Specific Management Objectives Research Articles

Evaluating drivers and predictability of catch composition in a highly mixed trawl fishery using stacked and joint species distribution models

Evaluating drivers and the predictability of catch is valuable for the management of mixed fisheries. Drivers can represent or help to identify levers for management and predictable catch compositions are a key component of simulation tools and dynamic management strategies. But modelling mixed fisheries can be challenging due to the large number of taxa, and analysis typically focuses on a few key species or highly aggregated taxa.Here we employ seven types of stacked and joint species distribution models to explore the drivers and predictability of trawl-level catches in an ocean prawn trawl fishery, in New South Wales, Australia. Catch data was sourced from an observer program, with 130 taxa able to be modelled. The main drivers of catch composition were latitude, depth, and seasonality represented here by water temperature. Water column mixing, lunar illumination, and fishing effort were also important for some taxa. Up to 60–80 taxa were predicted with good predictive skill (AUC>0.8, >35 % decline in mean absolute error relative to an intercept-only model), and an additional 40–60 taxa were predicted with lower but still useful predictive skill (AUC>0.7, 25–35 % decline in error). However, the level of predictive skill varied considerably among model type.The best framework for prediction was stacked random forests using a hurdle modelling approach, followed by a spatial joint species distribution model. Our results show that predictive models at a fine spatial-temporal and taxonomic resolutions can be a viable information tool for highly mixed fisheries, but these tools ultimately need to be tested against specific management objectives and performance metrics, such as spatial closures and bycatch:target catch ratios.

Tri-composed fuzzy relation inequality with weighted-max-min composition and the relevant min-max optimization problem

In the existing works, the classical fuzzy relation inequality (FRI) with double-composed operators has been introduced to describe the P2P network system. In this work, considering the successful rate of the line connection within the P2P network system, we establish the so-called tri-composed FRI, with a weighted-max-min composition, for the first time. We study the solutions induced through paths and further construct the complete solution set of the tri-composed FRI using the path-induced solutions. Moreover, the whole solution set could be fully determined by all the path-induced solutions and its unique maximum solution. Furthermore, considering a specific optimal management objective in the P2P network, we further study the min-max optimization problem with the tri-composed FRI constraints. A path-based algorithm is proposed for handling the problem we studied, accompanied by an illustrative example.

Managed aquifer recharge as a strategy to redistribute excess surface flow to baseflow in snowmelt hydrologic regimes

Water management in snowmelt hydrologic regimes, characterized by large annual fluctuations in stream flow driven by seasonal snow melt, faces the challenge of highly variable supply that often does not align with timing of demand. Climate change may exacerbate management challenges by significantly reducing snowpack or shifting snow melt earlier. Here, managed aquifer recharge (MAR) is evaluated as a potential strategy to reallocate excess early-season stream flow to time periods when less surface water is available. This strategy differs from traditional MAR, where the goal is to minimize loss to surface water. We assess how to site MAR operations such that groundwater recharge flows back to the surface water system in a lagged manor to benefit water management objectives, which we term “enhanced baseflow.” We use a regional groundwater model for the Treasure Valley aquifer located in southwestern Idaho, United States to demonstrate a generalizable approach using regional groundwater models as tools to identify favorable baseflow enhancement locations. Hypothetical MAR is simulated at 197 candidate locations, which are then evaluated for how effectively they meet potential management objectives. In addition to demonstrating the modeling and evaluation approach, we discuss lessons learned from applying a pre-existing regional groundwater model to MAR for enhanced baseflow and also describe important considerations, such as the physical and institutional availability of surface flows and specific management objectives, when assessing regional and site-specific suitability of MAR for enhanced baseflow as a potential management strategy.

