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Phosphatidylinositol‐4,5‐bisphosphate, PtdIns(4,5)P2, is an essential signalling lipid that regulates key processes such as endocytosis, exocytosis, actin cytoskeletal organization and calcium signalling. Maintaining proper levels of PtdIns(4,5)P2 at the plasma membrane (PM) is crucial for cell survival and growth. We show that the conserved PtdIns(4)P 5‐kinase, Mss4, forms dynamic, oligomeric structures at the PM that we term PIK patches. The dynamic assembly and disassembly of Mss4 PIK patches may provide a mechanism to precisely modulate Mss4 kinase activity, as needed, for localized regulation of PtdIns(4,5)P2 synthesis. Furthermore, we identify a tandem PH domain‐containing protein, Opy1, as a novel Mss4‐interacting protein that partially colocalizes with PIK patches. Based upon genetic, cell biological, and biochemical data, we propose that Opy1 functions as a coincidence detector of the Mss4 PtdIns(4)P 5‐kinase and PtdIns(4,5)P2 and serves as a negative regulator of PtdIns(4,5)P2 synthesis at the PM. Our results also suggest that additional conserved tandem PH domain‐containing proteins may play important roles in regulating phosphoinositide signalling.
Phosphorylated derivatives of phosphatidylinositol, collectively known as phosphoinositide (PIP) lipids, regulate cell polarity, growth and development, and membrane trafficking (Martin, 1998; Behnia and Munro, 2005; Di Paolo and De Camilli, 2006; Vicinanza et al, 2008). A wide range of protein effectors are directly regulated by PIP lipids through conserved PIP‐binding modules that specify effector recruitment and activation at distinct organelle membranes (Lemmon, 2008). However, how levels of distinct PIP isoforms are accurately maintained by the opposing actions of PIP kinases and PIP phosphatases is not fully understood. One of the major PIP speies, PtdIns(4,5)P2, is enriched in the inner leaflet of the plasma membrane (PM). PtdIns(4,5)P2 was initially shown to function as a precursor of the second messengers diacylglycerol (DAG) and 1,4,5‐inositol trisphosphate (IP3) generated by phospholipase C (Hokin, 1985). More recent studies have highlighted direct roles for PtdIns(4,5)P2 in the regulation of the endocytic machinery (Haucke, 2005), exocytosis (Liu et al, 2007; James et al, 2008), the actin cytoskeleton (Yin and Janmey, 2003) and septin assembly during cell division (Logan and Mandato, 2006; Bertin et al, 2010).
In the yeast Saccharomyces cerevisiae, PtdIns(4,5)P2 is synthesized by the conserved PtdIns(4)P 5‐kinase Mss4. Mss4 localizes to the PM and generates essential pools of PtdIns(4,5)P2 (Desrivieres et al, 1998; Homma et al, 1998; Audhya and Emr, 2002). Mss4 also undergoes nuclear‐cytoplasmic shuttling and nuclear sequestration may control Mss4 function (Audhya and Emr, 2003). However, little is known about how regulation of Mss4 at the PM is achieved. We have found that Mss4 assembles into oligomeric protein complexes at the PM that we term PIK (PIP kinase) patches. Mss4 PIK patches are dynamic and are distinct from other previously described cortical structures, such as actin patches (Pruyne and Bretscher, 2000a, 2000b) and eisosomes (Walther et al, 2006). Assembly of Mss4 PIK patches requires the C‐terminus of Mss4 and its substrate PtdIns(4)P. In addition, by genetic and quantitative proteomic approaches, we identify the dual PH domain‐containing protein Opy1 as a novel regulator of Mss4. We propose that assembly of Mss4 PIK patches permits coordinate regulation of multiple Mss4 kinase molecules by accessory factors, including the conserved Opy1 protein.
Mss4 forms dynamic protein complexes, PIK patches, at the PM
Mss4 is a cytoplasmic protein that associates with the inner face of the PM (Audhya and Emr, 2003). To understand how Mss4 is regulated, we employed cells solely expressing a functional Mss4–GFP fusion. Mss4–GFP formed cortical, punctate structures at the PM: PIK (phosphoinositide kinase) patches (Figure 1A, observed at both mid and top sections of cells; Supplementary Movie S1) similar to previously reported patterns for Mss4 localization (Audhya and Emr, 2002; Sun et al, 2007; Smaczynska‐de et al, 2008). Reconstructions (2D projections of Z series) of cells expressing Mss4–GFP indicated that there are ∼30–50 Mss4 PIK patches in each individual yeast cell. However, the oligomeric status or the dynamics of Mss4 PIK patches at the PM has not been addressed. To determine whether multiple copies of Mss4 assemble at PIK patches, we tested if an Mss4–13xmyc fusion isolated with an Mss4–3xHA fusion in coimmunoprecipitation experiments. Mss4–13xmyc was present in anti‐HA immunoprecipitates from cell lysates coexpressing Mss4–3xHA, but not from control cell lysates lacking Mss4–3xHA (Figure 1B), suggesting that Mss4 oligomerizes. To estimate the copy numbers of Mss4 molecules present in PIK patches, we expressed Mss4–GFP in cells coexpressing a Cse4–3xGFP fusion (both are integrated; Supplementary Figure S1A). Cse4–3xGFP forms a complex containing 96 GFP molecules in the nucleus of yeast cells (Markus et al, 2009). By comparing the GFP signal intensities of Mss4 PIK patches and Cse4–3xGFP in the nucleus, we found a distribution of ∼5–30 copies of Mss4–GFP in each PIK patch (Figure 1C). However, most PIK patches contained ∼10–20 Mss4–GFP molecules (Figure 1C). Thus, multiple copies of the Mss4 lipid kinase assemble at PIK patches.
Source Data for Figure 1 [emboj2012127-sup-0009.pdf]
To address the dynamics of Mss4 PIK patches, we performed time‐lapse imaging experiments following Mss4–GFP at the cell surface by focusing on the top of cells. Strikingly, Mss4 PIK patches were highly dynamic and short‐lived structures (Supplementary Movie S2). More than 75% of Mss4 PIK patches appear to change localization within 30 s (Figure 1D), and the lifetime of Mss4 PIK patches range from 10 to 40 s (Figure 1E; Supplementary Figure S3A). This dramatic rearrangement in distribution likely occurs by the dynamic assembly and disassembly of Mss4 PIK patches as well as lateral movements along the surface of the PM, as Mss4 PIK patches did not move into the interior of the cell by following Mss4–GFP in mid sections of cells (Supplementary Movie S3). Mss4 PIK patches were distinct from cortical actin patches (Pruyne and Bretscher, 2000a, 2000b) and did not require actin polymerization for assembly (Supplementary Figure S1B). Likewise, Mss4 PIK patches were distinct from eisosomes and independent of the eisosome component Pil1 (Supplementary Figure S1C and D). These results suggested that Mss4 assembles into unique dynamic structures at the PM. We thus sought to further understand how Mss4 organization and function are regulated.
The Mss4 kinase domain and PtdIns(4)P are required for PIK patch assembly
Mss4 consists of an uncharacterized N‐terminal domain, a central nuclear localization signal (NLS), and a conserved C‐terminal PIP 5‐kinase domain (Figure 2A). To map regions in Mss4 necessary for PIK patch assembly, we generated a series of truncated Mss4 mutants tagged with GFP. The large N‐terminal region of Mss4 (residues 2–346) and the NLS in Mss4 (residues 347–364) were dispensable for PM localization (Figure 2A). In contrast, a mutant form lacking the last 54 amino acids of Mss4 (residues 726–779), did not localize to the PM and instead accumulated in the cytoplasm and nucleus (Figure 2A). We then tested if the truncated Mss4–GFP fusions were functional using a plasmid shuffle growth assay. For this, we transformed an mss4Δ strain carrying an URA3‐marked wild‐type MSS4 plasmid or with plasmids encoding truncated forms of Mss4–GFP. As expected, cells expressing Mss4Δ726–779–GFP alone failed to grow on 5‐FOA media (due to loss of the URA3‐marked wild‐type MSS4 plasmid). However, neither the N‐terminal region nor the NLS were required for Mss4 function, as cells expressing mutant forms of Mss4 lacking these regions were able to grow on 5‐FOA plates (Figure 2B).
The truncation resulting in Mss4 mislocalization occurs in a conserved region of the C‐terminus, termed the activation loop (Supplementary Figure S2A; Kunz et al, 2000). The activation loops of mammalian PtdIns(4)P 5‐kinases control substrate recognition and subcellular targeting (Kunz et al, 2000). Substitution of two highly conserved lysine residues to negatively charged aspartate residues in the activation loop resulted in Mss4 mislocalization (Supplementary Figure S2B). In contrast, substitutions with arginine, retaining the positive charge, did not affect Mss4 PM localization (Supplementary Figure S2B). Thus, binding to the anionic substrate PtdIns(4)P may be important for Mss4 localization. Stt4 and Pik1 are the two major PtdIns 4‐kinases responsible for PtdIns(4)P synthesis in yeast (Audhya et al, 2000). To deplete PtdIns(4)P, we used a temperature conditional stt4tspik1ts double‐mutant strain. Mss4–GFP localized to the cytoplasm in stt4tspik1ts double‐mutant cells at the restrictive temperature (Figure 2C). However, Mss4–GFP localized to the PM in stt4ts and pik1ts single‐mutant cells at the non‐permissive temperature (Supplementary Figure S2C), suggesting that both PtdIns 4‐kinases contribute to Mss4 PM targeting. Mss4 localization was not dependent on PtdIns(4,5)P2 levels, as a kinase inactive form of Mss4–GFP localized to the PM when PtdIns(4,5)P2 is depleted in mss4ts cells (Supplementary Figure S2D; Stefan et al, 2002). Consistent with a role for PtdIns(4)P in targeting Mss4 to the PM, the purified Mss4 kinase domain, His6–SUMO–Mss4454–779, bound to PtdIns(4)P, as well as PtdIns(3)P and weakly to PtdIns(4,5)P2, in lipid overlay experiments (Supplementary Figure S2E). Thus, the C‐terminus of Mss4 and PtdIns(4)P target Mss4 to the PM.
