A growing body of evidence suggests that criminal activities associated with drug trafficking networks are a progressively important driver of forest loss in Central America. However, the scale at ...which drug trafficking represents a driver of forest loss is not presently known. We estimated the degree to which narcotics trafficking may contribute to forest loss using an unsupervised spatial clustering of 15 spatial and temporal forest loss patch metrics developed from global forest change data. We distinguished anomalous forest loss from background loss patches for each country exhibiting potential 'narco-capitalized' signatures which showed a statistically significant dissimilarity from other patches in terms of size, timing, and rate of forest loss. We also compared annual anomalous forest loss with the number of cocaine shipments and volume of cocaine seized, lost, or delivered at country- and department-level. For Honduras, results from linear mixed effects models showed a highly significant relationship between anomalous forest loss and the timing of increased drug trafficking (F = 9.90, p = 0.009) that also differed significantly from temporal patterns of background forest loss (t-ratio = 2.98, p = 0.004). Other locations of high forest loss in Central America showed mixed results. The timing of increased trafficking was not significantly related to anomalous forest loss in Guatemala and Nicaragua, but significantly differed in patch size compared to background losses. We estimated that cocaine trafficking could account for between 15% and 30% of annual national forest loss in these three countries over the past decade, and 30% to 60% of loss occurred within nationally and internationally designated protected areas. Cocaine trafficking is likely to have severe and lasting consequences in terms of maintaining moist tropical forest cover in Central America. Addressing forest loss in these and other tropical locations will require a stronger linkage between national and international drug interdiction and conservation policies.
Climate change is increasingly being implicated in species' range shifts throughout the world, including those of important vector and reservoir species for infectious diseases. In North America ...(México, United States, and Canada), leishmaniasis is a vector-borne disease that is autochthonous in México and Texas and has begun to expand its range northward. Further expansion to the north may be facilitated by climate change as more habitat becomes suitable for vector and reservoir species for leishmaniasis.
The analysis began with the construction of ecological niche models using a maximum entropy algorithm for the distribution of two sand fly vector species (Lutzomyia anthophora and L. diabolica), three confirmed rodent reservoir species (Neotoma albigula, N. floridana, and N. micropus), and one potential rodent reservoir species (N. mexicana) for leishmaniasis in northern México and the United States. As input, these models used species' occurrence records with topographic and climatic parameters as explanatory variables. Models were tested for their ability to predict correctly both a specified fraction of occurrence points set aside for this purpose and occurrence points from an independently derived data set. These models were refined to obtain predicted species' geographical distributions under increasingly strict assumptions about the ability of a species to disperse to suitable habitat and to persist in it, as modulated by its ecological suitability. Models successful at predictions were fitted to the extreme A2 and relatively conservative B2 projected climate scenarios for 2020, 2050, and 2080 using publicly available interpolated climate data from the Third Intergovernmental Panel on Climate Change Assessment Report. Further analyses included estimation of the projected human population that could potentially be exposed to leishmaniasis in 2020, 2050, and 2080 under the A2 and B2 scenarios. All confirmed vector and reservoir species will see an expansion of their potential range towards the north. Thus, leishmaniasis has the potential to expand northwards from México and the southern United States. In the eastern United States its spread is predicted to be limited by the range of L. diabolica; further west, L. anthophora may play the same role. In the east it may even reach the southern boundary of Canada. The risk of spread is greater for the A2 scenario than for the B2 scenario. Even in the latter case, with restrictive (contiguous) models for dispersal of vector and reservoir species, and limiting vector and reservoir species occupancy to only the top 10% of their potential suitable habitat, the expected number of human individuals exposed to leishmaniasis by 2080 will at least double its present value.
These models predict that climate change will exacerbate the ecological risk of human exposure to leishmaniasis in areas outside its present range in the United States and, possibly, in parts of southern Canada. This prediction suggests the adoption of measures such as surveillance for leishmaniasis north of Texas as disease cases spread northwards. Potential vector and reservoir control strategies-besides direct intervention in disease cases-should also be further investigated.