Early silvicultural intervention affects species dominance in efforts to restore pine-hardwood mixedwoods following stand-replacing disturbance

Interest in replacing monocultures with species diverse stands has steadily grown. Mixedwoods (stands containing a balance of conifer and hardwood species) represent an alternative to monocultures and occur naturally through forest succession on most sites in eastern North America. In the central and southeastern United States, mixedwoods were generally dominated by pine and upland oak species. However, a combination of anthropogenic land use legacies has allowed fire-sensitive species to establish creating an opportunity for different mixedwood types to develop (e.g., pine-oak, pine-poplar, pine-gum). While any mixedwoods combination would increase tree species diversity relative to a monoculture, interest exists in whether silvicultural intervention can improve the performance of individual species to promote the development of different mixture types based on specific management objectives (e.g., wildlife habitat, timber quality, drought resistance). To address this question, we established an experiment examining the response of juvenile volunteer loblolly pine and six planted hardwood species (northern red oak, white oak, sweetgum, blackgum, yellow-poplar, and mockernut hickory to four silvicultural treatments (controlled release hardwood fertilization, coppicing, coppicing + broadcast fertilization, and planted control) in northern Mississippi, USA.Four-years post-planting, our results demonstrate that all treatments produced loblolly pine-hardwood co-dominance; however, hardwood dominance varied among treatments. In the planted control, loblolly pine and sweetgum were the co-dominant species, and statistically outgrew all species except yellow-poplar. Mockernut hickory (+ 40%), yellow-poplar (+ 23%), and blackgum (+ 15%) seedling height increased in controlled release fertilization compared to the planted control; however, apart from northern red oak, seedling survival of all hardwood species was less than 50%. The controlled release hardwood fertilization treatment was co-dominated by loblolly pine, yellow-poplar, and sweetgum. Sprouting in the coppiced treatment (89%) statistically exceeded that in the coppiced + broadcast fertilization treatment (73%), but did not vary among species. In general, coppicing reduced sprout height and survival relative to seedlings in the planted control, and promoted loblolly pine, yellow poplar, and sweetgum co-dominance. Coppicing + broadcast fertilization consistently reduced sprout survival compared to the planted control. However, trends in seedling height were mixed, with northern red oak (+ 14%) showing the largest improvement, and volunteer loblolly pine the largest decline (- 34%). Moreover, coppicing + broadcast fertilization produced the most species diverse outcome featuring yellow-poplar, loblolly pine, sweetgum, and northern red oak in co-dominant growing positions. Collectively, these results indicate that sweetgum and loblolly pine are likely to be prominent species in contemporary mixedwoods regardless of treatment. However, more species-diverse mixtures may be promoted by coppicing and broadcast fertilizing early in stand development.

A multistate Langevin diffusion for inferring behavior-specific habitat selection and utilization distributions.

The identification of important habitat and the behavior(s) associated with it is critical to conservation and place-based management decisions. Behavior also links life-history requirements and habitat use, which are key to understanding why animals use certain habitats. Animal population studies often use tracking data to quantify space use and habitat selection, but they typically either ignore movement behavior (e.g., foraging, migrating, nesting) or adopt a two-stage approach that can induce bias and fail to propagate uncertainty. We develop a habitat-driven Langevin diffusion for animals that exhibit distinct movement behavior states, thereby providing a novel single-stage statistical method for inferring behavior-specific habitat selection and utilization distributions in continuous time. Practitioners can customize, fit, assess, and simulate our integrated model using the provided R package. Simulation experiments demonstrated that the model worked well under a range of sampling scenarios as long as observations were of sufficient temporal resolution. Our simulations also demonstrated the importance of accounting for different behaviors and the misleading inferences that can result when these are ignored. We provide case studies using plains zebra (Equus quagga) and Steller sea lion (Eumetopias jubatus) telemetry data. In the zebra example, our model identified distinct "encamped" and "exploratory" states, where the encamped state was characterized by strong selection for grassland and avoidance of other vegetation types, which may represent selection for foraging resources. In the sea lion example, our model identified distinct movement behavior modes typically associated with this marine central-place forager and, unlike previous analyses, found foraging-type movements to be associated with steeper offshore slopes characteristic of the continental shelf, submarine canyons, and seamounts that are believed to enhance prey concentrations. This is the first single-stage approach for inferring behavior-specific habitat selection and utilization distributions from tracking data that can be readily implemented with user-friendly software. As certain behaviors are often more relevant to specific conservation or management objectives, practitioners can use our model to help inform the identification and prioritization of important habitats. Moreover, by linking individual-level movement behaviors to population-level spatial processes, the multistate Langevin diffusion can advance inferences at the intersection of population, movement, and landscape ecology.