The N‐terminal region of Mss4 functions as a negative regulatory domain
Our initial results implicated the conserved C‐terminus of Mss4 in PIK patch assembly. However, the role of the Mss4 N‐terminal region remained unclear. We further examined Mss4 regulation by performing 3H‐inositol labelling experiments to measure cellular PtdIns(4,5)P2 levels in mss4ts cells coexpressing various forms of Mss4–GFP. As expected, the C‐terminal truncated Mss4Δ726–779–GFP was defective in PtdIns(4,5)P2 synthesis (Figure 2D; Supplementary Table S1). However, deletion of the N‐terminus increased Mss4 activity, as PtdIns(4,5)P2 levels were ∼2‐fold higher in mss4ts cells expressing Mss4Δ2–346–GFP compared with cells expressing full‐length Mss4–GFP (Figure 2D; Supplementary Table S1). Both Mss4Δ726–779–GFP and Mss4Δ2–346–GFP were expressed at levels similar to full‐length Mss4–GFP, indicating that the altered activities of the mutant proteins were not due to changes in protein stability (Supplementary Figure S2F). In addition, PIK patches containing Mss4–GFP and Mss4Δ2–346–GFP displayed similar dynamics and GFP fluorescence intensity distributions (Supplementary Figure S3A and B; Supplementary Movie S4). Thus, the increase in PtdIns(4,5)P2 levels in cells expressing Mss4Δ2–346–GFP was not due to increases in Mss4 assembly or PIK patch lifetime. Elevated PtdIns(4,5)P2 levels are toxic in cells with impaired PtdIns(4,5)P2 phosphatase activity (Stefan et al, 2002). Expression of the N‐terminal truncated form but not full‐length Mss4 impaired the growth of cells deficient in PIP 5‐phosphatase function (sjl1Δ sjl2tssjl3Δ inp54Δ cells) at a semi‐permissive temperature (Figure 2E), further suggesting that deletion of the N‐terminal region results in increased Mss4 PIP kinase activity.
The PH domain‐containing protein Opy1 binds Mss4
The mechanisms of Mss4 localization and regulation at the PM are poorly characterized. We reasoned that the localization and regulation of Mss4 are mediated in part by associated factors. To identify candidate proteins that interact with Mss4, we undertook a quantitative proteomics approach (Figure 3A). Cells were grown in media containing either light (for the control strain) or heavy (for cells expressing Mss4–3xFlag) isotope amino acids. We then performed crosslinking immunopurification (IP) experiments and processed the protein samples for quantitative mass spectrometry analysis. This approach detects the enrichment of proteins that specifically interact with Mss4, and allows for the identification of weak/transient interactions. One protein, Opy1, was highly enriched with purified Mss4–3xFlag (Figure 3B). To confirm the Mss4–Opy1 interaction, we repeated the crosslinking coIP experiment and monitored the results by immunoblotting. As expected, Opy1–3xHA was present in immunoprecipitates from cells expressing Mss4–3xFlag, but not control cells lacking Mss4–3xFlag (Figure 3C).
Source Data for Figure 3 [emboj2012127-sup-0010.pdf]
Opy1 consists of two PH domains and the C‐terminal PH domain has been proposed to bind PtdIns(4,5)P2 (Figure 3D; Szentpetery et al, 2009). By examining full‐length Opy1–GFP in vivo, we observed Opy1 in the cytoplasm and at cortical punctate structures (Figure 3D). Interestingly, the cortical Opy1 structures partially colocalized with Mss4 PIK patches at the PM (Supplementary Figure S3D), Taken together, these results suggested that Opy1 interacts with Mss4 at PIK patches.
Opy1 is a novel regulator of PtdIns(4,5)P2 synthesis
To study the function of Opy1 in vivo, we first deleted the OPY1 gene. Mss4 assembled into PIK patches at the PM in cells lacking OPY1 with wild‐type dynamics and Mss4–GFP fluorescence intensities, and thus Opy1 was not essential for Mss4 PIK patch formation (Supplementary Figure S3A and C; Supplementary Movie S5). To test if Opy1 regulates PtdIns(4,5)P2 metabolism, we performed 3H‐inositol labelling experiments to measure cellular PIP levels. We detected a two‐fold increase in PtdIns(4,5)P2 levels in opy1Δ cells compared with wild‐type cells (Figure 4A; Supplementary Table S1). In addition, overexpression of Opy1 in wild‐type cells resulted in a 40% decrease in PtdIns(4,5)P2 levels (Figure 4A; Supplementary Table S1). This was not due to decreases in Mss4 PIK patch lifetime (Supplementary Figure S3A; Supplementary Movie S6) or assembly (as measured by relative Mss4–GFP fluorescence intensity; Supplementary Figure S3C). Moreover, overexpression of Opy1 impaired the growth of mss4ts cells at a semi‐permissive temperature (34°C; Figure 4B), further suggesting that Opy1 regulates PtdIns(4,5)P2 metabolism, either by inhibiting its synthesis or by promoting its turnover.
In an independent genetic screen to identify regulators of PtdIns(4,5)P2 signalling, we isolated OPY1 as a high copy suppressor of synaptojanin mutant cells deficient in PIP 5‐phosphatase activity (sjl1Δ sjl2tssjl3Δ cells; Figure 4D). Consistent with this, OPY1 overexpression resulted in decreased PtdIns(4,5)P2 levels in sjl1Δ sjl2tssjl3Δ cells at the restrictive temperature (Figure 4C; Supplementary Table S1). Thus, Opy1 modulates PtdIns(4,5)P2 metabolism independently of the synaptojanin‐like PIP phosphatases. Consistent with this, loss of Opy1 did not alter the cortical localization of Sjl2 (Supplementary Figure S4A). Furthermore, triple deletion of SJL1, SJL2, and OPY1 resulted in an additive growth defect, as sjl1Δ sjl2Δ opy1Δ cells failed to grow upon loss of a URA3‐marked SJL2 plasmid on 5‐FOA media (Supplementary Figure S4B), suggesting that Opy1 and the synaptojanins regulate PtdIns(4,5)P2 by distinct mechanisms. In control experiments, OPY1 overexpression did not rescue the growth defects of other PIP phosphatase mutant cells that accumulate toxic levels of PtdIns(4)P and PtdIns(3)P, sac1tssjl2Δ sjl3Δ cells and ymr1tssjl2Δ sjl3Δ cells, respectively (Supplementary Figure S4C; Foti et al, 2001; Parrish et al, 2004). We observed that PtdIns(4)P levels were slightly elevated (1.5‐fold) in cells lacking Opy1 (opy1Δ cells; Supplementary Table S1). It was therefore possible that Opy1 could activate a PIP 4‐phosphatase such as the Sac1 enzyme (Foti et al, 2001; Stefan et al, 2011), and thus loss of Opy1 could lead to elevated levels of both PtdIns(4)P and PtdIns(4,5)P2. However, PtdIns(4,5)P2 levels were increased (1.8‐fold) in sac1Δ opy1Δ double‐mutant cells, as compared with sac1Δ single‐mutant cells (Supplementary Figure S4D; Supplementary Table S1). Thus, coupled with our co‐IP and colocalization results, we propose that Opy1 may inhibit Mss4 activity at PIK patches rather than activate a PIP phosphatase, such as the synaptojanins or Sac1.
Opy1 is a coincidence detector of PtdIns(4,5)P2 and Mss4
As Opy1 consists of two PH domains, we next addressed how Opy1 localizes to PIK patches at the PM. The N‐terminal PH domain of Opy1 fused to GFP (GFP–PH1) did not localize to the PM in vivo (Figure 5A; Yu et al, 2004). In contrast, the C‐terminal PH domain fused to GFP (GFP–PH2) was sufficient for PM targeting (Figure 5A; Yu et al, 2004). Similar to a previous study, the GFP–PH2 fusion still localized to the PM in mss4ts cells at the non‐permissive temperature (Yu et al, 2004; our unpublished observations). However, we found that GFP–PH2 became mis‐localized from the PM to the cytoplasm in pik1tsstt4ts double‐mutant cells upon an extended shift to 37°C (Figure 5A). A previous study reported that GFP–PH2 localized to the PM in pik1tsstt4ts mutant cells (Yu et al, 2004). However, GFP–PH2 was overexpressed from a high copy plasmid in this study. In addition, Yu et al found that overexpression of the PH2 domain caused growth defects in pik1tsstt4ts cells, suggesting that the PH2 domain may compete for some factor that becomes limiting in these cells. As pik1tsstt4ts double‐mutant cells have significantly reduced levels of PtdIns(4)P, PtdIns(4,5)P2, and Mss4 PIK patches at the PM (Audhya et al, 2000; Figure 2C in this study), we further addressed the lipid and protein binding activities for full‐length Opy1 and the Opy1 PH domains.
Source Data for Figure 5 [emboj2012127-sup-0011.pdf]
First, we examined whether Opy1 bound PtdIns(4,5)P2‐containing liposomes in vitro. For these experiments, we used GST, GST–PH1, GST–PH2, and GST–Opy1 fusion proteins purified from bacteria. GST–Opy1 (52% of the total protein) efficiently bound and floated with PC:PtdIns(4,5)P2‐containing liposomes (3% mol PtdIns4,5P2) on an equilibrium density gradient (Figure 5B). Likewise, GST–PH2 (41% of the total protein) was present with liposomes following equilibrium density fractionation, suggesting that the PH2 domain was sufficient for lipid binding (Figure 5B). In control experiments employing liposome sedimentation assays, neither GST–Opy1 nor GST–PH2 bound liposomes lacking PtdIns(4,5)P2 (e.g., PC:PtdIns‐containing liposomes; Supplementary Figure S5A). GST alone or the GST–PH1 fusion did not efficiently bind liposomes (Figure 5B; Supplementary Figure S5).
