Potential applications of randomised graph sampling to invasive species surveillance and monitoring.

Abstract Many invasive plants and animals disperse preferentially through linear networks in the landscape, including road networks, riparian corridors, and power transmission lines. Unless the network of interest is small, or the budget for surveillance is large, it may be necessary to draw inferences from a sample rather than a complete census on the network. Desired features of a surveillance system to detect and quantify invasion include: (1) the ability to make unbiased statements about the spatial extent of invasion, the abundance of the invading organism, and the degree of impact; (2) the ability to quantify the uncertainty associated with those statements; (3) the ability to sample by moving within the network in a reasonable fashion, and with little wasted non-measurement time; and (4) the ability to incorporate auxiliary information (such as remotely sensed data, ecological models, or expert opinion) to direct sampling where it will be most fruitful. Randomised graph sampling (RGS) has all of these attributes. The network of interest (such as a road network) is recomposed into a graph, consisting of vertices (such as road intersections) and edges (such as road segments connecting nodes). The vertices and edges are used to construct paths representing reasonable sampling routes through the network; these paths are then sampled, potentially with unequal probability. Randomised graph sampling is unbiased, and the incorporation of auxiliary information can dramatically reduce sample variances. We illustrate RGS using simplified examples, and a survey of Polygonum cuspidatum (Siebold & Zucc.) within a high-priority conservation region in southern Maine, USA

Population, Greenspace, and Development:Conversion Patterns in the Great Lakes Region

In this brief, authors Mark Ducey, Kenneth Johnson, Ethan Belair, and Barbara Cook combine demographic, land-cover, and other spatial data to estimate the incidence and extent of conversion from greenspace (forestland, shrublands, and grasslands) to development in the Great Lakes states. They report that greenspace conversions to developed land are most common in areas where greenspace is already limited. Population density strongly influences the conversion of greenspace to development. Conversions are most likely to occur on the urban periphery and in high-amenity rural areas. This research contributes to a better understanding of the linkages between demographic and land-cover change and provides facts that can inform policy aimed at balancing development and greenspace conservation

Forests in Flux: The Effects of Demographic Change on Forest Cover in New England and New York

This brief contributes to a better understanding of the linkages between demographic and forest cover change so as to inform policy efforts aimed at maintaining existing forested areas in and around sprawling urban centers. Authors Mark Ducey, Kenneth Johnson, Ethan Belair, and Miranda Mockrin report that forest cover has declined throughout New England and New York over the last decade. In rural areas, forest loss is primarily due to commercial timber harvesting and represents a temporary change. Conversely, forest cover decline in urban areas is usually the result of development and is likely to be permanent. Forest cover change is strongly linked to demographic variables throughout this region. Forest cover loss is most pronounced along the urban fringe, where population growth is greatest. Amenity-rich rural areas are also experiencing high rates of population growth and regionally-high rates of forest cover loss. However, the causes of forest cover change in these areas are less certain. Forest cover change has the potential to impact ecosystem services important to both local residents and the larger region

Biomass equations for forest regrowth in the eastern Amazon using randomized branch sampling.

Florestas secundárias ocupam uma área extensa e crescente na bacia Amazônica, porém determinações acuradas do impacto dessas florestas nos ciclos de carbono e nutrientes têm sido dificultadas pelo número reduzido de equações alométricas. Neste estudo, nós desenvolvemos equações em nível de comunidade e espécies individuais para estimar a biomassa total da parte aérea de uma floresta secundária com 15 anos de idade na Amazônia oriental. O trabalho de campo utilizou amostragem aleatória de ramos, que é uma técnica rápida, porém pouco utilizada em florestas tropicais. Baseada no erro padrão da série de segmentos individuais (14%), a consistência da série de segmentos totais amostrados foi considerada elevada, sugerindo que o método pode ser eficiente em comparação com procedimentos tradicionais. Os melhores ajustes foram obtidos com a equação tradicional Y=a×DBHb, onde Y é a biomassa, DBH é o diâmetro à altura do peito, e a e b são parâmetros para cada espécie arbórea. Ajustes razoáveis também foram alcançados com equações da forma Y=a(BA×H), onde Y é a biomassa, BA é a área basal, H é a altura e a é um parâmetro específico para cada espécie arbórea. Comparações com equações disponíveis na literatura indicaram uma faixa de erro provável de -33% a +29% usando-se relações desenvolvidas para outros sítios. Nós também apresentamos equações para os seguintes componentes da biomassa da parte aérea: tronco, ramos e folhas

Modeling raccoon (Procyon lotor) habitat connectivity to identify potential corridors for rabies spread