Developing a Structural Complexity Index for Oriental Beech Forests in Northern Iran

Abstract The structural complexity index (SCI) has become an important metric for forest managers to monitor ecosystem services and conservation value in a wide variety of forest types. In this study, we developed an SCI for an unmanaged mixed Fagus orientalis Lipsky forest in northern Iran, which incorporated structural information specific to mature and old-growth forests. Our results showed that we were able to develop an SCI for this forest that would assist managers to make conservation decisions in a forest where large overstory trees and small understory trees are equally important. The SCI was significantly positively correlated with the density of five minor tree species (Acer velutinum Boiss., Acer cappadocicum Gled., Tilia begoniifolia Chun & H.D. Wong, Quercus castaneifolia C.A. Mey., and Prunus avium L.) and the density of large ([50 cm < diameter at breast height {DBH} < 75 cm]) and very large (DBH > 75 cm) overstory trees. The SCI remains a highly flexible tool for forest conservation and decision making and may assist with decisions about forest management in response to climate change and shifting disturbance regimes. Study Implications: Forest managers have begun to use the structural complexity index (SCI) to assess the successful achievement of conservation management objectives. In many mature, mixed-species forests, large trees, minor species, and understory tree species are important structural components. In this study, we demonstrate that reduction of the minimum diameter used for sampling trees and careful selection of the variables used to calculate SCI results in a valuable metric for making conservation decisions. The advantage of SCI as a forest decision tool is that forest managers are able to adjust the inputs used to calculate SCI to reflect specific management objectives or monitoring goals.

Zoonotic implications of white-footed mice habitat selection and territoriality in fragmented landscapes.

White-footed mouse (Peromyscus leucopus) populations can thrive in fragmented suburban and urban parks and residential spaces and play a pivotal role in the spread and prevalence of tick-borne diseases. We collected spatial data on 58 individual mice living at the intersection of county park land and residential land in suburban Howard County, MD, U.S.A. We analyzed mouse density, home-range size and overlap, and a Bayesian mixed-effects model to identify the habitats where they were found relative to where they were caught, as well as a resource selection function for general habitat use. We found that as mouse density increased, home-range size decreased. The overlap indices and the resource selection function supported territoriality coupled with site-specific space use in these suburban mouse populations. While mice occurred in open areas, forest edge, and forest, they showed a strong preference for forested areas. Interestingly, mice captured only 30 to 40 m into the forest rarely used the nearby private yards or human structures and this has direct implications for the placement of rodent-targeted tick control treatments. Our study supports the need for zoonotic disease management frameworks that are based on site-specific land cover characteristics as well as specific management objectives.

Structural and functional changes in Artificial Reefs ecosystem stressed by trophic modelling approach: Case study in the Bay of Biscay

Artificial Reefs (ARs) are commonly cited as a tool used for increasing fishery production and reinstating ecosystem functionalities. The assessment of ARs deployment is mostly based on analysis of the evolution of fish communities. Recently, studies have focused on trophic modelling to understand the functioning of such ecosystems in a more holistic approach. Trophic models are able to address this concern by describing the interaction between species at different trophic levels and based on the quantification of energy and matter flows through ecosystems. These models allow the application of numerical methods – also called Ecological Network Analysis (ENA) – to characterize emergent properties of the ecosystem. Usually, ENA indices are proposed as indicators of ecosystem health as they are sensitive to different impacts on marine ecosystems. In the present study, the Ecopath software is used to build an ecosystem model composed of 23 compartments, from detritus and phytoplankton to mammals, to describe the situation “before” and “after” the deployment of ARs in the south of the Bay of Biscay along the Landes coast. In addition, ENA indices are calculated for two periods, “before” and “after” the deployment of artificial reefs, to compare network functioning and the overall properties of the structural trophic network. Our results show little structural change in the ecosystem, with a rearrangement of the trophic levels and a simultaneous increase in biomass and system maturity. These preliminary results evidently need to be confronted with other environmental factors such as, for instance, substrate composition, proximity to natural reefs and larval supply. Nonetheless, we consider that the maturity index could be used as a new indicator to assess the evolution of ARs with specific management objectives.

