, selection method, and number of sampling units within and across habitats, which determine the spatial and temporal scales under which results can be interpreted. The sampling unit size can span orders of magnitude from microhabitats to river drainages, ultimately informing management decisions at several spatial scales. The intended scope of inference and the interaction between biological questions and the fiscal and logistical capabilities of the study are integral considerations when designing an effective larval lamprey survey.

Synthesizing integrated ecosystem research to create informed stock-specific indicators for next generation stock assessments

Over the past two decades, numerous ecosystem surveys and process studies have emerged to monitor and assess the large marine ecosystems of Alaska. Several regional collaborative integrated ecosystem research projects (IERPs) were conducted to gain understanding of fish population fluctuations in relation to the surrounding environment. The Gulf of Alaska (GOA) IERP is one example of such an effort. Products of this program include a suite of in situ observations from fully integrated ecosystem surveys, laboratory experiments of physical thresholds for fish condition, and high-resolution oceanographic, planktonic, and habitat distribution models. When coupled, the synthesis products of this program can be utilized to understand system connectivity and highlight the primary ecosystem drivers of the GOA. Much of this information was included in annual GOA ecosystem status reports through individual indicator contributions. However, assimilation of these data into single-species stock assessments has remained limited. We provide a clear and direct avenue for including the products of these IERPs through the new ecosystem and socioeconomic profile (ESP) framework that identifies mechanistic relationships and tests ecosystem linkages within the stock assessment process. We present a case study using a data synthesis of the five commercially and ecologically valuable focal species of the GOAIERP (sablefish, pollock, Pacific cod, arrowtooth flounder, and Pacific ocean perch). Information was organized along the categories of distribution, phenology, and condition by life history stage to develop life history narratives for each species. These narratives identified critical ecosystem processes that could impact survival of each species. We then used habitat distribution models, seasonal phenology, and energy allocation strategies to sequentially reduce two gridded temperature datasets to reflect the life experience of the stock. This method essentially aligns ecosystem information at a spatial and temporal scale relevant to a stock and creates informed indicators that could then be related to a stock assessment parameter of interest, such as recruitment. Informed temperature indicators differed in magnitude and variability when compared to non-informed indicators and demonstrating species and stage-specific thermal preferences. The difference between the informed indicators and the non-informed indicators can also highlight thresholds and trends in habitat preference that could be further investigated with targeted process studies or laboratory experiments. The coordinated nature of the IERP allowed for the creation of these informed indicators that would not be possible with the results of any one process study. Both the stock-specific narratives and the informed indicators can be included into the ESPs for further monitoring and development. This integration ensures that the identified ecosystem linkages are evaluated concurrently with the stock assessment and ultimately transferred to fishery managers in an efficient and effective format for informing management decisions.

The Influence of Leader-member Exchange on Employee Task Performance in Coal Enterprises: A Study from the Perspective of Conservation of Resources Theory

Purpose: Ensuring high levels of employee performance is critical in the coal industry, in light of disruptions caused by clean energy industries and consequent increased competitiveness in the energy market. Therefore, this study investigated the relationship between leader-member exchange (LMX), job embeddedness, and task performance in the context of the Chinese coal industry. Methodology: Employees of a coal enterprise in China, selected via random cluster samplings, completed a survey on site. Based on the data of 202 employees, we used correlation analysis to explore relationships between variables. We used a regression analysis to study the influence of LMX relationships and job embeddedness on task performance and a structural equation model to analyze the mediating role of job embeddedness. Findings: Based on the Conservation of Resources Theory, among the three factors of the LMX relationship, task performance, and job embeddedness in coal enterprises, any two of them correlated positively and significantly with each other; The LMX relationship here had a significant and positive prediction effect on the task performance of employees in coal enterprises. Job embeddedness also significantly and positively predicted task performance and played a significant mediating role between LMX relationships and task performance. Our findings can inform management decisions in the coal industry, help enterprises determine their position in the market, and enhance the performance level of employees. Originality: Few studies address the relationship between LMX, job embeddedness, and task performance in Chinese coal enterprises.