The United States Department of Agriculture (USDA), Animal and Plant Health Inspection Service (APHIS), Wildlife Services National Rabies Management Program has conducted cooperative oral rabies vaccination (ORV) programs since 1997. Understanding the eco-epidemiology of raccoon (Procyon lotor) variant rabies (raccoon rabies) is critical to successful management. Pine (Pinus spp.)-dominated landscapes generally support low relative raccoon densities that may inhibit rabies spread. However, confounding landscape features, such as wetlands and human development, represent potentially elevated risk corridors for rabies spread, possibly imperiling enhanced rabies surveillance and ORV planning. Raccoon habitat suitability in pine-dominated landscapes in Massachusetts, Florida, and Alabama was modeled by the maximum entropy (Maxent) procedure using raccoon presence, and landscape and environmental data. Replicated (n = 100/state) bootstrapped Maxent models based on raccoon sampling locations from 2012–2014 indicated that soil type was the most influential variable in Alabama (permutation importance PI = 38.3), which, based on its relation to landcover type and resource distribution and abundance, was unsurprising. Precipitation (PI = 46.9) and temperature (PI = 52.1) were the most important variables in Massachusetts and Florida, but these possibly spurious results require further investigation. The Alabama Maxent probability surface map was ingested into Circuitscape for conductance visualizations of potential areas of habitat connectivity. Incorporating these and future results into raccoon rabies containment and elimination strategies could result in significant cost-savings for rabies management here and elsewhere

Rapid Assessment of Relative Density in Mixed-Species Stands of the Northeastern United States

Basal area has shortcomings as a measure of stand density, but it is often preferred for operational assessments because it is easy to measure. Previous work has demonstrated that an additive version of Reineke's stand density index can be estimated by a simple tree count using a modified horizontal point sampling technique. We show that this technique can be extended further to estimate a mixed-species density measure that has been developed for complex stands in the northeastern United States, using wood specific gravity to harmonize the density contributions of different species. The sampling technique provides design-unbiased estimates of stand density from a weighted tree count, where the weights depend on specific gravity but not on diameter. Rounding the specific gravity values for different species in the calculation of estimates introduces a trivial amount of bias but streamlines the procedure for rapid use in the field

Placental microbial–metabolite profiles and inflammatory mechanisms associated with preterm birth

There is growing emphasis on the potential significance of the placental microbiome and microbiome–metabolite interactions in immune responses and subsequent pregnancy outcome, especially in relation to preterm birth (PTB). This review discusses in detail the pathomechanisms of placental inflammatory responses and the resultant maternal–fetal allograft rejection in both microbial-induced and sterile conditions. It also highlights some potential placental-associated predictive markers of PTB for future investigation. The existence of a placental microbiome remains debatable. Therefore, an overview of our current understanding of the state and role of the placental microbiome (if it exists) and metabolome in human pregnancy is also provided. We critical evaluate the evidence for a placental microbiome, discuss its functional capacity through the elaborated metabolic products and also describe the consequent and more established fetomaternal inflammatory responses that stimulate the pathway to preterm premature rupture of membranes, preterm labour and spontaneous PTB

Salvage decision-making based on carbon following an eastern spruce budworm outbreak

Forest disturbances, such as an eastern spruce budworm (Choristoneura fumiferana) outbreak, impact the strength and persistence of forest carbon sinks. Salvage harvests are a typical management response to widespread tree mortality, but the decision to salvage mortality has large implications for the fate of carbon stocks (including forest carbon and harvested wood products) in the near and long terms. In this study, we created decision-support models for salvage harvesting based on carbon after an eastern spruce budworm outbreak. We used lasso regression to determine which stand characteristics (e.g., basal area) are the best predictors of carbon 40 years after an outbreak in both salvage and no salvage scenarios. We modeled carbon at year 40 for different treatment scenarios and discount rates. Treatment scenarios represent residual stand conditions that may be present when an outbreak occurs. Economic discount rates were applied to 40-year carbon values to account for near and long-term carbon storage aspects. We found that the volume and size of eastern spruce budworm host species are significant predictors of salvage preference based on carbon. We found overall that salvaging less volume is recommended to avoid major swings in carbon budgets and that discounting carbon values to apply weight to near or long-term sequestration greatly affects whether salvaging is preferred. Lasso models are constructed for the northeastern US, however, similar concepts may be applied beyond our study area and potentially for other insect outbreaks similar to spruce budworm, such as mountain pine beetle (Dendroctonus ponderosae) or hemlock woolly adelgid (Adelges tsugae). From a policy standpoint widespread salvaging could create a large carbon emissions deficit with the risk of not being fully replenished within a desired timeframe. Since salvaging is often financially driven, especially for private landowners, carbon market payments or incentives for not salvaging is a consideration for future policy