Prioritizing areas for management of non-native invasive plants is critical, as invasive plants can negatively impact plant community structure. Extensive and multi-jurisdictional inventories are ...essential to prioritize actions aimed at mitigating the impact of invasions and changes in disturbance regimes. However, previous work devoted little effort to devising sampling methods sufficient to assess the scope of multi-jurisdictional invasion over extensive areas. Here we describe a large-scale sampling design that used species occurrence data, habitat suitability models, and iterative and targeted sampling efforts to sample five species and satisfy two key management objectives: 1) detecting non-native invasive plants across previously unsampled gradients, and 2) characterizing the distribution of non-native invasive plants at landscape to regional scales. Habitat suitability models of five species were based on occurrence records and predictor variables derived from topography, precipitation, and remotely sensed data. We stratified and established field sampling locations according to predicted habitat suitability and phenological, substrate, and logistical constraints. Across previously unvisited areas, we detected at least one of our focal species on 77% of plots. In turn, we used detections from 2011 to improve habitat suitability models and sampling efforts in 2012, as well as additional spatial constraints to increase detections. These modifications resulted in a 96% detection rate at plots. The range of habitat suitability values that identified highly and less suitable habitats and their environmental conditions corresponded to field detections with mixed levels of agreement. Our study demonstrated that an iterative and targeted sampling framework can address sampling bias, reduce time costs, and increase detections. Other studies can extend the sampling framework to develop methods in other ecosystems to provide detection data. The sampling methods implemented here provide a meaningful tool when understanding the potential distribution and habitat of species over multi-jurisdictional and extensive areas is needed for achieving management objectives.
Recruitment limitation, which occurs when species either fail to reach regeneration sites or the number of suitable regeneration sites is limited, has been proposed as an important factor that ...controls population dynamics and species coexistence in tropical moist forests. Dwarf palms in some Neotropical forests dominate the understory strata, and their umbrella-like architecture may intensify understory shade and make the site less suitable for seedling regeneration. In this study we surveyed seedlings under dwarf palms in four habitats at La Selva Biological Station, Costa Rica. We compared seedling recruitment in both 2001 and 2002 at non-palm microsites vs microsites under 1) tall dwarf palms, 2) short dwarf palms, and 3) short palms surrounded by dwarf palms. Light environments at non-palm and under-palm sites were quantified with hemispherical photos. Seedling growth, survivorship, density, and species richness all differed significantly among microsites, and were all greatest at non-palm sites and lowest at dense palm sites. Overall, seedling growth, survivorship, density, and species richness were 30%, 50%, 50%, and 40%, respectively, less at under-palm than at non-palm sites. The main restriction by dwarf palms occurred on post-cotyledonous and woody seedlings. Percent canopy openness differed among microsites, and was greatest at non-palm sites and lowest at dense palm sites. However, seedling responses were only weakly correlated with percent canopy openness. These results revealed significant reduction in seedling recruitment under individual dwarf palms, with greatest negative effects where a palm was surrounded by palms. Dwarf palms occur at high density (2611 individuals/ha) and cover 21% of the understory in the four habitats (alluvium, residual flat area, residual slope area, swamp) of the primary forest. Therefore, this negative impact by individual dwarf palms is significant at the landscape scale as well, based on the great dwarf palm density and coverage in the four habitats.
The number of travel-acquired dengue infections has been on a constant rise in the United States and Europe over the past decade. An increased volume of international passenger air traffic ...originating from regions with endemic dengue contributes to the increasing number of dengue cases. This paper reports results from a network-based regression model which uses international passenger travel volumes, travel distances, predictive species distribution models (for the vector species), and infection data to quantify the relative risk of importing travel-acquired dengue infections into the US and Europe from dengue-endemic regions. Given the necessary data, this model can be used to identify optimal locations (origin cities, destination airports, etc.) for dengue surveillance. The model can be extended to other geographical regions and vector-borne diseases, as well as other network-based processes.