Next, we examined the PIP‐binding specificities of Opy1 and the PH2 domain in liposome sedimentation experiments. GST–Opy1 (32% of the total protein) specifically bound to liposomes containing 3% PtdIns(4,5)P2, but not to liposomes containing equal concentrations of other PIP isoforms (PtdIns(3)P, PtdIns(4)P, or PtdIns(3,5)P2; Supplementary Figure S5B). The GST–PH2 fusion sedimented with PtdIns(4,5)P2‐ and PtdIns(4)P‐containing liposomes (30% and 18% of the total protein, respectively; Supplementary Figure S5B), but not with PtdIns(3)P‐ or PtdIns(3,5)P2‐containing liposomes (2 and 1% of the total protein, respectively; Supplementary Figure S5B). As expected, GST alone or the GST–PH1 fusion did not efficiently sediment with PIP‐containing liposomes (Supplementary Figure S5). PtdIns(4)P binding by the PH2 domain may have resulted in the Pik1‐ and Stt4‐dependent PM localization of the GFP–PH2 fusion in vivo (Figure 5A). However, unlike the PH2 domain alone, full‐length Opy1 specifically bound PtdIns(4,5)P2in vitro. To confirm whether full‐length Opy1 localizes to the PM in a PtdIns(4,5)P2‐dependent fashion, we examined GFP–Opy1 localization in mss4ts cells that have reduced levels of PtdIns(4,5)P2 at the restrictive temperature (Stefan et al, 2002). The PM localization of full‐length Opy1–GFP was reduced in mss4ts cells shifted to the restrictive temperature but not in wild‐type cells (Figure 5C), suggesting that the recruitment of Opy1 to Mss4 PIK patches was dependent on PtdIns(4,5)P2 synthesis.
Since the Mss4 N‐terminal domain attenuates PtdIns(4,5)P2 synthesis (Figure 2D), we addressed whether it regulates Opy1 function. Strikingly, Opy1–GFP localized diffusely in the cytoplasm in cells expressing only the N‐terminal truncated form of Mss4 (mss4Δ2–346 cells; Figure 6A). To test if the Mss4 N‐terminal region was necessary for the Mss4–Opy1 interaction, we performed crosslinking co‐IP experiments using either full‐length or N‐terminally truncated Mss4. As in our previous results (Figure 3C), Opy1 copurified with full‐length Mss4 (Figure 6B). However, Opy1 did not interact with the mutant form of Mss4 lacking its N‐terminal region (Figure 6B), even though this truncated Mss4 localized to the PM and was functional (Figure 2A and B). Therefore, the Mss4 N‐terminal region may serve as a scaffold for Opy1 recruitment to PIK patches. Consistent with this, overexpression of OPY1 in mss4Δ2–346 cells did not result in a reduction in PtdIns(4,5)P2 levels (Figure 6C; Supplementary Table S1). Together, these results suggest that the tandem PH domain protein Opy1 serves dual roles as a coincidence detector of PtdIns(4,5)P2 and Mss4 as well as a regulator of PtdIns(4,5)P2 synthesis at the PM (Supplementary Figure S6C).
Source Data for Figure 6 [emboj2012127-sup-0012.pdf]
To further dissect the functions of the two PH domains in Opy1, we overexpressed either the PH1 domain or the PH2 domain in sjl1Δ sjl2tssjl3Δ cells. Neither of the PH domains was sufficient to complement the growth defect of sjl1Δ sjl2tssjl3Δ cells at the non‐permissive temperature (Figure 4D), suggesting they may function together to regulate PtdIns(4,5)P2 synthesis. However, to test whether the PH1 domain was functional when artificially targeted to the PM, we fused a palmitoylation motif (from Psr1) to the N‐terminus of the PH1 domain, which resulted in its efficient targeting to the PM (Supplementary Figure S6A). Interestingly, this fusion partially rescued the growth defect of sjl1Δ sjl2tssjl3Δ cells (Supplementary Figure S6B). These results predicted that both PH1 and PH2 might interact independently with Mss4 and have distinct roles in PIK patch targeting and Mss4 PIP 5‐kinase regulation. To test this idea, cell lysates containing Mss4–3xHA were incubated with GST, GST–PH1, GST–PH2, or GST–Opy1 fusion proteins bound to glutathione sepharose beads. As expected, full‐length GST–Opy1 pulled down Mss4–3xHA from cell lysates but GST alone did not (Figure 6D) Interestingly, Mss4–3xHA was isolated with both the GST–PH1 and GST–PH2 fusion proteins in pull‐down experiments (Figure 6D). Thus, the PH2 domain may target Opy1 to the PM by binding PtdIns(4,5)P2 and Mss4, and the PH1 domain may serve as a negative regulator of PtdIns(4,5)P2 synthesis.
Mammalian TAPP1 rescues the growth defect of yeast synaptojanin mutant cells
Mammalian cells have several putative Opy1 homologues with tandem PH domains. Three members of this protein family, pleckstrin, TAPP1, and TAPP2, bind PtdIns(3,4)P2 through their PH2 domains (Figure 7A; Haslam et al, 1993; Dowler et al, 2000; Allam and Marshall, 2005; Edlich et al, 2005). To test whether these proteins have conserved functions in PIP signalling, we overexpressed pleckstrin or TAPP1 in sjl1Δ sjl2tssjl3Δ cells that accumulate toxic levels of PtdIns(4,5)P2. Intriguingly, TAPP1, but not pleckstrin, weakly rescued the growth defect of sjl1Δ sjl2tssjl3Δ cells at the non‐permissive temperature (Figure 7B). And consistently, PtdIns(4,5)P2 levels were restored to normal in sjl1Δ sjl2tssjl3Δ cells upon overexpression of TAPP1 (Figure 7C). To address whether inhibition of PtdIns(4,5)P2 synthesis by TAPP1 occurred through Mss4–TAPP1 interactions, cell lysates containing GFP–TAPP1 were incubated with His6–SUMO–Mss41–346 or His6–SUMO–Mss4347–779 fusion proteins bound to nickel‐charged agarose beads. Interestingly, both His6–SUMO–Mss41–346 and His6–SUMO–Mss4347–779 fusion proteins pulled down GFP–TAPP1 from cell lysates, but not GFP alone (Figure 7D). TAPP1 and TAPP2 downregulate insulin and PtdIns(3,4,5)P3 signalling upon generation of PtdIns(3,4)P2 by the PIP 5‐phosphatase SHIP2 (Wullschleger et al, 2011). Our results suggests TAPP1 may inhibit PIP 5‐kinase activity thus reducing PtdIns(4,5)P2 levels as substrate for the PIP 3‐kinase (PI3K) isoforms that synthesize PtdIns(3,4,5)P3. Alternatively, TAPP1 could inhibit PI3K itself given the similarity between PIP kinases (Supplementary Figure S6D). Importantly, our results have identified conserved roles for this family of tandem PH domain proteins as monitors and regulators of PIP metabolism at the PM.
Source Data for Figure 7 [emboj2012127-sup-0013.pdf]
PtdIns(4,5)P2 is essential for a variety of cellular processes and its distribution and abundance must be tightly controlled (Stefan et al, 2002). We demonstrate that Mss4 assembles into dynamic, oligomeric structures: PIK patches. The dynamic assembly and disassembly of Mss4 PIK patches may serve as a mechanism for localized synthesis of PtdIns(4,5)P2 at the PM. Furthermore, oligomerization of Mss4 provides a mechanism to precisely modulate multiple copies of PIP kinase activity, as needed, for localized increases in PtdIns(4,5)P2 synthesis through the recruitment of specific activators such as small GTPases and clathrin adaptors (Nakano‐Kobayashi et al, 2007; Smaczynska‐de et al, 2008). In addition, we found that the tandem PH domain protein, Opy1, associates with Mss4 at PIK patches and inhibits PtdIns(4,5)P2 synthesis. Thus, Mss4 PIP 5‐kinase activity is attenuated by negative regulatory factors, such as Opy1, prior to the disassembly of PIK patches.
Mss4 PIK patches are distinct from other known cortical structures such as actin patches and eisosomes. The PtdIns 4‐kinase Stt4 also oligomerizes at the PM to form PIK patches (Baird et al, 2008). However, Stt4 and Mss4 PIK patches are distinct structures and show unique characteristics (Audhya and Emr, 2002; Baird et al, 2008). Stt4 PIK patches are relatively static at the PM, with a lifetime on the order of 3 min (Baird et al, 2008). Unexpectedly, Mss4 PIK patches are highly dynamic structures undergoing rapid assembly/disassembly and lateral movements. The biological function of PIK patches is not completely clear. However, the assembly of Mss4 into PIK patches may provide spatial and temporal control of PtdIns(4,5)P2 synthesis necessary to coordinate the numerous processes regulated by PtdIns(4,5)P2 (e.g., polarized secretion, endocytosis, MAPK activation). Accordingly, individual PIK patches may perform specialized functions and have different compositions (distinct nucleation and regulatory factors). Consistent with this idea, mammalian PtdIns(4)P 5‐kinase isoforms are differentially recruited to focal adhesion sites and clathrin‐coated pits by talin and the μ2 AP‐2 adaptor subunit, respectively (Ling et al, 2002; Krauss et al, 2006; Nakano‐Kobayashi et al, 2007).
