Assessment and Management of Plant Invasions (Springer Series on Environmental Management)
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It is widely recognized that eradication and containment of Invasive woody plant species is both difficult and costly. Ecological monitoring programmes aim to assess changes in biodiversity and ecosystem properties. Monitoring programmes can be set up at different spatial scales e. In Europe, the Natura network of protected areas represents an opportunity for testing and implementing adaptive management of invasive woody plant species at regional scales since many LIFE EU funded projects have been undertaken in those areas EEA Moreover, the new European Union EU regulation for prevention and management of invasive alien species has entered into force on the 1st of January representing a milestone in the conservation of European biodiversity European Parliament and Council of the European Union Member states are expected to ensure coordination and cooperation of invasive species management by establishing a European monitoring system that is implemented and harmonized across countries.
We propose integrating species distribution models SDMs , scenario analysis and estimates of surveillance effort hierarchically, to improve assessment of woody plant species invasions at regional and local scales. We illustrate the framework using Acacia dealbata Link. The implementation of the proposed framework aims at identifying the current and future areas where the species is predicted to occur and to prioritize the areas where monitoring networks will be most effective in capturing the state and trends of the species.
To handle multicollinearity, Spearman's rho correlation tests between variables and generalized variance inflation factors VIF were used. This approach yielded a final set of 24 environmental predictors.
The baseline climate data was based on interpolations of observed data from — Based on the spatial autocorrelation structure of each predictor, we classified them into two groups: those varying locally and those varying regionally. Then, to express the likelihood of each predictor belongs to each class local vs. In a first step, areas of high conservation value were mapped based on the two conservation areas networks in the region: the European Natura Network and the National Protected Areas Network.
Conservation status the level of protection for nature conservation purposes was used as a proxy of conservation value.
Each map was classified into four classes, from 1 no conservation status to 4 highest conservation status. For the nationally protected areas available in the region one national park and three natural parks , conservation status was extracted from the corresponding management plans by the National Agency for Nature Conservation and Forestry ranging from 1 — no protection to 4 — maximum protection.
For each cell, the conservation status was computed from the percentage of the cell occupied by each class weighted mean e. Finally, the two maps were combined to obtain a conservation value area map. Species distribution models are increasingly used to test the importance of key environmental drivers of invasive woody plant species distributions e.
Combined predictions of species distributions were mapped over the full geographical extent of the study area. To produce projections of species distribution into the future, regional climate variables obtained from climate change scenarios were used and utilized with the same modelling procedures used. Local variables e. To identify spatial conflicts between conservation value areas and invasion, we overlaid predictions and projections derived from combined SDMs with the conservation value map, which allow a refined detection of present and future conflict areas see Fig.
We created spatial projections of current and future impacts of the distribution of the invasive species, A.
Assessment and Management of Plant Invasions (Springer Series on Environmental Management)
The connectivity of predicted suitable areas for A. The connectivity index attains a maximum value of 1 when all cells surrounding a focal suitable cell belong to class A. Monitoring networks were identified through hierarchical assessments in the previous steps coupled with area network selection. Area network selection was performed using a nested design.
At any hierarchical stage sampling was done from a pool of areas selected to be part of the network in the precedent stage. We defined two types of networks based on different priorities: i one that prioritizes monitoring of invasive species in currently established in European Natura Network and the National Protected Areas Network protected area networks, PAN and ii one that prioritizes monitoring of invasive species at the regional scale including the north of Portugal Regional Networks, RN.
The outputs from steps 1 to 5 in the analytical framework Fig. The criteria used for network delineation were as follows:. The higher the connectivity, the higher the probability of a given cell being selected Fig. If the number of cells to select was higher than the number of protected areas available, then the remaining cells were uniformly selected from the unprotected area set Fig. Depending on the network type, these criteria were allocated to different hierarchical levels of the decision protocol Fig.