While studying ecological patterns at large scales, ecologists are often unable to identify all collections, forcing them to either omit these unidentified records entirely, without knowing the ...effect of this, or pursue very costly and time‐consuming efforts for identifying them. These “indets” may be of critical importance, but as yet, their impact on the reliability of ecological analyses is poorly known. We investigated the consequence of omitting the unidentified records and provide an explanation for the results. We used three large‐scale independent datasets, (Guyana/ Suriname, French Guiana, Ecuador) each consisting of records having been identified to a valid species name (identified morpho‐species – IMS) and a number of unidentified records (unidentified morpho‐species – UMS). A subset was created for each dataset containing only the IMS, which was compared with the complete dataset containing all morpho‐species (AMS: = IMS + UMS) for the following analyses: species diversity (Fisher's alpha), similarity of species composition, Mantel test and ordination (NMDS). In addition, we also simulated an even larger number of unidentified records for all three datasets and analyzed the agreement between similarities again with these simulated datasets. For all analyses, results were extremely similar when using the complete datasets or the truncated subsets. IMS predicted ≥91% of the variation in AMS in all tests/analyses. Even when simulating a larger fraction of UMS, IMS predicted the results for AMS rather well. Using only IMS also out‐performed using higher taxon data (genus‐level identification) for similarity analyses. Finding a high congruence for all analyses when using IMS rather than AMS suggests that patterns of similarity and composition are very robust. In other words, having a large number of unidentified species in a dataset may not affect our conclusions as much as is often thought.
By using three often used macro‐ecological analyses, we show that omitting unidentified species from datasets does not affect our conclusions as much as is often thought. Results were extremely similar using either the complete dataset or only named taxa on species level. We also show that using a higher taxon‐level approach, similarity values are much more deviating from what was expected based on the all taxa dataset in comparison to using only the named dataset.
Drainage in tropical peatlands increases CO.sub.2 emissions, the rate of subsidence, and the risk of forest fires. To a certain extent, these effects can be mitigated by raising the water table depth ...(WTD) using canal or ditch blocks. The performance of canal blocks in raising WTD is, however, poorly understood because the WTD monitoring data are limited and spatially concentrated around canals and canal blocks. This raises the following question: how effective are canal blocks in raising the WTD over large areas? In this work, we composed a process-based hydrological model to assess the peatland restoration performance of 168 canal blocks in a 22 000 ha peatland area in Sumatra, Indonesia. We simulated daily WTD over 1 year using an existing canal block setup and compared it to the situation without blocks. The study was performed across two contrasting weather scenarios representing dry (1997) and wet (2013) years. Our simulations revealed that, while canal blocks had a net positive impact on WTD rise, they lowered WTD in some areas, and the extent of their effect over 1 year was limited to a distance of about 600 m around the canals. We also show that canal blocks are most effective in peatlands with high hydraulic conductivity. Averaging over all modeled scenarios, blocks raised the annual mean WTD by only 1.5 cm. This value was similar in the dry (1.44 cm) and wet (1.57 cm) years, and there was a 2.13 fold difference between the scenarios with large and small hydraulic conductivities (2.05 cm versus 0.96 cm). Using a linear relationship between WTD and CO.sub.2 emissions, we estimated that, averaging over peat hydraulic properties, canal blocks prevented the emission of 1.07 Mg ha.sup.-1 CO.sub.2 in the dry year and 1.17 Mg ha.sup.-1 CO.sub.2 in the wet year. We believe that the modeling tools developed in this work could be adopted by local stakeholders aiming at a more effective and evidence-based approach to canal-block-based peatland restoration.