A striking feature of Mss4 PIK patches is their rapid assembly and disassembly. The assembly of Mss4 PIK patches involves the activation loop in the Mss4 lipid kinase domain and its substrate PtdIns(4)P at the PM (Figure 8). Although the kinase–substrate interaction is necessary for PIK patch formation, PtdIns(4)P is not sufficient to recruit Mss4 to membranes as Mss4 was not observed at Golgi compartments that are enriched in PtdIns(4)P (Audhya et al, 2000; Stefan et al, 2002). In addition, elevation of PtdIns(4)P levels (e.g., in mutant cells deficient in Sac1 PtdIns(4)P phosphatase activity) does not result in increased PtdIns(4,5)P2 levels (Foti et al, 2001; Stefan et al, 2011). Thus, there must be factors in addition to PtdIns(4)P that specify the PM localization and activity of Mss4. We speculate that the conversion of PtdIns(4)P to PtdIns(4,5)P2 by Mss4 may lead to PIK patch disassembly as PtdIns(4)P becomes locally depleted (Figure 8). This elegant mechanism would provide an intrinsic switch for the localized control of Mss4 assembly and disassembly reactions at the PM. An electrostatic switch mechanism has been proposed for the membrane association of a mammalian PIP 5‐kinase during phagocytosis (Fairn et al, 2009). However, this process involves PIP turnover (by lipases and phosphatases) rather than inherent PIP kinase activity.
Using independent proteomic and genetic approaches, we identified the tandem PH domain protein Opy1 as a negative regulator of Mss4 PIP kinase activity. Our results show that Opy1 has dual functions as a PtdIns(4,5)P2 sensor and regulator. First, localization of Opy1 to cortical patches is dependent on PtdIns(4,5)P2 as well as the N‐terminus of Mss4. In addition, overexpression or deletion of Opy1 results in mis‐regulation of PtdIns(4,5)P2 synthesis at the PM. Full‐length Opy1 protein is mostly cytoplasmic under conditions when PtdIns(4,5)P2 levels at the PM are low (e.g., mss4ts cells). Upon activation of PtdIns(4,5)P2 signalling in response to extracellular or intracellular cues, Opy1 may be initially recruited to the PM (Figure 8). In support of this, Opy1 directly binds PtdIns(4,5)P2‐containing liposomes in vitro. We propose that Opy1 is recruited to PIK patches through its interaction with the Mss4 N‐terminus to subsequently downregulate Mss4 PIP kinase activity. Consistent with this model, the N‐terminal truncated form of Mss4 displays increased activity compared with full‐length Mss4. Thus, together with PIP 5‐phosphatases, Opy1 may be part of a rapid negative regulatory feedback system that is activated as PtdIns(4,5)P2 levels rise (Supplementary Figure S6C). Following attenuation of PtdIns(4,5)P2 synthesis and disassembly of Mss4 PIK patches, Opy1 may then disassociate from the PM.
Mammalian pleckstrin, TAPP1, and TAPP2 are tandem PH domain proteins that specifically bind PtdIns(3,4)P2in vitro (Haslam et al, 1993; Dowler et al, 2000; Allam and Marshall, 2005; Edlich et al, 2005). Intriguingly, TAPP1, TAPP2, and pleckstrin inhibit PI3K signalling (Abrams et al, 1996; Wullschleger et al, 2011). The inhibition of PI3Kγ activity by pleckstrin has been proposed to occur by direct interaction between PI3Kγ and pleckstrin, or alternatively through binding of pleckstrin to PI3Kγ activators, the βγ subunits of heterotrimeric GTP‐binding proteins (Abrams et al, 1996). TAPP1 and TAPP2 may regulate PtdIns(3,4,5)P3 levels in cells by analogous mechanisms. Our results suggest yet another possible model for the control of PI3K signalling by dual PH domain proteins–inhibition of PIP 5‐kinases and PtdIns(4,5)P2 synthesis that would impinge on PI3K activity (Supplementary Figure S6D). Though the PIP‐binding specificities of pleckstrin, TAPP1, TAPP2, and Opy1 have diverged, they appear to share similar roles in attenuating PIP signalling. Diversity in PIP‐binding specificities is consistent with a widespread role for this protein family in the regulation of multiple PIP kinases (e.g., PIP 3‐kinase, 4‐kinase, and 5‐kinase activities). In support of this idea, we found that the PH2 domain of Opy1 bound PtdIns(4)P‐containing liposomes in vitro. In addition, PtdIns(4)P levels were modestly increased in cells lacking Opy1. Thus, future studies may reveal new roles for Opy1 and other tandem PH domain proteins in the regulation of additional PIP kinase activities.
We propose that the C‐terminal PH2 domains of these tandem PH domain proteins serve as PIP sensors, while the N‐terminal PH1 domains regulate PIP kinases. Consistent with this, PH domains are involved in protein–protein interactions in addition to PIP binding (Wang et al, 1994; Yao et al, 1994). It remains unclear whether these tandem PH domain proteins directly inhibit PIP kinases or indirectly act through additional factors. Opy1 was originally identified as a regulator of GPCR and MAPK signalling in yeast (Edwards et al, 1997) and MAPK activation in yeast requires localized PtdIns(4,5)P2 signalling (Garrenton et al, 2010). Our study links the regulation of GPCR, MAPK, and PIP signalling through Opy1 function. It is therefore interesting that pleckstrin and TAPP1, TAPP2 control PI3K activity in response to GPCR and insulin receptor signalling. Thus, future studies on this family of dual PH domain proteins will likely provide new insight into our understanding of PIP signalling pathways.
Materials and methods
Additional details of the Materials and methods are provided in the Supplementary data.
Yeast strains and plasmid construction
A list of S. cerevisiae strains and plasmids used in this study and their genotypes can be found in Supplementary Tables S2 and S3. Homologous recombination was used to tag or delete genes in yeast (Longtine et al, 1998). All integrations and deletions were verified by PCR analysis and expression of fusion proteins was confirmed by western blot analysis. The yeast shuttle vectors used in this study have been previously described (Sikorski and Hieter, 1989).
Fluorescence microscopy and quantification of fluorescence intensity
Microscopy was performed using a fluorescence microscope (DeltaVision RT; Applied Precision) equipped with FITC and rhodamine filters. Images were captured with a digital camera (Cool Snap HQ; Photometrics) and deconvolved using softWoRx 3.5.0 software (Applied Precision). To quantify numbers of Mss4–GFP molecules in PIK patches in Figure 1C, cells coexpressing Mss4–GFP and Cse4–3xGFP were grown to mid‐log phase. Cells were examined by fluorescence microscopy and undeconvolved data were used for quantification of intensities. Regions of interest (with identical areas) that contained a single Mss4 PIK patch or Cse4–3xGFP structure were selected and quantified using softWoRx 3.5.0 software (Applied Precision). Background signal was subtracted from measured fluorescence intensities of PIK patches and Cse4–GFP. Additional methods for comparing PIK patch intensities are described in the Supplementary data.
In‐vivo analysis of PIPs
PIPs levels were analysed as previously described (Stefan et al, 2002; Baird et al, 2008). Briefly, 5 OD600 units of cells were labelled with 50 μCi of myo‐[2‐3H]‐inositol (Perkin‐Elmer) in media lacking inositol. After precipitation in 4.5% perchloric acid for 5 min, phospholipids were deacylated by incubation in methylamine reagent at 53°C. Samples were dried in a vacuum chamber, washed, dried again, and resuspended in 300 μl sterile water. Extraction reagent (1‐butanol/ethyl‐ether/formic acid ethyl ester at a ratio of 20:4:1) was added and [3H]glycero‐PIPs were separated into the aqueous phase by vortexing and centrifugation at 14 000 g. The extraction was repeated twice and the final aqueous phase was collected and dried. Dried pellets were resuspended in water and separated on a Partisphere SAX column (Whatman, Florham Park, NJ) attached to a Shimadzu HPLC system (Shimadzu, Kyoto, Japan) and a 610TR on‐line radiomatic detector (Perkin‐Elmer, Waltham, MA) using Ultima Flo scintillation fluid (Perkin‐Elmer). The HPLC and on‐line detector were controlled with EZStart 7.2.1 and ProFSA 3.3 software, respectively, and data were analysed using ProFSA 3.3 software.
Analysis of cellular protein expression levels
In all, 5 OD600 equivalents of mid‐log cells were harvested by precipitation in 10% trichloroacidic acid (TCA). Precipitates were washed in acetone, aspirated, resuspended in lysis buffer (150 mM NaCl, 50 mM Tris pH 7.5, 1 mM EDTA, 1% SDS), and mechanically lysed with glass beads. Protein sample buffer (150 mM Tris pH 6.8, 6 M Urea, 6% SDS, 10% β‐mercaptoethanol, 20% Glycerol) was added and extracts were analysed by SDS–PAGE and immunoblotting with anti‐G6PDH (Sigma) and anti‐GFP (Santa Cruz Biotechnology) antibodies.
In‐vivo crosslinking and coimmunoprecipitation
Yeast cells expressing epitope‐tagged proteins were grown to an OD600 of 0.5–0.8. Cells were harvested and spheroplasted with Zymolyase 100T (Seikagaku Biobusiness). Spheroplasts were washed and crosslinked by 1 mM DSP (Pierce) in crosslinking buffer (20 mM HEPES, 0.7 M Sorbitol, 100 mM KOAc pH=7.4) for 30 min. In all, 100 mM Tris–HCl (pH=7.5) was added to the crosslinking buffer to stop the reaction. Spheroplasts were lysed by vortexing with glass beads in Urea cracking buffer (6 M Urea, 50 mM Tris–HCl, 1 mM EDTA, 1% SDS, pH=7.5). Cell lysates were diluted in Tris IP buffer (50 mM Tris–HCl, 150 mM NaCl, 5 mM EDTA, 0.5% Tween‐20, pH=7.5 with protease inhibitors added) and cleared by centrifugation at 13 000 g. Immunoprecipitations were performed by adding either HA or Flag affinity gel (Sigma‐Aldrich) to the supernatant at 4°C. The affinity matrix was washed with IP buffer four times. Immunoprecipitated proteins were eluted and reduced with elution buffer (100 mM Tris–HCl pH=8.0, 1% SDS, 10 mM DTT) at 65°C. Elutes were mixed with sample buffer (6 M Urea, 150 mM Tris–HCl pH=6.8, 6% SDS, Bromophenol Blue) and analysed by SDS–PAGE and immunoblotting.
