Persistence and quality of vegetation cover in expired Conservation Reserve Program fields

For nearly 40 years, the Conservation Reserve Program (CRP) has implemented practices to reduce soil erosion, improve water quality, and provide habitat for wildlife and pollinators on highly erodible cropland in the United States. However, an approximately 40,470 ha (10 million acres) decline in enrolled CRP land over the last decade has greatly reduced the program\u27s environmental benefits. We sought to assess the program\u27s enduring benefits in the central and western United States by (1) determining the proportion of fields that persist in CRP cover after contracts expired, (2) identifying the type of agricultural production that CRP fields shift to after contract expiration, (3) comparing the vegetation characteristics of expired CRP fields that are persisting in CRP-type cover with enrolled CRP fields, and (4) identifying differences in management activities (e.g., haying, grazing) between expired and enrolled CRP fields. We conducted edge-of-field vegetation cover surveys in 1092 CRP fields with contracts that expired ≥3 years prior and 1786 currently enrolled CRP fields in 14 states. We found that 41% of expired CRP fields retained at least half of their area in CRP-type cover, with significant variation in persistence among regions ranging from 19% to 84%. When expired fields retained CRP vegetation, bare ground was low in all regions and grass cover was somewhat greater than in fields with current CRP contracts, but at the expense of forb cover in some regions. Evidence of more frequent management in expired CRP fields may explain differences between active and expired CRP fields. Overall, there is clear evidence that CRP-type cover frequently persists and provides benefits for more than three years after contract expiration. Retaining CRP-type cover, post-contract, is an under-recognized program benefit that persists across the central and western United States long after the initial retirement from cropland

Restored Agricultural Wetlands in central Iowa: Habitat Quality and Amphibian Response

Amphibians are declining throughout the United States and worldwide due, partly, to habitat loss. Conservation practices on the landscape restore wetlands to denitrify tile drainage effluent and restore ecosystem services. Understanding how water quality, hydroperiod, predation, and disease affect amphibians in restored wetlands is central to maintaining healthy amphibian populations in the region. We examined the quality of amphibian habitat in restored wetlands relative to reference wetlands by comparing species richness, developmental stress, and adult leopard frog (Lithobates pipiens) survival probabilities to a suite of environmental metrics. Although measured habitat variables differed between restored and reference wetlands, differences appeared to have sub-lethal rather than lethal effects on resident amphibian populations. There were few differences in amphibian species richness and no difference in estimated survival probabilities between wetland types. Restored wetlands had more nitrate and alkaline pH, longer hydroperiods, and were deeper, whereas reference wetlands had more amphibian chytrid fungus zoospores in water samples and resident amphibians exhibited increased developmental stress. Restored and reference wetlands are both important components of the landscape in central Iowa and maintaining a complex of fish-free wetlands with a variety of hydroperiods will likely contribute to the persistence of amphibians in this landscape

Allelopathic Cover Crop Prior to Seeding Is More Important Than Subsequent Grazing/Mowing in Grassland Establishment

The effects of grazing, mowing, and type of cover crop were evaluated in a previous winter wheat-fallow cropland seeded to grassland under the Conservation Reserve Program in eastern Colorado. Prior to seeding, the fallow strips were planted to forage sorghum or wheat in alternating strips (cover crops), with no grazing, moderate to heavy grazing, and mowing (grazing treatments) superimposed 4 yr after planting and studied for 3 yr. Plots previously in wheat had more annual and exotic species than sorghum plots. Concomitantly, there were much greater abundances of perennial native grass and all native species in sorghum than wheat cropped areas. The competitive advantage gained by seeded species in sorghum plots resulted in large increases in rhizomatous western wheatgrass. Sorghum is known to be allelopathic and is used in crop agriculture rotations to suppress weeds and increase crop yields, consistent with the responses of weed and desired native species in this study. Grazing treatment had relatively minor effects on basal and canopy cover composition of annual or exotic species versus perennial native grass or native species. Although grazing treatment never was a significant main effect, it occasionally modified cover crop or year effects. Opportunistic grazing reduced exotic cheatgrass by year 3 but also decreased the native palatable western wheatgrass. Mowing was a less effective weed control practice than grazing. Vegetative basal cover and aboveground primary production varied primarily with year. Common management practices for revegetation/restoration currently use herbicides and mowing as weed control practices and restrict grazing in all stages of development. Results suggest that allelopathic cover crop selection and opportunistic grazing can be effective alternative grass establishment and weed control practices. Susceptibility, resistance, and interactions of weed and seeded species to allelopathic cover species/cultivars may be a fruitful area of research.The Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information.Migrated from OJS platform August 202

Comparing modern identification methods for wild bees: Metabarcoding and image-based morphological taxonomic assignment.