Smart Irrigation System Using Arduino

Abstract: Agriculture is a source of livelihood of majority Indians and has great impact on the economy of the country. In dry areas or in case of inadequate rainfall, irrigation becomes difficult. So, it needs to be automated for proper yield and handled remotely for farmer safety. Increasing energy costs and decreasing water supplies point out the need for better water management. Irrigation management is a complex decision making process to determine when and how much water to apply to a growing crop to meet specific management objectives. If the farmer is far From the agricultural land he will not be noticed of current conditions. So, efficient water management plays an important role in the irrigated agricultural cropping systems. A low cost alternative solution for efficient water management currently in use is drip irrigation systems that consist of an automated controller to turn on & off the control values, which in turn helps the farmers by managing the water supply to the crop fields and further maintains the moisture levels of soil that helps in better crop production. This project probes into the design of the automated irrigation system based on Arduino. This Embedded project is to design and develop a low cost feature which is based on embedded platform for water irrigation system. This project uses temperature and soil moisture sensors to detect the water quantity present in agriculture. The project uses Arduino micro controller which is controller to process the information. The aim of the implementation was to demonstrate that the automatic irrigation can be used to reduce water use

Performance Based on Measurements from Individual-Tree Progeny Tests Strongly Predicts Early Stand Yield in Loblolly Pine

Abstract To facilitate the utility of genetic improvement in loblolly pine, individual-tree volume (productivity) scores estimated from single-tree plot or row-plot progeny test designs were compared with stand-level volume per unit area from block plots. A large number of families representing a wide range of progeny test scores for volume were established in growth and yield trials to generalize the results to families created by the breeding program. Individual-tree volume scores from progeny tests strongly corresponded with stand-level volume from block plots, especially after accounting for site quality and the risk of fusiform rust disease. A ten-point increase in the volume score from progeny test data was estimated to increase stand-level volume by 3.9 m3 ha-1 at age 6 years. A prediction model is presented that includes a new statistic, rust risk index, which is the expected rust incidence for a family at a new site when the hazard of rust for a checklot can be estimated from historical data. The study results through age 6 years corroborate the Performance Rating System as effective in guiding family deployment decisions. The models presented are based on pre-crown closure data at 6 years and will be updated with older measurements as the study matures. Study Implications: The Performance Rating System (PRS™) has been a successful tool for presenting genetic merit of improved loblolly pine families for landowners and forest managers in a more coherent and standardized manner. This system can be easily applied in other forest tree improvement programs, because it makes genetic improvement user-friendly for silviculturists and forest managers. Landowners can use this system to make decisions for selecting improved families suited to their specific forest management objectives. Seed orchard and nursery managers also depend on the PRS to choose the families to produce and as a third-party verification to market their genetic merit to customers. This study demonstrates that higher stand-level volume per unit area can be achieved when forest managers plant fast growing families with low fusiform rust disease risk on productive sites. The combined effect of genetic improvement for productivity and fusiform rust disease resistance is significant on stand-level volume per unit area.

