Search

Species distribution modelling (SDM) is a valuable tool for predicting the potential distribution of invasive species across space and time. Maximum entropy modelling (MaxEnt) is a popular choice for SDM, but questions have been raised about how these models are developed. Without biologically informed baseline assumptions, complex default SDM models could be selected, even though alternative settings may be more appropriate. Here we explored the effects of various SDM design strategies on distribution mapping of four forest invasive species (FIS) in Canada. We found that if we ignored the underlying FIS biology such as use of biologically relevant predictors, appropriate feature selection and inclusion of dispersal and biotic interactions when we developed our SDMs, we obtained complex SDMs (default) that provided an incomplete picture of the potential FIS invasion. We recommend simplifying SDM complexity and including biologically informed assumptions to achieve more accurate dispersal predictions, particularly when projecting FIS spread across time. We strongly encourage SDM users to perform species-specific tuning when modeling FIS distributions with MaxEnt to determine the best SDM design. [ABSTRACT FROM AUTHOR]

Context: Selective logging has been commonly mapped using binary maps, representing logged and unlogged forests. However, binary maps may fall short regarding the optimum representation of this type of disturbance, as tree harvest in tropical forests can be highly heterogeneous. Objectives: The objective of this study is to map forest disturbance intensities in areas of selective logging located in the Brazilian Amazon. Methods: Selective logging activities were mapped in ten forest management units using Sentinel-2 data at 10 m resolution. A spatial pattern analysis was applied to the logging map, using a moving window approach with different window sizes. Two landscape metrics were used to derive a forest disturbance intensity map. This map was then compared with actual disturbances using field data and a post-harvest forest recovery analysis. Results: Disturbed areas were grouped into five distinct disturbance intensity classes, from very low to very high. Classes high and very high were found to be related to log landings and large felling gaps, while very low intensities were mainly related to isolated disturbance types. The post-harvest forest recovery analysis showed that the five classes can be clearly distinguished from one another, with the clearest differences in the year of logging and one year after it. Conclusions: The approach described represents an important step towards a better mapping of selectively logged areas, when compared to the use of binary maps. The disturbance intensity classes could be used as indicators for forest monitoring as well as for further evaluation of areas under forest management. [ABSTRACT FROM AUTHOR]

Gypsy moth (Lymantria dispar L.) is one of the world's worst hardwood defoliating invasive alien species. It is currently spreading across North America, damaging forest ecosystems and posing a significant economic threat. Two subspecies L. d. asiatica and L. d. japonica, collectively referred to as Asian gypsy moth (AGM) are of special concern as they have traits that make them better invaders than their European counterpart (e.g. flight capability of females). We assessed the potential distribution of AGM in Canada using two presence-only species distribution models, Maximum Entropy (MaxEnt) and Genetic Algorithm for Rule-set Prediction (GARP). In addition, we mapped AGM potential future distribution under two climate change scenarios (A1B and A2) while implementing dispersal constraints using the cellular automation model MigClim. MaxEnt had higher AUC, pAUC and sensitivity scores (0.82/1.40/1.00) when compared to GARP (0.70/1.26/0.9), indicating better discrimination of suitable versus unsuitable areas for AGM. The models indicated that suitable conditions for AGM were present in the provinces of British Columbia, Ontario, Quebec, Nova Scotia and New Brunswick. The human influence index was the variable found to contribute the most in predicting the distribution of AGM. These model results can be used to identify areas at risk for this pest, to inform strategic and tactical pest management decisions. [ABSTRACT FROM AUTHOR]

Invasive species pose significant threats to forest ecosystems. Early intervention strategies are the most cost-effective means to control biological invasions, but are reliant on robust biosurveillance. State-of-the-art genomic approaches can provide an unprecedented opportunity to access detailed information on the invasion process and adaptive potential of invasive insects that pose an immediate threat to forests environments. Genomics can improve diagnostics of the invader and identify its route of invasion by determining the source population(s), assess its probability of establishment and patterns of spread, as well as provide evidence of adaptation. Applied biosurveillance efforts by plant health regulatory agencies will benefit substantially from the detailed insights that genomic data bring to our understanding of biological invasions. [ABSTRACT FROM AUTHOR]

Early intervention, effective management, and regulations are essential to mitigate the potential negative impacts of invasive forest insects. Biosurveillance provides the necessary knowledge to inform management, and regulatory practices. Genomic approaches can contribute valuable information to this process. Unfortunately, adoption and incorporation of genomic tools into biosurveillance frameworks is not straightforward. To realize the full potential of genomic knowledge, researchers must work together with end users to ensure full  adoption, standardization, validation, and interpretation of genomic results. [ABSTRACT FROM AUTHOR]

Panama has the highest rate of change in the area of primary forests within Central America. However, to meet growing timber demands, it became popular over the last decades to establish plantations made up of foreign species such as Tectona grandis or Pinus spp. In the majority of the cases the species used are well known; their characteristics such as growth performance have been reviewed intensively and can be accessed in numerous publications. Characteristics of Panama's native tree species of commercial relevance such as Hieronyma alchorneoides, Swietenia macrophylla and Terminalia amazonia are largely unknown and have been investigated within the study at hand. Using valuation methods of financial mathematics, the competitive position of these three indigenous species was assessed, the results compared to those of T. grandis stands in the same area. Land costs and taxes were not considered, as they would be the same for all species. Financial estimates for indigenous species will enlarge their acceptance for use in reforestation and plantation projects. Using the NPV method and applying the standard scenario, the profitability of T. grandis is lower than that of T. amazonia and S. macrophylla and lies only slightly above the profitability calculated for H. alchorneoides. This result clearly indicates that the investigated native tree species are comparable with T. grandis regarding their economic profitability. Besides its ecological impact, growing native tree species is now also economically legitimate. By calculating land expectation values for all tree species, ideal rotation lengths could be determined. For these species, considerable flexibility exists regarding the optimal rotation length. [ABSTRACT FROM AUTHOR]