Drainage Investment and Wetlands Loss: an Analysis of the National Resources Inventory Data

Douglas, Aaron J.; Johnson, Richard L.

doi:10.1006/jema.1994.1027

Cited by 5 publications

(6 citation statements)

References 13 publications

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“…). The temporal changes in bird species composition indicate that the drying and draining of wetlands negatively affect biodiversity, a finding that is in line with patterns observed in other wetlands globally (Douglas & Johnson ; Gerakis & Kalburtji ; Smith & Chow‐Fraser ).…”

Section: Discussionsupporting

confidence: 82%

Changes in bird assemblages in a wetland ecosystem after 14 years of intensified cattle farming

et al. 2018

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Human activities have modified wetlands all over the word. Water control structures that are frequently implemented in these ecosystems to keep lands free of flooding can decrease or degrade habitat for biodiversity. The Paran a River Delta, one of the largest wetlands in Argentina, has recently experienced rapid cattle grazing intensification facilitated by water control structures, resulting in extensive conversion of wetlands to pastures. It is unclear if this loss of wetlands has had a negative impact on the highly diverse bird community. Here, we evaluated the changes in bird assemblages in the Lower Delta of Paran a River after 14 years of cattle grazing intensification. We compared point count data from 1997 to 1999 with data collected in 2012 and 2013 using the same survey methods. We assessed the temporal changes in bird richness and composition using paired permutation tests and multivariate analysis. We related the bird composition to landscape changes to analyse if avian changes were associated with landscape dynamics. We found that after 14 years, the bird community differed greatly. In general, species richness decreased, especially in wet years. We found fewer wetland species in recent surveys; in particular we did not register saffron-cowled blackbird (Xanthopsar flavus), a species listed as globally vulnerable. Changes in bird composition were associated with an increase in bare soil due to land-use changes. Even though inter-annual differences in precipitation and river stage have great effects on the species present in the surveys, the absence of many wetland species in recent wet years, that is when habitat is suitable for them, is most likely due to changes in land cover. Globally, agricultural land use makes inroads into many wetlands, eroding their quality and extent. Maintenance of wetland species requires that conservation efforts focus on these vulnerable ecosystems before full-scale land conversion occurs.

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Section: Discussionsupporting

confidence: 82%

Changes in bird assemblages in a wetland ecosystem after 14 years of intensified cattle farming

et al. 2018

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“…Likewise, wetlands in cultivated fields or pastures were expected to have higher impact rates than wetlands located in idle grasslands or wooded areas. Finally, we expected jurisdictional differences in rates and incidence of impact to wetlands due to provincial differences in agricultural and wetland protection policies as well as other socioeconomic drivers (Douglas andJohnson 1994, Bradshaw andSmit 1997).…”

Section: Hypotheses and Predictionsmentioning

confidence: 99%

“…Fluctuating commodity prices for agricultural products and agricultural subsidies may influence rates of wetland impact (Bradshaw andSmit 1997, Drever et al 2007). Wetland size and distance to roads could also influence impact and recovery (Douglas andJohnson 1994, Daniels andCumming 2008). These factors could be considered as covariates in future analyses.…”

Section: Implications For Managementmentioning

confidence: 99%

Trends in agricultural impact and recovery of wetlands in prairie Canada

Bartzen

Dufour

Clark

et al. 2010

Ecological Applications

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Despite widespread recognition that they provide valuable ecosystem services and contribute significantly to global biodiversity, over half of the world's wetlands have been lost, primarily to agriculture. Wetland loss is evident in prairie Canada, but comprehensive information about causes of ongoing impact for existing wetlands is lacking. Habitat data collected for approximately 10,500 wetlands during annual waterfowl surveys (1985-2005) were analyzed using multistate models to estimate rates of wetland impact and recovery from agricultural activities in the Canadian prairies. An impact was defined as an agricultural activity that visibly altered a wetland margin (natural vegetation surrounding wetland interiors) or basin (interior depression capable of holding water), whereas recovery was deemed to have occurred if agricultural activities had ceased and effects were no longer visibly apparent. We estimated separate impact and recovery rates for wetland basins and wetland margins and considered covariates such as location, time, wetness indices, land use, and wetland permanence. Results indicate that impact rates for wetland margins have declined over time, likely due to a decreasing percentage of unaffected wetlands on the landscape. Recovery rates for margins were always lower than impact rates, suggesting progressive incidence of impacts to wetlands over time. Unlike margins, impact and recovery rates for basins fluctuated with May pond densities, which we used as a wetness index. Shallow ephemeral wetlands located in agricultural fields had the highest impact and lowest recovery rates relative to wetlands with higher water permanence or situated in areas of lower agricultural intensity. High rates and incidence of wetland impact in conjunction with low recovery rates clearly demonstrate the need for stronger wetland protection in prairie Canada.