Estimating Species-Specific Stem Size Distributions of Uneven-Aged Mixed Deciduous Forests Using ALS Data and Neural Networks

Sustainable forest management requires accurate fine-scale description of wood resources. Stem size distribution (SSD) by species is used by foresters worldwide as a representative overview of forest structure and species composition suitable for informing management decisions at shorter and longer terms. In mixed uneven-aged deciduous forests, tree data required for SSD estimation are most often collected in the field through traditional forest management inventories (FMIs), but these are time-consuming and costly with respect to the sampled area. Combining FMIs with remote sensing methods such as airborne laser scanning (ALS), which has high potential for predicting forest structure and composition, and is becoming increasingly accessible and affordable, could provide cheaper and faster SSD data across large areas. In this study, we developed a method for estimating species-specific SSDs by combining FMIs and dual-wavelength ALS data using neural networks (NNs). The proposed method was tested and validated using 178 FMI plots within 22,000 ha of a mixed uneven-aged deciduous forest in Belgium. The forest canopy was segmented, and metrics were derived from the ALS point cloud. A NN with a custom architecture was set up to simultaneously predict the three components required to compute species-specific SSDs (species, circumference, and number of stems) at segment level. Species-specific SSDs were thereafter estimated at stand level by aggregating the estimates for the segments. A robustness test was set up using fully independent plots to thoroughly assess the method precision at stand-level on a larger area. The global Reynolds index for the species-specific SSDs was 21.2 for the training dataset and 54.0 for the independent dataset. The proposed method does not require allometric models, prior knowledge of the structure, or the predefinition of variables; it is versatile and thus potentially adaptable to other forest types having different structures and compositions.

Urine and fecal excretion patterns of dairy cows divergent for milk urea nitrogen breeding values consuming either a plantain or ryegrass diet

Environmental degradation has been attributed to inefficient nitrogen utilization from pastoral dairy production systems. This degradation has especially been associated with the urine patch, which has been identified as a key component of nitrate leaching to waterways. However, a lack of information exists regarding the pattern of urination events and individual urination characteristics across the day, which would help inform strategic management decisions. The aim of this study was therefore to evaluate and report the patterns and characteristics of fecal and urination events throughout the day for cows divergent for milk urea nitrogen breeding values (MUNBV) on either a plantain [Plantago lanceolata L. (PL)] or ryegrass [Lolium perenne L. (RG)] diet as ways to reduce environmental impact. Sixteen multiparous lactating Holstein Friesian × Jersey cows divergent for MUNBV were housed in metabolism crates for 72 h, with all excretion events captured and analyzed. Cows selected as low for MUNBV consistently had a 65.2-kg lower urinary urea nitrogen (UUN) load (kg/ha) than high MUNBV cows for all hours of the day when consuming RG. The association between lower urinary urea loading rates and less N leaching implies a reduced environmental impact from low MUNBV cows consuming RG. When cows consumed PL, regardless of MUNBV, they had on average a 137.5-kg (UUN/ha) lower loading rate compared with high MUNBV cows on RG and a 72.2-kg (UUN/ha) lower loading rate compared with low MUNBV cows consuming RG across the day. Cows on PL also exhibited a different diel pattern of UUN load compared with cows consuming RG. Differences in the diel pattern of N excreted in feces were also detected based on MUNBV and by diet, with low MUNBV cows excreting on average 3.06 g more N in feces per event for the majority of the day compared with high MUNBV cows when consuming RG. Lower UUN loading rates and more N excreted in feces indicate a potentially lower environmental impact from low MUNBV cows when consuming RG compared with high MUNBV cows. The use of the PL diet also resulted in lower UUN loading rates and greater levels of N excreted in feces compared with RG, therefore also indicating its ability to reduce environmental impact compared with RG.

Volunteer engagement in urban forestry in the United States: reviewing the literature

ABSTRACT This article presents the results of a literature review related to volunteerism in urban forestry in the United States. Themes explored were inductively emergent from the research reviewed and included ‘volunteer demographics’, ‘motivations of volunteers’, ‘benefits of volunteering’, ‘volunteer engagement and barriers’, ‘value of volunteering’, and ‘volunteer recruitment and retention’. Urban forestry volunteers are often motivated by personal, social, and environmental considerations. Volunteers in urban forestry may not be representative of a cross-section of the communities that they are serving, rather they are often middle-aged, well-educated white women. Further research is required both to ascertain barriers to volunteerism and to enhance future volunteer recruitment and retainment efforts. Volunteers in the United States account for 5% of municipal tree care in urban forests – accounting for an estimated $35 million USD in value. Volunteers perform critical urban forestry-related tasks that aim to increase urban tree canopy cover through tree selection and planting efforts. Volunteers encourage urban tree survival by advocating for, as well as performing, important maintenance-related duties including the administration of supplemental watering and urban tree pruning. With proper training and support, volunteers may accurately perform important data collection efforts that may inform management decisions and urban tree care maintenance programmes.