Estimating heat tolerance of buds in southeastern US trees in fire-prone forests

BackgroundTraits of mature trees, such as bark thickness and texture, have been documented to promote resistance or resilience to heating in fire-prone forests. These traits often assist managers as they plan and promote prescribed fire management to accomplish specific land management objectives. Species are often grouped together as pyrophobes or pyrophytes as a result of these features. Nonetheless, little is known about species-specific traits of other structures, such as bud diameter, length, mass, moisture content, and surface area, that might be related to heat tolerance. Many prescribed fires are utilized in the eastern United States to control regeneration of less desired species, which could apply a more mechanistic understanding of energy doses that result in topkilling mid-story stems. In this study, we investigated potential relationships between terminal bud mortality from lateral branches of midstory stems and species-specific bud features of six eastern US deciduous trees. Characterized at maturity as either pyrophytes or pyrophobes, each was exposed to different heat dosages in a laboratory setting.ResultsBud diameter, length, mass, moisture content, and surface area differed by species. Bud percent mortality at the first heat flux density (0.255–0.891MJm−2) was highest for two pyrophobes, chestnut oak (Quercus montana Willd.) and scarlet oak (Quercus coccinea Münchh). For the second heat flux density (1.275–1.485MJm−2), bud percent mortality was highest for these species and red maple (Acer rubrum L.). Principal component analysis suggested that bud surface area and length differentiated species. Red maple, chestnut oak, and scarlet oak produced clusters of buds, which may explain their more pronounced bud mortality. Yellow-poplar (Liriodendron tulipifera L.) was also present in that cluster, suggesting that its unique bud architecture of pre-emergent leaves may have elicited responses most similar to those of the clustered buds.ConclusionsContrary to expectations, lateral buds of species regarded as pyrophytes at maturity displayed some of the highest values of bud percent mortality when heated at two heat flux densities generated in a laboratory. Their responses may be related to clustering of their lateral buds. Testing of additional species using these methods in a laboratory setting, and perhaps additional methodologies in the field, is warranted.

Establishing an ecological monitoring system for national parks in China: A theoretical framework

• A theoretical framework for ecological monitoring in national parks is designed. • The importance of balancing conservation and development objectives is emphasized. • A unified and park-specific monitoring indicator system is highlighted. • An implementation mechanism combining top-down with bottom-up approaches is proposed. The protected area system in China is entering a new stage where its management seeks to consolidate governance while balancing multiple management objectives. National parks, as the mainstay of this new system, have received considerable attention in order to maintain the authenticity and integrity of ecosystems and protect globally recognized biodiversity. Well-designed ecological monitoring and the information it yields is increasingly recognized as compulsory for the effective management of national parks. However, pilot national parks in China were established through the integration of different types of protected areas and, as a result, are confronting the difficulties of integrating and synthesizing disparate monitoring programs. In this research, we put forward a theoretical framework for establishing an integrated ecological monitoring system for national parks in China. The proposed framework highlights the importance of balancing ecological conservation and community development objectives and offers the trade-off analysis method to pair key ecosystem services to the dual management objectives. It also emphasizes a unified and park-specific monitoring indicator system that requires matching the indicators to key ecological processes and specific management objectives. Moreover, we propose an implementation mechanism with a combination of top-down and bottom-up approaches, and encourage local communities to participate in and have access to information generated through monitoring of national parks. We submit that this research described will not only provide scientific support for policy makers to establish an ecological monitoring system in national parks, but also contribute to more informed and efficient management of the expanding network of national parks in China.

Historical seasonal changes in prescribed burn windows in California

Prescribed (Rx) burns are conducted on days when the meteorological thresholds of maximum air temperature, relative humidity, and wind speeds are all met (burn window) in order to ensure safe Rx burn practices. Limited burn windows have been consistently identified as one of the most important constraints for conducting Rx burns in California. We investigate whether burn windows across California can be extended from the typical fall season to include other opportune seasons for facilitating specific management objectives. We quantify the seasonal Rx burn efficiencies by assessing the frequency and burned areas using an aggregate of Rx datasets, and we compute the seasonal spatiotemporal trends in the number of days the set of meteorological parameters are met over thirty-five years (1984 to 2019), using the gridMET 4 km dataset. Our results indicate that while fall burns are most frequently executed (40% of the time), the spring (and to a lesser extent winter) seasons yield efficient Rx burns similar to fall because greater acres are being consumed with less burns. In addition, winter and spring seasons experience burn window opportunities (70-90% of the time) over larger areas than the other seasons, and this is predominantly over forested regions in Northern California. Our results also indicate that burn windows in the winter and spring are decreasing at a rate of one day per year over a larger spatial area than that of summer and fall. This decrease is primarily driven by changes in the number of days the relative humidity thresholds are met. Policymakers recognize the critical importance that Rx burns have on a multitude of ecosystem restoration factors, fire behavior dynamics, and firefighter safety. Therefore, there is a need to capitalize on these additional burn windows before these opportunities become less feasible in the future.