Drainage in tropical peatlands increases CO2 emissions, the rate of subsidence, and the risk of forest fires. To a certain extent, these effects can be mitigated by raising the water table depth ...(WTD) using canal or ditch blocks. The performance of canal blocks in raising WTD is, however, poorly understood because the WTD monitoring data are limited and spatially concentrated around canals and canal blocks. This raises the following question: how effective are canal blocks in raising the WTD over large areas? In this work, we composed a process-based hydrological model to assess the peatland restoration performance of 168 canal blocks in a 22 000 ha peatland area in Sumatra, Indonesia. We simulated daily WTD over 1 year using an existing canal block setup and compared it to the situation without blocks. The study was performed across two contrasting weather scenarios representing dry (1997) and wet (2013) years. Our simulations revealed that, while canal blocks had a net positive impact on WTD rise, they lowered WTD in some areas, and the extent of their effect over 1 year was limited to a distance of about 600 m around the canals. We also show that canal blocks are most effective in peatlands with high hydraulic conductivity. Averaging over all modeled scenarios, blocks raised the annual mean WTD by only 1.5 cm. This value was similar in the dry (1.44 cm) and wet (1.57 cm) years, and there was a 2.13 fold difference between the scenarios with large and small hydraulic conductivities (2.05 cm versus 0.96 cm). Using a linear relationship between WTD and CO2 emissions, we estimated that, averaging over peat hydraulic properties, canal blocks prevented the emission of 1.07 Mg ha−1 CO2 in the dry year and 1.17 Mg ha−1 CO2 in the wet year. We believe that the modeling tools developed in this work could be adopted by local stakeholders aiming at a more effective and evidence-based approach to canal-block-based peatland restoration.
Drug Policy as Conservation Policy: Narco-Deforestation McSweeney, Kendra; Nielsen, Erik A.; Taylor, Matthew J. ...
Science (American Association for the Advancement of Science),
01/2014, Letnik:
343, Številka:
6170
Journal Article
Recenzirano
Drug trafficking is taking a toll on Central America's biodiverse forests.
The watershed 2013 report,
The Drug Problem in the Americas
(
1
), highlights a shift toward multilateral support for ...hemispheric drug policy reform. This report by the Organization of American States (OAS) reviews failures of the U.S.-led prohibitionist “war on drugs” and urges states to reconsider orthodox “supply-side” strategies (including interdiction and drug crop eradication), and to focus more on demand-side policy experimentation. In Central America, a key zone of drug transit that is being ripped apart by narco-fueled violence and corruption (
2
,
3
), the push for reform signals hope that the conditions fueling drug traffickers' profits and corrosive political influence may eventually be dismantled (
4
).
Drainage in tropical peatlands increases CO2 emissions, the rate of subsidence, and the risk of forest fires. To a certain extent, these effects can be mitigated by raising the water table depth ...(WTD) using canal or ditch blocks. The performance of canal blocks in raising WTD is, however, poorly understood because the WTD monitoring data are limited and spatially concentrated around canals and canal blocks. This raises the following question: how effective are canal blocks in raising the WTD over large areas? In this work, we composed a process-based hydrological model to assess the peatland restoration performance of 168 canal blocks in a 22 000 ha peatland area in Sumatra, Indonesia. We simulated daily WTD over 1 year using an existing canal block setup and compared it to the situation without blocks. The study was performed across two contrasting weather scenarios representing dry (1997) and wet (2013) years. Our simulations revealed that, while canal blocks had a net positive impact on WTD rise, they lowered WTD in some areas, and the extent of their effect over 1 year was limited to a distance of about 600 m around the canals. We also show that canal blocks are most effective in peatlands with high hydraulic conductivity. Averaging over all modeled scenarios, blocks raised the annual mean WTD by only 1.5 cm. This value was similar in the dry (1.44 cm) and wet (1.57 cm) years, and there was a 2.13 fold difference between the scenarios with large and small hydraulic conductivities (2.05 cm versus 0.96 cm). Using a linear relationship between WTD and CO2 emissions, we estimated that, averaging over peat hydraulic properties, canal blocks prevented the emission of 1.07 Mgha-1 CO2 in the dry year and 1.17 Mgha-1 CO2 in the wet year. We believe that the modeling tools developed in this work could be adopted by local stakeholders aiming at a more effective and evidence-based approach to canal-block-based peatland restoration.
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