Influence of toileting behavior on the natural course of anterior vaginal wall prolapse

BackgroundMany risk factors for pelvic organ prolapse (POP) have been proposed, and the cause is most likely multifactorial. This study aimed to investigate the effect of toileting behaviors on the natural course of anterior vaginal wall prolapse (AVWP).MethodsData on 75 women who underwent surgery for symptomatic AVWP were collected. Patients with grade ≥ II AVWP were included in this study and were divided into two groups according to their voiding and defecation position. The volunteers who voided and defecated in a sitting position comprised Group 1, and those who voided and defecated in a squatting position comprised Group 2. The Colorectal-Anal Impact Questionnaire (CRAIQ), Pelvic Floor Impact Questionnaire (PFIQ), Pelvic Organ Prolapse Impact Questionnaire (POPIQ), Urinary Impact Questionnaire (UIQ) and visual analog scale (VAS) pain scores were used to evaluate the patients’ symptoms.ResultsForty-four patients were included in Group 1 (sitting position), and 31 patients were included in Group 2 (squatting position). The groups were similar in terms of BMI, parity, menopause duration, topical estrogen use, comorbidities, the presence of constipation and urinary incontinence, and the pad count for incontinence. The time from initial symptoms to surgery was shorter in Group 2 than in Group 1 12 (3–73) and 24 (2–182) months (p = 0.001), respectively. The PFIQ, POPIQ and POP-related VAS scores were significantly higher in patients who voided and defecated in a squatting position.ConclusionIn patients with symptomatic POP, increased IAP while performing the squat position during defecation and voiding may increase the severity of patients' symptoms related to prolapse more than that of sitting position. Therefore, questioning the toileting position of patients with AVWP may help inform management decisions, with changing to a sitting position encouraged.

Моделирование нарративного управления в социально-экономических системах

The article considers approaches to modeling management process in socio-economic systems. A management model is proposed, in which goal-setting is considered as a dynamic process that forms the controlled development of a socio-economic system at all stages of its life cycle. Goal achievement is understood as the activity of management process participants for achieving a given general goal in a dynamically formed goal space. Management is modeled as a trade-off between goal setting and goal achievement, the ultimate goal of which is ensuring the existence of the system and the fulfillment of its mission, assigned by the system environment. The fulfillment of the system mission in the context of its continuous interaction with the environment requires continuous collecting and processing data on the current state of the system and its environment, constant monitoring, analysing information flows as information carriers necessary for making prompt and informed management decisions. Socio-economic systems having computing resources that ensure the management of information flows are considered as cyber-social systems. The management process in socio-economic systems is considered in terms of narrative practice, therefore, within the framework of the narrative management model, human behavior as a subject and object of management in a socio-economic system is not modeled fundamentally. Mathematical models allowing formalization and reasonable interpretation in terms of a real simulated system are proposed to support the management stages. The architecture of the software package for supporting narrative management is given, in which the proposed models are implemented

Modeling the risk of illegal forest activity and its distribution in the southeastern region of the Sierra Madre Mountain Range, Philippines

Illegal activity within protected forests, such as illegal logging, slash-and-burn farming, and agricultural expansion, has brought many plant and animal species to the brink of extinction and threatens various conservation efforts. The Philippine government has introduced a number of actions to combat environmental degradation, including the use of mobile platforms such as the SMART-Lawin system to collect patrol data from the field, which represents a remarkable step towards data-driven conservation management. However, it remains difficult to control illegal forest activity within protected landscapes due to limited patrol and law enforcement resources. A better understanding of the spatial distribution of illegal activity is crucial to strengthening and efficiently implementing forest protection practices. In the present study, we predicted the spatial distribution of illegal activity and identified the associated environmental factors using maximum entropy modeling (MaxEnt). Patrol data collected using the SMART-Lawin system from the Baliuag Conservation Area for the period 2017-2019 were used to train and validate the MaxEnt models. We tuned the MaxEnt parameter setting using the ENMeval package in R to overcome sampling bias, avoid overfitting, and balance model complexity. The resulting MaxEnt models provided a clear understanding of the overall risk of illegal activity and its spatial distribution within the conservation area. This study demonstrated the potential utility of data-driven models developed from patrol observation records. The output of this research is beneficial for conservation managers who are required to allocate limited resources and make informed management decisions.