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“…If land-use policy and planning are to be efficient in conserving wetland habitats, it is imperative to identify, in a geographically explicit fashion, those areas where the risks of future wetland habitat conversion are highest. Recent efforts to develop predictive models of wetland conversion have considered physical and socioeconomic variables (Douglas and Johnson 1994) and suites of environmental variables that reflect wetland type, soil and topographic conditions, landuse and land-cover characteristics, and the spatial proximity of roads and cities (Koneff andRoyle 2004, Daniels andCumming 2008). Variation in wetland loss rates at the spatial extent of states in the USA was associated strongly with three variables: land drained (drainage investment), wetland rural acreage, and farmland realty value (Douglas and Johnson 1994).…”

Section: Introductionmentioning

confidence: 99%

“…Recent efforts to develop predictive models of wetland conversion have considered physical and socioeconomic variables (Douglas and Johnson 1994) and suites of environmental variables that reflect wetland type, soil and topographic conditions, landuse and land-cover characteristics, and the spatial proximity of roads and cities (Koneff andRoyle 2004, Daniels andCumming 2008). Variation in wetland loss rates at the spatial extent of states in the USA was associated strongly with three variables: land drained (drainage investment), wetland rural acreage, and farmland realty value (Douglas and Johnson 1994). Elevation and a wetness index (derived from slope and location in a watershed) were important predictors of wetland occurrence in Atlantic Coast states (Koneff and Royle 2004).…”

Section: Introductionmentioning

confidence: 99%

Wetland features and landscape context predict the risk of wetland habitat loss

Gutzwiller

Flather

2011

Ecological Applications

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Wetlands generally provide significant ecosystem services and function as important harbors of biodiversity. To ensure that these habitats are conserved, an efficient means of identifying wetlands at risk of conversion is needed, especially in the southern United States where the rate of wetland loss has been highest in recent decades. We used multivariate adaptive regression splines to develop a model to predict the risk of wetland habitat loss as a function of wetland features and landscape context. Fates of wetland habitats from 1992 to 1997 were obtained from the National Resources Inventory for the U.S. Forest Service's Southern Region, and land-cover data were obtained from the National Land Cover Data. We randomly selected 70% of our 40 617 observations to build the model (n = 28 432), and randomly divided the remaining 30% of the data into five Test data sets (n = 2437 each). The wetland and landscape variables that were important in the model, and their relative contributions to the model's predictive ability (100 = largest, 0 = smallest), were land-cover/ land-use of the surrounding landscape (100.0), size and proximity of development patches within 570 m (39.5), land ownership (39.1), road density within 570 m (37.5), percent woody and herbaceous wetland cover within 570 m (27.8), size and proximity of development patches within 5130 m (25.7), percent grasslands/herbaceous plants and pasture/hay cover within 5130 m (21.7), wetland type (21.2), and percent woody and herbaceous wetland cover within 1710 m (16.6). For the five Test data sets, Kappa statistics (0.40, 0.50, 0.52, 0.55, 0.56; P < 0.0001), area-under-the-receiver-operating-curve (AUC) statistics (0.78, 0.82, 0.83, 0.83, 0.84; P < 0.0001), and percent correct prediction of wetland habitat loss (69.1, 80.4, 81.7, 82.3, 83.1) indicated the model generally had substantial predictive ability across the South. Policy analysts and land-use planners can use the model and associated maps to prioritize at-risk wetlands for protection, evaluate wetland habitat connectivity, predict future conversion of wetland habitat based on projected land-use trends, and assess the effectiveness of wetland conservation programs.

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Drainage Investment and Wetlands Loss: an Analysis of the National Resources Inventory Data

Cited by 5 publications

References 13 publications

Changes in bird assemblages in a wetland ecosystem after 14 years of intensified cattle farming

Changes in bird assemblages in a wetland ecosystem after 14 years of intensified cattle farming

Trends in agricultural impact and recovery of wetlands in prairie Canada

Wetland features and landscape context predict the risk of wetland habitat loss

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