SILAC and quantitative mass spectrometry analysis
For quantitative mass spectrometry analysis using SILAC (Stable isotope labelled amino acids in cell culture), yeast strains auxotrophic for lysine and arginine were grown to mid‐log phase in either heavy or light lysine and arginine isotopes. Following affinity purification, light and heavy elutes were mixed, reduced with 10 mM DTT and alkylated with 20 mM iodoacetimide (Sigma‐Aldrich). Proteins were precipitated by adding (3:1) 50% acetone, 49.9% ethanol, and 0.1% acetic acid, resuspended in 8 M urea, 50 mM Tris–HCl pH=8.0, diluted 3:1 with water and digested with 1 μg of trypsin overnight. Tryptic peptides were fractionated by hydrophilic interaction chromatography (HILIC), dried, and reconstituted in 0.1% trifluoroacetic acid. Each fraction was analysed by LC–MS/MS using an Orbitrap XL mass spectrometer (Thermo). Peptide analysis and SILAC quantitation was performed using Sorcerer software.
Recombinant protein expression and purification
The bacterial expression vectors pGEX6P‐1 (GE Healthcare) and ppSUMO (Sondermann Lab) were used to generate recombinant fusion proteins. C41 (DE3) cells (Lucigen) transformed with protein expression plasmids were grown at 37°C to an OD600 of 0.4. The bacteria were then shifted to 25°C and protein expression was induced by the addition of 0.1 mM IPTG for 16 h. GST and His6 fusion proteins were purified from C41 (DE3) cells with glutathione sepharose 4B (GE Healthcare) and Ni‐NTA agarose (Qiagen) according to the manufacture's instructions. Protein concentrations were determined by the Bradford assay (Bio‐Rad). Purified proteins were stored at −80°C in phosphate‐buffered saline (PBS) or in storage buffer (PBS, 50% glycerol) until further use.
Lipid‐binding assays
For liposome flotation assays, 97%PC: 3%PtdIns(4,5)P2 (Avanti Polar Lipids) liposomes were generated by dehydration in a chloroform:methanol mix using a speed vacuum centrifuge, and then rehydrated in PBS with 1 mM DTT at a final concentration of 1.2 mM total lipid. To create unilamellar liposomes, the liposomes were sonciated for 1 min at room temperature in a water bath. Liposomes (1.2 mM) were then mixed with an equal volume (50 μl) of GST fusion proteins (resulting in 1.7 μM final protein concentration and 0.6 mM final lipid concentration) and allowed to incubate for 30 min at room temperature. Samples were then resuspended in 200 μl buffer (PBS, 1 mM DTT) containing 30% Optiprep density gradient medium (Sigma) and pipetted into thick walled 2.2 ml centrifuge tubes. In all, 150 μl of 15% Optiprep buffer was overlaid over the samples, followed by 50 μl of buffer (PBS, 1 mM DTT). Samples were centrifuged for 1 h at 55 000 r.p.m. at 10°C in a TLS‐55 ultracentrifuge rotor in desktop ultracentrifuge (Beckman Coulter). The top 200 μl of the gradient containing liposomes and bound proteins was then collected as the 'bound' fraction. The bottom 200 μl 'unbound' fraction was collected separately. Samples were resuspended in protein sample buffer, run on 10% SDS–PAGE gels, and GST fusion proteins were detected by immunoblotting using GST antisera. The relative amounts of fusion proteins in bound and unbound fractions were determined using NIH ImageJ software.
For liposome sedimentation assays, 100%PC, 97%PC: 3%PtdIns and 97%PC:3%PIP‐containing liposomes were prepared as described above except that the final lipid concentration was 0.3 mM, incubated with 1.7 μM recombinant GST, GST–Opy1, GST–PH1, or GST–PH2 fusion proteins for 30 min at room temperature, and centrifuged at 13 000 g for 20 min at 4°C. The resulting supernatant and pellet fractions were prepared for SDS–PAGE analysis and Coomassie stained to detect recombinant proteins. The gels were scanned and relative amounts of fusion proteins in pellet (bound) and in supernatant (unbound) fractions were determined using LI‐COR software.
Methods for lipid overlay assays are described in the Supplementary data.
Protein‐binding assays
For Mss4–3xHA and GST–Opy1 binding, GST, GST–Opy1, GST–PH1, or GST–PH2 fusion proteins immobilized on glutathione sepharose 4B were incubated with Mss4–3xHA lysates solubilized in Tris IP buffer (50 mM Tris–HCl, 150 mM NaCl, 5 mM EDTA, 0.5% Tween‐20, pH=7.5, with protease inhibitors added) for 1 h at 4°C. Beads were washed with IP buffer three times and elutes were analysed by SDS–PAGE and immunoblotting using anti‐HA antibodies. Similarly, For Mss4 and TAPP1 binding, His6–SUMO–Mss41–346 and His6–SUMO–Mss4347–779 proteins immobilized on Ni‐NTA beads were incubated with cell lysates expressing GFP–TAPP1 or GFP alone in Tris IP buffer for 1 h at 4°C. Beads were washed with IP buffer three times and elutes were analysed by SDS–PAGE and immunoblotting using GFP antisera.
Conflict of Interest
The authors declare that they have no conflict of interest.
Supplementary Information
Supplementary Information [emboj2012127-sup-0001.pdf]
Supplementary Movie 1 [emboj2012127-sup-0002.mpg]
Supplementary Movie 2 [emboj2012127-sup-0003.mpg]
Supplementary Movie 3 [emboj2012127-sup-0004.mpg]
Supplementary Movie 4 [emboj2012127-sup-0005.mpg]
Supplementary Movie 5 [emboj2012127-sup-0006.mpg]
Supplementary Movie 6 [emboj2012127-sup-0007.mpg]
Supplementary Dataset 1 [emboj2012127-sup-0008.xls]
Source Data for Figure S2 [emboj2012127-sup-0014.pdf]
Source Data for Figure S5 [emboj2012127-sup-0015.pdf]
We thank Haiyuan Yu for providing the TAPP1 and pleckstrin plasmids. We thank Qi Wang and Holger Sondermann for providing the His6–SUMO vector. We thank the members of the SDE laboratory, David Holowka, Yuxin Mao, Marcus Smolka, and John York (Duke University) for helpful discussions and comments on the manuscript. We are grateful to Marcus Smolka for assistance with the quantitative mass spectrometry experiments. This work was supported by funds from the Weill Institute for Cell and Molecular Biology and a Cornell University Research Grant (to SDE) and by a Sam and Nancy Fleming Research Fellowship (to JAM).
Author contributions: YL, CJS, and SDE designed the experiments; YL and CJS performed the experiments; JAM performed the quantitative mass spectrometry analysis; AA isolated OPY1 in a genetic screen; YL, CJS, and SDE analysed the data; YL, CJS, and SDE wrote the manuscript. All authors discussed the results and contributed to the final manuscript.
- Copyright © 2012 European Molecular Biology Organization


text: Save Whittington Hospital Saturday 16 March 2013 at 11:30-18:00 Join the fight to save Whittington Hospital on Saturday 16 March from 11.30am Assemble Highbury corner, Holloway Road, London N5 Join the fight to save Whittington Hospital. Join the march. WHEN: Saturday 16 March at 11.30am WHERE: Assemble Highbury corner, Holloway Road, London N5 Say NO to: 580 job losses, including 220 nurses The sell off of around one third of the site to property speculators Downgrading an acute hospital with an A&E unit to an urgent care centre And more Download a Defend Whittington Hospital campaign flyer Find out more from the Defend the Whittingham Hospital coalition

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text:
Indianapolis Symphonic Choir
The Indianapolis Symphonic Choir and Indianapolis Public Schools have united to resurrect the All-City Honor Choir. Eliminated from the IPS offerings in 2009 due to deep financial reductions, the All-City Honor Choir returned in 2015 to the music education offerings in the Hoosier State's largest public school system, re-imagined, refreshed and reaching gifted young musicians. The Indianapolis Symphonic Choir is pleased to partner with IPS, bringing to life a choir that includes students from all 8 IPS schools who were selected through a competitive audition process. The Indianapolis Symphonic Choir looks to grow and expand this program through the 2016-2017 season.


text:
Screenshot of the Week 592
Posted 02 January 2017 - 12:10 AM
A prison where the guards are trapped in a cell is a prison with bad design.
This dungeon is dark... too dark...
Happy New Year 2017 PZC!
- Joelmacool likes this
Posted 02 January 2017 - 07:00 AM
Ganondorf - This seems like a pretty simple screen, definitely reminds me of ALTTP. There isn't much else to say about it though, but nice job.
Joelmacool - Seems like a good shot, but I feel this is one of your weaker entries. There is a lack of wall design on the bottom of the screen, and that Link looks horrible (I'd use the Link from earlier versions of DoR).
Demonlink - Back at it again with the awesome EZGBZ screens I see. Really nice job with this one, got no critiques with this.
I voted for Demonlink this week.
Posted 04 January 2017 - 12:13 AM
Voted for Demonlink. Very nice use of EZGBZ.
Posted 07 January 2017 - 02:09 AM
Posted 07 January 2017 - 09:51 AM
I really like Demonlink's screen on this one. The others aren't really bad either, just pretty basic screens. I voted Demonlink because it does more with design in terms of not just being blocky and has detail done right.
- Neptune likes this
Posted 07 January 2017 - 10:02 PM
I am a simple man. I see Ganondorf with the LttP throwback, I vote.