With the decline of bee populations worldwide, studies determining current wild bee distributions and diversity are increasingly important. Wild bee identification is often completed by experienced taxonomists or by genetic analysis. The current study was designed to compare two methods of identification including: (1) morphological identification by experienced taxonomists using images of field-collected wild bees and (2) genetic analysis of composite bee legs (multiple taxa) using metabarcoding. Bees were collected from conservation grasslands in eastern Iowa in summer 2019 and identified to the lowest taxonomic unit using both methods. Sanger sequencing of individual wild bee legs was used as a positive control for metabarcoding. Morphological identification of bees using images resulted in 36 unique taxa among 22 genera, and >80% of Bombus specimens were identified to species. Metabarcoding was limited to genus-level assignments among 18 genera but resolved some morphologically similar genera. Metabarcoding did not consistently detect all genera in the composite samples, including kleptoparasitic bees. Sanger sequencing showed similar presence or absence detection results as metabarcoding but provided species-level identifications for cryptic species (i.e., Lasioglossum). Genus-specific detections were more frequent with morphological identification than metabarcoding, but certain genera such as Ceratina and Halictus were identified equally well with metabarcoding and morphology. Genera with proportionately less tissue in a composite sample were less likely to be detected using metabarcoding. Image-based methods were limited by image quality and visible morphological features, while genetic methods were limited by databases, primers, and amplification at target loci. This study shows how an image-based identification method compares with genetic techniques, and how in combination, the methods provide valuable genus- and species-level information for wild bees while preserving tissue for other analyses. These methods could be improved and transferred to a field setting to advance our understanding of wild bee distributions and to expedite conservation research

Number of vials in which a bee genus was detected using DNA metabarcoding (blue) and morphological identification (orange).

Bees were morphologically identified using images, and a leg from each bee was composited. Vials contained composite bee legs from one or more genera, and genera richness was assessed in each sample that had a genetic detection (n = 84).</p

Difference in the number of bee genera detected per site visit with two identification methods (morphological minus metabarcoding).

Comparisons were made for 47 site visits where bees were captured. Most site visits included both a large and a small composite vial. Positive values along the x-axis indicated how many additional genera were identified using morphological identification compared to metabarcoding.</p

Comparing the number of wild bee genera not detected through metabarcoding to the number of bee legs in the composite sample.

Composite samples included tissue from multiple taxa. Composite samples either contained legs from large bees (intertegular distance >3 mm) or small bees (intertegular distance ≤3 mm). (TIF)</p

Aggregate sequence counts for bee genera from six workflows.

Some workflows were restricted by the regional bee list while others were unrestricted. The full nucleotide (nt) database was searched, and then matches were "filtered" to only include accessions of taxa included on the regional bee list. Two custom databases were assessed: 1) an inclusive version generated from GenBank with a minimum length of 250 bases and 2) a curated version that was generated from both GenBank and Barcodes of Life databases, with a threshold of 400 bases and dereplicated within species. The final counts table used in this study was derived from the lowest common ancestor (LCA) method with the curated database. The RDP Classifier (Wang et al., 2007) is a Bayesian kmer-based classifier that requires prior training, for which the CO1 v.5 database of Porter and Hajibabaei (2018) was used. SINTAX (Edgar, 2016) is an alternative kmer-based classifier that does not require an external training set. (PDF)</p

The difference in the number of bee genera detected with two identification methods (image-based morphological identification and DNA metabarcoding) in composite vials from site visits in July ("J") and August ("A").

Site visits without bars show that the number of bee genera detected with the two identification methods was the same. Positive values along the x-axis indicate more genera were detected by morphological identification than metabarcoding. Data were used to create Fig 2. (TIF)</p