Developing a typology of female forest landowners in Georgia, United States

ABSTRACT The percentage of female forest landowners (FFLs) in the United States increased from 11% in 2006 to 20% in 2018. Since women almost outlive men by about five years, the percentage of FFLs is likely to further increase in the future. Due to this likely shift in forestland ownership, it is vital to develop typologies of FFLs based on their motivations for forestland management. In this study, we used Q methodology to develop a typology of FFLs in Georgia – a prominent forestry state located in the Southern United States. Each participant sorted 30 statements that represented 10 unique forestland management objectives common for FFLs. Analysis of the responses identified three types of FFLs that reflect the land management objectives of the participants. Type 1 FFLs find part of their identity in their forestland. Type 2 FFLs prioritize financial returns from their forestlands. Type 3 FFLs prioritize improving wildlife habitat. Salient to the three types, all FFLs display high levels of place attachment and prioritize future generations in management decisions. These results illustrate the need for educational and networking opportunities that better cater to the specific forest management objectives of FFLs.

Data-Driven Recommendations for Establishing Threshold Values for the NIS Trend Indicator in the Mediterranean Sea

In the present work, we analysed time series data on the introduction of new non-indigenous species (NIS) in the Mediterranean between 1970 and 2017, aiming to arrive at recommendations concerning the reference period and provisional threshold values for the NIS trend indicator. We employed regression analysis and breakpoint structural analysis. Our results confirm earlier findings that the reference conditions differ for the four Mediterranean subregions, and support a shortening of the reporting cycle from six to three years, with a two-year time lag for the ensuing assessment. Excluding Lessepsian fishes and parasites, the reference period, defined as the most recent time segment with stable mean new NIS values, was estimated as 1997–2017 for the eastern Mediterranean, 2012–2017 for the central Mediterranean, 2000–2017 for the Adriatic and 1970–2017 for the western Mediterranean. These findings are interpreted primarily on the basis of a basin scale temperature regime shift in the late 1990s, shifts in driving forces such as shellfish culture, and as a result of intensified research efforts and citizen scientist initiatives targeting NIS in the last decade. The threshold values, i.e., the three-year average new NIS values during the reference period, are indicative and will ultimately depend on the choice of species and pathways to be used in the calculations. This is discussed through the prism of target setting in alignment with specific management objectives.

Developing a Risk Management Process for General Contractors in the Bidding Stage for Design–Build Projects in Vietnam

Design–build (DB) projects have become increasingly popular for construction projects in developing countries due to the cost and scheduling advantages and their design optimization ability. As a result, much research has been conducted on improving DB efficiency in terms of cost, scheduling, risk management, etc. However, the existing studies have mainly focused on the owner’s roles, whereas general contractors (GCs) must also take many risks on behalf of owners in DB projects. The adequate identification and assessment of risks before engaging a contractor can increase the likelihood of a project’s success, at least from a DB contractor’s perspective. Therefore, this study interviewed procurement experts to conduct a survey at the local level, then analyzed, developed, and proposed an additional risk management process (RMP) for use by GCs during the bidding process of DB projects. A case study was conducted with a large Vietnamese GC to evaluate the effectiveness of the process and find ways to optimize it in the future. The results of the study showed that risk management during a DB project is imperative. Nevertheless, preparing bids is time-consuming and increases the contingency costs, reducing the competitiveness of the bid prices for contractors. Therefore, depending on the specific project and risk management objectives, an RMP is recommended for adjusting the risk management target to reduce the risk, while still maintaining the competitiveness of the bid prices.

Application of explicit precautionary principles in data-limited fisheries management

Abstract Many management bodies require applying the precautionary approach when managing marine fisheries resources to achieve sustainability and avoid exceeding limits. For data-limited stocks, however, defining and achieving management objectives can be difficult. Management procedures can be optimized towards specific management objectives with genetic algorithms. We explored the feasibility of including an objective that limited the risk of a stock falling below various limit reference points in the optimization routine for an empirical data-limited control rule that uses a biomass index, mean catch length, and includes constraints (the “rfb-rule”). This was tested through management strategy evaluation on several fish stocks representing various life-history traits. We show that risk objectives could be met, but more restrictive risk limits can lead to a potential loss of yield. Outcomes were sensitive to simulation conditions such as observation uncertainty, which can be highly uncertain in data-limited situations. The rfb-rule outperforms the method currently applied by ICES, particularly when risk limitation objectives are considered. We conclude that the application of explicit precautionary levels is useful to avoid overfishing. However, we caution against the indiscriminate use of arbitrary risk limits without scientific evaluation to analyse their impact on stock yields and sustainability.