Posted 08 January 2017 - 05:39 AM
Very close week. These felt pretty equal in terms of design, but while the others seem like shots taken right from ALttP or OoA/S, Joel's area had an atmosphere that felt a little more distinct- my reason for voting.
- Joelmacool likes this
Posted 08 January 2017 - 06:06 PM
With 65.12% of the vote, the winner of Screenshot of the Week 592 is Demonlink!
Voting totals:
- Ganondorf (11 votes [25.58%])
- Joelmacool (4 votes [9.30%])
- Demonlink (28 votes [65.12%])
Also tagged with one or more of these keywords: Demonlink, Ganondorf, Joelmacool
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text:
PDF Version
Types of Assessments
Pathways of Assessment of Advice
Definitions of Technical
Resource Evaluation and Assessment Division of the Northeast Fisheries
Science Center (NEFSC), National Marine Fisheries Service (NMFS),
with headquarters in Woods Hole, Massachusetts, regularly updates
assessments of finfish and shellfish resources off the northeastern
coast of the United States and presents information as needed to
administrators, managers, the fishing industry, other stakeholders
and constituency groups and the general public. Some of these assessments
are prepared exclusively by NEFSC scientists; many others are prepared
jointly with researchers at other federal and state agencies and
academic institutions. This website summarizes the status of selected
finfish and shellfish resources off the northeastern coast of the
United States from Cape Hatteras to Nova Scotia.
webpage includes review chapters on aggregate resource and landings
trends, and stock status information for 62 stocks of marine finfish
and shellfish from the Gulf of Maine to Cape Hatteras. The Aggregate Resource and Landings Trends section provides an overview
of trends in abundance for major finfish assemblages on the northeast
shelf, together with an overview of resource status. In most cases,
this information is based on the most recent peer-reviewed assessment.
In some cases, however, assessments have been infrequent, and the
information included herein has been brought up to date without
a formal review.
The species and stocks described
herein can be logically grouped into 7 categories: principal
groundfish, flounders, other groundfish, principal pelagics,
other finfish, invertebrates, and anadromous fish. The
region occupied by these stocks (including areas in
Canadian waters occupied by resources exploited by both
the U.S. and Canada) is shown in (Figure
Several different
types of assessments may be performed depending on the
nature of the fishery and the type and amount of data
available. The simplest involve use of commercial landings
and fishing effort data and/or research vessel survey
data to generate indices of abundance. As research vessel
surveys are performed using small mesh gear to sample
juvenile fish and invertebrates, survey data are also
used to develop indices of incoming recruitment. A second
approach is to use commercial landings and effort data
and/or information on population size and productivity
to determine relationships between effort and yield; this
is referred to as a surplus production or surplus yield
model. Results from this model may be displayed as yield
vs. biomass (Figure
2a) or fishing mortality vs. biomass (Figure
2b). Yield and spawning stock biomass per recruit
curves may also be developed based on biological parameters
(growth and natural mortality rates, maturation, etc.)
generated from biological sampling or other sources of
information (Figure
The most complex
(and useful) assessments can be performed when size and
age composition of the catch and the population can be
determined reliably through sampling of commercial and
recreational catches at sea and at dockside and research
vessel survey catches at sea. This allows development
of more detailed analytic (size or age structured) assessments
which provide information on stock size, recruitment and
fishing mortality and exploitation patterns over time.
These analyses are performed using virtual population
analysis or statistical catch at age models .
Such assessments may incorporate relationships between
spawning stock size and recruitment (stock recruitment
models) which provide a basis for benchmark advice on
management options. These models may account for changes
in environmental conditions.
The type of
assessment performed is usually driven by management
needs. For moderately exploited fisheries where management
is less intensive, surplus production or index based
methods may be adequate. For intensively fished stocks,
analytic assessments are generally required; and thus
improvement of "fishery dependent" and "fishery
independent" data collection programs and databases
continues to be a high priority of the NEFSC and NMFS.
Also, much remains to be learned about the biology of
many species, and current biological information often
requires updating since biological parameters may vary
with exploitation and environmental changes. These needs
will increase as research and management requirements
continue to intensify.
Index: assessment involves
development of an index of stock size from research vessel survey
data (mean catch per tow) or from fishery catch per unit of
effort (CPUE) data. This type of assessment may also involve
a model framework.
Surplus production:
assessment models the relationships between yield and fishing
effort. Models are based on simple biological rules of increase
and decrease and allow useful analyses with relatively little
data, but cannot be readily adapted to account for detailed biological
or fishery-related information.
Yield per recruit:
assessment provides evaluations of yield as a function of fishing
mortality and age at entry to the fishery, incorporating information
on biological parameters (growth and natural mortality rates).
Spawning stock biomass per recruit calculations are analogous
in that they use such information along with maturation data to
model trends in spawning biomass.
Age/size structured:
assessment includes analysis of the observed size or age composition
of the catch (e.g., virtual population analysis, statistical catch
at age models, modified DeLury analysis) and biological information
(size and weight at age, maturation rates) to provide estimates
of fishing mortality and total and spawning stock size (numbers
and weight) over time.
estimates can be combined with estimates of incoming recruitment
from research vessel surveys or other sources to make predictions
of catch and stock size in upcoming years in relation to fishing
mortality. They also provide data for a wide variety of more sophisticated
analyses e.g., recruitment in relation to spawning stock size
or multispecies modeling.
the level of complexity of an assessment requires a substantial
additional commitment of resources to develop and maintain it
at its more complex level. Conversely, the level and information
content of an assessment can decrease relatively quickly if sufficient
resources are not allocated to it.
The assessments
on this webpage consider each species as a separate entity, with
no consideration of species interactions. However, there are significant
biological (predator/prey) as well as technological (bycatch)
interactions for northeastern U.S. fishery resources, and a large
part of the Center's research program is dedicated to modeling
the effects of these interactions. The results of these studies
are not presented here. The significance of the mixed species
nature of the northeast trawl fisheries is illustrated under Aggregate Resource and Landings Trends, where aggregate research
trawl survey and commercial fishery data are presented illustrating
major trends in abundance and catches. The approaches used, however,
do not address species interactions and other resource complexities.
occurring primarily in the Exclusive Economic Zone (EEZ) off the
Northeastern U.S. are managed under Fishery Management Plans (FMPs)
developed by the New England and Mid Atlantic Fishery Management
Councils. Fisheries occurring primarily in state waters are managed
by the individual states or under Interstate Agreements under
the auspices of the Atlantic States Marine Fisheries Commission
(ASMFC). The management plans currently in place are shown in
Table 1.
The current
era of stock assessment and management began in 1976 with the
establishment of the Fishery Conservation and Management Act or
FCMA, now termed the Magnuson-Stevens Fishery Conservation and
Management Act or MSFCMA. The Act sought to eliminate perceived
overfishing in the EEZ by establishing eight regional fishery
management councils (FMCs), which were charged with developing
fishery management plans (FMPs) to achieve optimum yield (OY).
The FCMA contained National Standards that provided guidance for
the preparation of FMPs to achieve OY, defined as maximum sustainable
yield, or MSY, as modified by relevant biological, social or economic
factors. Thus it was permissible to harvest at or above the MSY
level under certain conditions. While effective in removing effort
by foreign nationals from the EEZ, the FCMA did not provide the
stringent controls on domestic effort that were necessary for
preventing overfishing and rebuilding overexploited stocks; and,
during the 1980s, many resources were severely impacted.
In subsequent
years additional legislation was formulated to increase the effectiveness
of the FCMA. In 1989, NMFS published the "602 Guidelines"
(50 CFR Part 602, Guidelines for the Preparation of Fishery Management
Plans Under the FCMA), which provided a formal definition of overfishing
and required that all FMPs be amended to include measurable definitions
of overfishing for each stock or stock complex covered. Most of
the resulting definitions were based on a limit fishing mortality
rate designed to prevent recruitment overfishing, by maintaining
some acceptable minimum spawning biomass per recruit level,e.g.
F20% or F30% to achieve 20% or 30% of the
unfished level. Further, the 602 guidelines required rebuilding
plans for overfished stocks.
In 1996,
the Sustainable Fisheries Act or SFA (PL 104-297) was passed
and integrated into the Magnuson Act, which was subsequently
renamed the MSFCMA. The SFA contained significant changes, notably
a redefinition of OY to be no greater than MSY. Furthermore,
FMCs were required to end overfishing and rebuild overfished
stocks to biomass levels corresponding to MSY in 10 years or
less, if the biology of the species allowed, or the time it
would take for the stock to rebuild in the absence of any fishing
mortality, plus one mean generation time, in the case of species
that could not be rebuilt in 10 years or less. Final National
Standard Guidelines published in 1998 require that FMPs include
"status determination criteria" for evaluation of
stock conditions relative to existing fishing mortality rates
(overfishing occurring/not occurring) and existing biomass levels
(overfished/not overfished). Overfishing is said to be occurring
if fishing mortality exceeds the Maximum Fishing Mortality Threshold
(MFMT, or FTHRESHOLD) which will normally be equivalent
to FMSY. A stock is considered to be overfished if
biomass falls below the Minimum Stock Size Threshold (MSST,
or BTHRESHOLD); usually 1/2 the stock biomass level
that can produce MSY (BMSY ). NMFS is required to
prepare a report to Congress each year summarizing the status
of every stock within each FMC's geographical area of authority
with respect to the above status determination criteria.
To comply
with the National Standard Guidelines, rebuilding plans have been
devised for many stocks, which specify how F should vary over
time to allow the stock to reach Bmsy within the required time
frame (see Figure
4 for an example). Here, levels of fishing mortality may be
applied to achieve the desired biomass level e.g. FREBUILD,
typically a level of F that can be expected to achieve stock rebuilding
within a set time frame. For rebuilt stocks, the threshold and
target levels of F may be constant at BMSY or higher,
but as stock biomass declines below BMSY, FTHRESHOLD
and FTARGET may decline as well. If stock biomass declines
to BTHRESHOLD or below, FTHRESHOLD could
decrease to zero or the lowest level of F that is practicable.