Technological creep masks continued decline in a lobster (Homarus gammarus) fishery over a century

Fishery-dependent data are frequently used to inform management decisions. However, inferences about stock development based on commercial data such as Catch-Per-Unit-Effort (CPUE) can be severely biased due to a phenomenon known as technological creep, where fishing technology improves over time. Here we show how trap improvement over nine decades has driven technological creep in a European lobster (Homarus gammarus) fishery. We combined fishing data, experimental fishing with contemporary and older trap types, and information on depletion effects during fishing seasons. The resulting standardized CPUE time series indicates a 92% decline in lobster abundance between 1928 and 2019 compared to 70% if technological creep is not corrected for. Differences are most pronounced within the last 40 years when the most substantial shift in gear technology occurred: an uncorrected CPUE index suggests an 8% increase in lobster abundance during this period, while the corrected CPUE index declined by 57%. We conclude that technological creep has masked a continuous stock decline, particularly in recent decades and largely driven by the shift from one- to two-chambered traps, as well as the ability of newer trap designs to capture larger lobsters. Our study confirms the importance of adequate standardization, including technological development, when using fishery dependent CPUE for monitoring and management of data-limited fisheries.

Examining the impacts of pinnipeds on Atlantic salmon: The effects of river restoration on predator–prey interactions

Abstract Seal populations in the Gulf of Maine have been recovering from historical bounty‐driven declines since they received federal protection in 1972. In the past few decades, their population growth has sparked renewed concerns over conflict between pinniped and fish conservation. In the Penobscot River in Maine, USA, where restoration efforts over the past decade have aimed at restoring diadromous fish runs, seal predation on the endangered Atlantic salmon (Salmo salar) has become a growing concern. Quantitative and qualitative data for individual salmon, as well as the presence of putative seal‐induced injury, have been collected from salmon passing upriver at dams in the Penobscot River since 2012. An analysis of seal‐induced injury rate with demographic data, river herring returns, estuary fish biomass estimates, and timing of peak estuary fish biomass revealed that the seal‐induced injury rate declined in the Penobscot River from 2012 to 2019, coincident with increasing river herring returns and estuary fish biomass. Despite a potentially increasing seal population, these results suggest that predator swamping from increasing forage fish may provide protection to salmon against seal predation. The presence of multiple injuries on an individual salmon was also significantly associated with the probability of a salmon having a seal‐induced injury. Lamprey wounds and lacerations on salmon were commonly associated with seal‐induced injury, suggesting a confounding effect of multiple stressors. This assessment illustrates how multi‐species diadromous restoration activities may alter predator–prey interactions in ways that support salmon conservation efforts. As demonstrated in the Penobscot River, a focus on overall ecosystem health and restoration can benefit multiple species that use the river. Insights from this study may help inform future management decisions in other human‐impacted systems where protected predators come into conflict with endangered prey.

Regional-scale genetic differentiation of the stony coral Desmophyllum dianthus in the southwest Pacific Ocean is consistent with regional-scale physico-chemical oceanography

Deep-sea corals are diverse and abundant in New Zealand’s EEZ and the southwest Pacific Ocean. We assessed genetic diversity and gene flow of the deep-sea scleractinian (stony cup coral) Desmophyllum dianthus in five areas (Kermadec Ridge, Louisville Seamount Chain, Chatham Rise, Campbell Plateau, Macquarie Ridge), and applied dispersal kernels estimated from drifters observations and seascape genetics to compare with observed connectivity patterns and regional physico-chemical data. We observed pronounced between-region genetic differentiation, high levels of self-recruitment, but also high connectivity between distant sites (e.g., at the Kermadec Ridge inside the New Zealand EEZ, and the Louisville Seamount Chain outside the New Zealand EEZ). Genetic diversity was marginally highest at the Kermadec Ridge, whilst populations on the Chatham Rise showed evidence of unique genetic diversity that may be driven by converging ocean currents. Overall, patterns of genetic connectivity were consistent with oceanographic predictions of dispersal routes. Seascape genetic analyses indicated that environmental variables most often related to physical seafloor habitat characteristics were important predictors of regional-scale genetic differentiation of D. dianthus. Our research shows that current spatial closures within the New Zealand EEZ and surrounding high seas areas do not encompass the extent of genetic diversity and connectivity for D. dianthus, which parallels research for other deep-sea taxa in the region. Future measures implemented to protect deep-sea coral biodiversity require consideration of complex connectivity patterns and migration routes amongst taxa, at various spatial scales. This study demonstrates that a combined gene flow, seascape genetics and dispersal kernel modelling approach can provide a robust evaluation of connectivity in deep-sea environments to inform management decision making at the scale of the southwest Pacific Ocean.