Carnivore Detection at the Domestic/Wildlife Interface within Mpumalanga Province, South Africa.

Simple SummaryThe management of carnivore populations in protected areas includes disease management and census taking. The presence of prey species and environmental variables influence the detection of wild carnivore species. The aim of this study was to identify the important predictors of wild carnivore detection within two South African wildlife reserves using motion-detection camera traps. The study further investigated the difference between traditional census call-up surveys and camera traps within nearby locations. Buffalo, impala, and warthog were associated with lion and spotted hyena detections. Detections of lions and spotted hyenas and also leopards and spotted hyena were correlated, suggesting competition between these wild carnivore species. Competition among wild carnivore species has importance for implementing appropriate management procedures, including infectious disease prevention.South African protected areas account for 8% of the total landmass according to World Bank indicators. Effective conservation of biodiversity in protected areas requires the development of specific reserve management objectives addressing species and disease management. The primary objective of the current study was to identify predictors of carnivore detection in an effort to inform carnivore species management plans on Andover and Manyeleti nature reserves in South Africa. A limited number of camera traps were placed randomly using a grid system. Species detection data were analysed using mixed-effects logistic regression and Spearman’s correlation coefficients. Deterministic inverse distance weighted distribution maps were used to describe the spatial distribution of carnivore species. Camera traps identified similar species as traditional call-up surveys during the study and would be useful as an adjunct census method. Carnivore detection was associated with several variables, including the presence of specific prey species. The measured intra-and interspecies interactions suggested the risk of disease transmission among species, and vaccination for prevalent diseases should be considered to manage this risk.

Spatial databases and techniques to assist with prescribed fire management in the south-east Queensland bioregion

This paper identifies key fire history and fire-related spatial databases that can be utilised for effective planning and assessment of prescribed burns in south-eastern Queensland. To ensure that appropriate fire regimes are maintained for specific management objectives (e.g. biodiversity conservation or risk management), and to assist fire managers with planning prescribed fire and post-fire assessments, we describe, using case studies and existing tools, the application of remote sensing data and derived burned area products together with field data to potentially: (1) improve mapping of fire-prone areas; (2) improve the accuracy of mapping burned areas; (3) monitor temporal changes in fuel structure; and (4) map post-fire severity. This study utilised data collected from aerial and satellite-based multispectral, microwave and laser (LiDAR) sensors. There are several spatial databases and analytical methods available that are not currently used by fire management agencies in this region. For example, the methods to estimate fuel, such as LiDAR, are underutilised and unburned patches within a burned area are not routinely mapped. Better use of spatial datasets could lead to an improved understanding of variables such as fuel status, resulting in more efficient use of fire management resources.

The relationship between volume increment and stand density in Norway spruce plantations

AbstractAn understanding of the relationship between volume increment and stand density (basal area, stand density index, etc.) is of utmost importance for properly managing stand density to achieve specific management objectives. There are two main approaches to analyse growth–density relationships. The first relates volume increment to stand density through a basic relationship, which can vary with site productivity, age, and potentially incorporates treatment effects. The second is to relate the volume increment and density of thinned experimental plots relative to that of an unthinned experimental plot on the same site. Using a dataset of 229 thinned and unthinned experimental plots of Norway spruce, a growth model is developed describing the relationship between gross or net volume increment and basal area. The models indicate that gross volume increases with increasing basal area up to 50 m2 and thereafter becomes constant out to the maximum basal area. Alternatively, net volume increment was maximized at a basal area of 43 m2 and decreased with further increases in basal area. However, the models indicated a wide range where net volume increment was essentially constant, varying by less than 1 m3 ha−1 year−1. An analysis of different thinning scenarios indicated that the relative relationship between volume increment and stand density was dynamic and changed over the course of a rotation.