The form of the relationship is determined by biomass and recruitment
projections that incorporate available data on resource productivity.
Values for F at stock biomass values below BMSY are
projected to result in stock rebuilding to BMSY within
the required time frame. Note that FTHRESHOLD is a
limit reference point indicating the point at which the stock
is overfished; thus, harvests should be constrained substantially
and the probability for exceeding this value should be low. FTARGET
is set below FTHRESHOLD to ensure that fishing mortality
exceeds the threshold only rarely. In a rebuilding situation,
FTARGET might not be increased as stock biomass increases,
until BMSY is achieved.
As an illustration, (Figure
5) shows the relationship between fishing
mortality and biomass, relative to status determination criteria.
The vertical lines representing ½ BMSY and BMSY
and the horizontal line representing FMSY form a
grid indicating resource status. If the status determination
criteria for a stock were ½ BMSY for the MSST
and FMSY for the MFMT, the stock in Sector A, with
biomass below ½ BMSY and F above FMSY
would be classified as "overfished" (B is below BTHRESHOLD)
, and "overfishing is occurring" (F is above FTHRESHOLD).
In this case the FMC would be required to develop a rebuilding
plan and an F reduction plan within one year. A stock falling
in Sector B (biomass is below ½ BMSY and F is
below FMSY) would again be classified as "overfished"
although here "overfishing is not occurring" (F is
below FTHRESHOLD). In this case only a rebuilding
plan would be mandated. A stock falling in Sector C, between
½ BMSY and BMSY and above FMSY,
is not "overfished" (B is above BTHRESHOLD),
although "overfishing is occurring" (F is above FTHRESHOLD),
requiring an F reduction. Finally, for a stock for which B is
between ½ BMSY and BMSY, and F is
below FMSY (Sector D) no action is required; however,
since stocks are intended to be managed to produce MSY, the
FMCs must pursue management policies to rebuild the stocks to
and maintain them at BMSY in such cases.
assessments and related analyses and documentation are sometimes
provided directly to the Councils through Scientific and Statistical
Committee meetings or to ASMFC via section meetings. Increasingly,
however, managers are depending upon the Northeast Regional
Stock Assessment Workshop (SAW) process for assessment advice.
SAW originated in 1985 as a vehicle for in house or local peer
review of stock assessments and related research. As the condition
of fishery resources in the Northeast deteriorated and pressure
for assessment and management advice intensified, the SAW evolved
into an intensive biannual review process involving four components:
a Steering Committee, to oversee the process and determine priorities;
working groups, responsible for completion of stock assessments
and working papers; a Stock Assessment Review Committee (SARC)
that reviews assessments and prepares management advice; and
a Public Review Workshop that presents SARC reports and advice
at meetings of the New England and Mid Atlantic Councils. SARC
membership was structured to include experts from the NEFSC
and other NMFS Centers, the Councils and ASMFC, state agencies
and academic institutions, and Canada; and all SAW related meetings
and workshops are open to participation by industry representatives
and other interested parties. Since 2004, the SARC has consisted
of a small panel of independent experts who convene to review
the scientific merit of the assessment analyses and determine
whether the assessments are sufficiently rigorous to form the
basis of management advice. The SAW has been very effective
in generating high quality assessment advice while enhancing
the credibility of this advice through intensive peer review
and participation by fisheries scientists, industry and the
general public.
2002, assessments of the 19-20 large mesh groundfish stocks
managed by the New England Fishery Management Council under
the Northeast Multi-Species Fishery Management Plan have been
assessed on a three year cycle at Groundfish Assessment Review
Meetings (GARM).
additional pathway has recently become available, the
Transboundary Resource Assessment Committee (TRAC) process
for completion and peer-review of assessments for transboundary
resources shared by Canada and the United States. The
two countries have cooperated closely for many years
in collecting and sharing data, preparation of joint
assessments and peer review activities; and in recent
years it has become obvious that a formal cooperative
arrangement would promote efficiency and consistency
in reporting. As a result, a unified process was started
in 1998. This consists of both periodic assessment benchmark
meetings and annual assessment update meetings. The
benchmarks take place off the management cycle and perform
in-depth model formulation and model comparison reviews.
The annual updates apply the benchmark standards in
the updated assessments and forward consensus-based
reports for use in resource management by both countries.
To date, the TRAC process has been used only for Georges
Bank stocks of cod, haddock and yellowtail, as well
as the Georges Bank/Gulf of Maine Atlantic herring complex
and it provides a logical option for other transboundary
terms used throughout this document may not be familiar to all.
A brief explanation of some of these terms follows, organized
level: Categories of the level of complexity of each
assessment included in this document are as given above (Index,
Surplus production, Yield per recruit, and Age/size structured).
The latter may include projections of future catch and stock
sizes or modeling of relationships between recruitment and spawning
stock size.
The long-term average stock biomass level required to achieve
Maximum Sustainable Yield or MSY, when the stock is fished at
FMSY. Biomass is usually measured in terms of metric
tons (mt).
(Minimum stock size threshold or MSST): One of two
Status Determination Criteria, specified in the national standard
guidelines as the greater of (a) ½ BMSY, or
(b) the minimum stock size at which rebuilding to BMSY
will occur within 10 years when fishing at the Maximum Fishing
Mortality Threshold or MFMT. At stock sizes below BTHRESHOLD,
the stock is considered to be overfished.
Biological reference
points: Specific values for variables that describe
the state of a fishery, used to evaluate its status. These may
include "target" reference points, corresponding to
a desired goal or level and "limit" reference points
or "thresholds" carrying an unacceptably high risk
to the stock if exceeded. Examples are F0.1, FMSY,
FTHRESHOLD, and Fmax.
Biomass-weighted F: An estimate of fishing
mortality in which F for each age group in the stock, as determined
from virtual population analysis or VPA, is weighted by corresponding
stock biomass-at-age values. This calculation is needed to make
F from age structured assessments comparable to FMSY
estimates obtained from surplus-production (e.g. ASPIC) modeling
of all components in the stock.
Catch per unit
effort (CPUE): A measure of relative success of fishing
operations, often used as a proxy for relative abundance under
the assumption of a linear relation to stock size. To be valid,
should be standardized to account for differences in fishing
power or temporal/spatial changes in catchability.
Control rule (MSY Control Rule): A protocol
for specifying harvest rates in relation to stock status and
limit and target reference points. Technically, a harvest strategy
which, if implemented, would be expected to result in a long-term
average catch approximating MSY.
Exploitation pattern: The distribution of fishing
mortality over the age composition of the fish population, determined
by the type of fishing gear, areal and seasonal distribution
of fishing, and the growth and migration of the fish. The pattern
can be changed by modifications to fishing gear, for example,
increasing mesh or hook size, or by changing the ratio of harvest
by gears exploiting the fish (e.g., gill net, trawl, hook and
line, etc.).
rate: The proportion of a population at the beginning
of a given time period that is caught during that time period
(usually expressed on a yearly basis). For example, if 720,000
fish were caught during the year from a population of 1 million
fish alive at the beginning of the year, the annual exploitation
rate (or annual fishing mortality rate) would be 0.72. Note
that this rate cannot exceed unity; obviously, more fish cannot
die than were originally present.
mortality rate (F): That part of the total mortality
rate applying to a fish population that is caused by fishing.
Fishing mortality is usually expressed as an instantaneous rate,
as discussed under Mortality rates, and can range to values
exceeding unity, such as 2.0 or higher.
Fmax: The fishing mortality rate
that results in the maximum level of yield per recruit. This
is the point that defines growth overfishing.
The fishing mortality rate at which recruitment balances removals
over time, as estimated from stock recruitment data.
The fishing mortality rate that produces MSY by taking a constant
fraction of a stock that is fluctuating around BMSY.
The fishing mortality rate at which the increase in yield per
recruit in weight for an increase in a unit of effort is 10
percent of the yield per recruit produced by the first unit
of effort on the unexploited stock (i.e., the slope of the yield
per recruit curve for the F0.1 rate is one tenth
the slope of the curve at its origin).
The fishing mortality rate at which spawning per recruit (usually
using spawning biomass per recruit as a proxy) is reduced to
20% of the unfished level. Other levels may be used depending
on biological characteristics of the target species and/or management
The fishing mortality rate(s) that, when applied over a specified
time frame, will result in stock biomass increasing to BMSY
with some specified probability level).
The fishing mortality rate which (with some specified probability
level) will prevent FTHRESHOLD from being exceeded.
(Maximum fishing mortality threshold or MFMT): One
of two Status Determination Criteria specified in the national
standard guidelines as the fishing mortality rate associated
with the MSY Control Rule. Usually, FTHRESHOLD is
FMSY if stock biomass is moderate to high, and a
lower value if it is low. Exceeding FTHRESHOLD for
one year or more constitutes overfishing.
F: An estimate of fishing mortality for all age groups
fully vulnerable to fishing. It may or may not be weighted by
population size in number.
Growth overfishing: The rate of fishing, as
indicated by a yield-per-recruit curve, greater than that at
which the loss in weight from total mortality equals the gain
in weight due to growth. This point is defined as Fmax.
Reported in this document wherever possible as median length
or age at maturity (L50 or A50) as determined
from length and age-specific maturation ogives.