The targeted number of monitoring areas n 5 was alternatively 50, , or n 5. We identified networks for two periods of time: baseline and future conditions. Finally, we ran the selection algorithm times for each combination of network type, size, nestedness condition and time context. We also generated random networks of the same network size n 5 to define benchmarks to which the generated networks were compared a procedure with long tradition in conservation planning; e.
Indeed, although optimization is, by definition, a process to attain best performances then null models, because our framework is not mathematically driven and entails some stochasticity, it turns out to be relevant testing our results against random generated networks. For each combination of network type, size, nestedness condition and temporal context, we obtained solutions.
Since the resulting frequency distribution of solution sets did not follow a Gaussian distribution, we applied Kruskal—Wallis tests to assess significant differences between network types regional network vs. PAN regarding each one of the five analysed factors. Because these data sets do not satisfy Gaussian assumptions we used nonparametric Mann—Whitney—Wilcoxon tests.
We ranked each monitoring network based on the five analysed factors.
Serie: Springer Series on Environmental Management
This assessment was done separately for the regional and PAN s. We used the concept of Pareto dominance Clark , in which a solution is said to dominate another if it is not inferior to the second in all the objectives and if it is better in at least one them Fig. The areas with suitable regional and local conditions for A. All spatial combinations expressing impacts types a—d between A.
Spatially, the higher impacts will potentially take place in the western part of the study area, particularly along the western limits of protected areas, where the high protection value coincides with suitable conditions for the invasive species Fig. Current connectivity among populations was higher in the whole study area than inside the protected areas, but the latter is predicted to slightly increase by Importantly, the optimization performance of our framework was positively validated as the factors related to the lowest levels in the hierarchical procedure protected area connectivity in PAN; regional connectivity in RN presented the largest differences to the random networks.
Broadly, the factors that most differentiated network types were regional connectivity, FC, and entropy i. RN targeted areas with higher predicted impacts of invasion than PAN, although the impacts FI entered into higher levels in the hierarchical decision process, and therefore, it was settled a more distal goal to drive the RN design. This result is derived from the significantly positive correlation between FI and the lowest factor i. Within PAN and RN, constrained nestedness resulted in more uniform distributions of environmental classes i.
In RN, differences were less marked and inconsistencies occurred among solutions of different size. When comparing time periods, a more balanced representation of suitability classes i. For the remaining factors including survey cost , networks defined for reached significantly higher values. Community Response to Plant 1nvasion.
Assessment and Management of Plant Invasions by James O. Luken
Driving Forces Behind. Direct Management. Methods ior Management oi Nonindigenous Aquatic Plants. Prioritizing 1nvasive Plants and Planning ior Management.
Assessment and Management of Plant Invasions
Prevention oi 1nvasive Plant 1ntroductions on National and Local Levels. CoveringWalks in Graphs is aimed at researchers and graduate students in the graph theory community and provides a comprehensive treatment on measures of two well studied graphical properties, namely Hamiltonicity and traversability in graphs. This text looks into the famous Typically, landscape ecologists use empirical observations to conduct research and devise solutions for applied problems Typically, landscape ecologists use empirical observations to conduct research and devise solutions for applied problems in conservation and management.
In some instances, they rely on advice and input of experienced professionals in both developing and applying knowledge. Given the wealth The importance of restoration continues to grow, and this book integrates the restoration of forest The importance of restoration continues to grow, and this book integrates the restoration of forest functions into landscape conservation plans. The global conservation organization WWF has made forest landscape restoration a key topic and priority for its environmental work. Insect-Plant Interactions. The authoritative overviews in this volume provide a wealth of practical information on current approaches The authoritative overviews in this volume provide a wealth of practical information on current approaches to the study of insect-plant interactions.
Methods described include direct behavioral observation; assays of host finding, oviposition, and feeding behavior of insect herbivores; post-ingestion physiological Multidimensional Hyperbolic Problems and Computations.
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