Maximum sustainable yield (MSY): The largest
long-term average catch or yield that can be taken from a stock
or stock complex under prevailing ecological and environmental
conditions. In order to achieve the maximum average yield over
the long term it will usually be necessary to vary annual yields
in response to natural fluctuations in stock size (e.g. by applying
a constant fishing mortality rate of FMSY).
spawning potential reference points: Reference points
based on some fraction of maximum spawning potential (MSP) as
determined from spawning stock biomass per recruit models, used
to define overfishing. MSP is the spawning stock biomass per
recruit in the absence of fishing; it is then reduced to a percentage
of the maximum as F increases. If the %MSP level is reduced
below the overfishing definition level, then the stock is considered
to be overfished. This level is typically determined by stock-recruitment
modeling, to determine the fishing mortality rate beyond which
the stock will be unable to replace itself.
biomass: The product of mean abundance (numbers) and
the average weight of individual fish. Mean abundance is calculated
from abundance at the beginning of the year and the annual mortality
rate, while average weights are derived from population size
and weight at age data. Mean abundance and biomass are usually
calculated for each age group separately and then summed to
estimate the mean biomass of the population.
Mortality rates:
The rates at which fish die from fishing and/or natural causes.
Mortality rates can be described in several ways.
conceptually simple approach is to express mortality on an annual
basis, i.e., A, the annual mortality rate, expressed
as a proportion (5% or 0.05 per year). This is the fraction
of the population alive at the beginning of the year which dies
during the year. The survivors may be represented by (1-A) =
S, the annual survival rate.
exploited populations, however, it is important to account for
both fishing and natural mortality. This can pose complex problems,
because population changes tend to be exponential; and different
components tend to be multiplicative (that is, in any given
period of time, individuals that die from natural causes would
otherwise be killed by fishing and vice versa).
these reasons, biologists tend to work with instantaneous
rates, in which time intervals are sufficiently short so as
to allow separation of the primary components as instantaneous
fishing mortality (F) and instantaneous natural mortality (M).
Together the two are equivalent to instantaneous total mortality
(Z), i.e. Z = F+M.
necessary mathematics are based on a logarithmic scale which
relates well to biological processes (since they tend to be
exponential); and effects which are multiplicative in nature
become additive on a logarithmic scale.
The concept of instantaneous
rates can be illustrated by a simple example. Imagine a year
of a fish's life to be divided into a large number (n)
of equal time intervals, and Z/n is the number dying within
that interval. If n = 1,000 and Z =1.0, then during the first
time interval 1/1000 = 0.1% of the population dies. For a population
of 1,000,000 fish, 1000 would die, leaving 999,000 survivors.
In the next time interval 0.1% of 999,000 fish, or 999 fish
die, leaving 998,001 survivors, and so on. Repeated 1,000 times,
we would have:
e is the base of natural logarithms (2.71828).
calculation provides the same approximate result. Note that
the annual mortality rate A = 1-e -Z, hence, 1-0.3679
or 0.6321 or 63% in our example. Again, A can never exceed
unity, although F and Z can considerably exceed unity for
heavily exploited stocks.
The utility of instantaneous rates for dealing with different
sources of mortality over time can be illustrated as follows.
Assume a population at the beginning of a given year consists
of 1,000 fish, and that during the year it is subjected to
an instantaneous fishing mortality rate of F = 0.5, while
instantaneous natural mortality (M) = 0.2. The instantaneous
total mortality rate (Z) is equal to (F+M) = 0.7. Removals
by fishing are calculated by applying the annual exploitation
the year, 0.3596(1000) = 360 fish are caught, and S = e -0.7
= 0.4966(1000) = 497 fish survive. The difference from the
original number of 1,000 fish (1,000-360-497), or 143 fish,
is the number dying from natural causes. The additive property
of instantaneous rates allows us to obtain approximately the
same result for natural mortality, i.e.,
the absence of fishing this number would be A = (1-e -0.2)1000
= 0.1813 x 1000 = 181 fish, with 819 fish surviving to the
beginning of the following year. If the process is continued
for another year, the catch in the exploited population would
be 179 fish, 71 fish would die from natural causes, and 247
fish would survive, while in the unfished population 149 fish
would die, leaving 670 survivors. Continued for 10 years the
exploited population would be essentially eliminated (1 surviving
fish) whereas 14% of the unfished population (135 fish) would
example uses an annual exploitation rate (36%) for the exploited
population that is somewhat high but was sustained historically
by some Northeast stocks. For some heavily fished stocks exploitation
rates have in some years exceeded 50-60 percent. The number
of fish alive after 5 years from a year class of 1,000,000
fish exploited at F=1.0 and M=0.2 (58% exploitation rate)
would be:
mortality rate (M): That part of total mortality
applying to a fish population that is caused by factors other
than fishing. It is common practice to consider all sources
together since they usually account for much less than fishing
mortality. It is usually expressed as an instantaneous rate
as discussed above.
catch: The sum of the catches that are landed (expressed
as live weight or equivalent). Nominal catches do not include
Optimum yield (OY): The amount of fish that
will provide the greatest overall benefit to the nation, particularly
with respect to food production and recreational opportunities
and taking into account the protection of marine ecosystems.
Under the Magnuson-Stevens Fishery Conservation and Management
Act or MFCMA, OY cannot exceed MSY.
According to the National Standard Guidelines, "overfishing
occurs whenever a stock or stock complex is subjected to a
rate or level of fishing mortality that jeopardizes the capacity
of a stock or stock complex to produce MSY on a continuing
basis." Overfishing is occurring if FTHRESHOLD
is exceeded for a year or more. An "overfished"
stock has been reduced below BTHRESHOLD requiring
management actions to rebuild to the MSY level within an acceptable
time frame.
definition: An objective and measurable guideline
or guidelines for a given stock defining a fishing mortality
rate that constitutes overfishing, and/or the point at which
the stock reaches an overfished condition; formerly required
for each fishery management plan or FMP under revised guidelines
(50 CFR Part 602) to National Standards 1 and 2 of the Magnuson
Fishery Conservation and Management Act or MFCMA. Reauthorization
of the Act (Magnuson-Stevens Fishery Conservation and Management
Act or MSFCMA) under the Sustainable Fisheries Act or SFA
resulted in a requirement for status determination criteria
to describe both overfishing and the condition of being overfished.
A portion of a total allowable catch (TAC) allocated to an
operating unit, such as a vessel size class or a country.
The amount of fish added to the exploitable stock each year
due to growth and/or migration into the fishing area. The
number of fish that grow to become vulnerable to the fishing
gear in a given year would be the recruitment to the fishable
population in that year. The term is also used in referring
to the number of fish reaching a certain age or size.
overfishing: The rate of fishing above which recruitment
to the exploitable stock becomes significantly reduced. This
is characterized by a greatly reduced spawning stock, a decreasing
proportion of older fish in the catch, and generally very
low recruitment year after year.
stock biomass (SSB): The total weight of all sexually
mature fish in the population. This quantity depends on year
class abundance, the exploitation pattern, the rate of growth,
fishing and natural mortality rates, the onset of sexual maturity
and environmental conditions.
Spawning stock
biomass per recruit (SSB/R): The expected lifetime
contribution to the spawning stock biomass for a recruit of
a specific age (e.g., per age 2 individual). For a given exploitation
pattern, rate of growth, and natural mortality, an expected
equilibrium value of SSB/R can be calculated for each level
of F. A useful reference point is the level of SSB/R that
would be realized if there were no fishing. This is a maximum
value for SSB/R, and can be compared to levels of SSB/R generated
under different rates of fishing. For example, the maximum
SSB/R for Georges Bank haddock is approximately 9 kg for a
recruit at age 1.
Catch at Age Model: An approach to estimating population
abundance and fishing mortality rates from catch at age data
and indices of abundance. These models start at the earliest
point of available data and project forward through the time
series. Fishing mortality is separated into age and year components.
The models change parameters such as recruitment, fishing
mortality by year, selectivity at age, and catchability coefficients
until the predicted catch and indices most closely match the
observed values. In essence, statistical catch at age models
create a simulated population using a set of parameters that
generates predicted values. The parameters are changed until
the predicted values most closely match the observed values.
There is a great deal of flexibility in the approach because
missing data are easily handled and many types of data can
be matched by the simulated population.
Determination Criteria: Objective and measurable
criteria used to determine if overfishing is occurring or
the stock is in an overfished state according to National
Standard Guidelines.
Total allowable catch is the total regulated catch from a
stock in a given time period, usually a year.
Vessel class:
Commercial fishing vessels are classified according to their
gross registered tons (grt) of displacement. Vessels displacing
less than 5 tons were not routinely monitored prior to the
new mandatory reporting system implemented in the Northeast
in 1994, and were referred to as undertonnage. The current
classification scheme is as follows:
population analysis (or cohort analysis): An analysis
of the catches from a given year class over its life in the
fishery. If 10 fish from the 1988 year class were caught each
year for 10 successive years from 1990 to 1999 (age 2 to age
11), then 100 fish would have been caught from the 1988 year
class during its life in the fishery. Since 10 fish were caught
during 1999, then 10 fish must have been alive at the beginning
of that year. At the beginning of 1998, there must have been
at least 20 fish alive because 10 were caught in 1998 and
10 more were caught in 1999. By working backward year by year,
one can be virtually certain that at least 100 fish were alive
at the beginning of 1990.
virtual population analysis goes a step further and calculates
the number of fish that must have been alive if some fish
also died from causes other than fishing. For example, if
in addition to the 10 fish caught per year in the fishery,
the instantaneous natural mortality rate was also known, then
a virtual population analysis calculates the number that must
have been alive each year to produce a catch of 10 fish each
year plus those that died from natural causes.
one knows the fishing mortality rate during the last year
for which catch data are available (in this case, 1999), then
the exact abundance of the year class can be determined in
each and every year. Even when an approximate fishing mortality
rate is used in the last year (1999), a precise estimate of
the abundance can usually be determined for the stock in years
prior to the most recent one or two (e.g., for 1990-1996 or
1997 in the example).
depends on the rate of population decline and the correctness
of the starting value of the fishing mortality rate (in the
most recent year). This technique is used extensively in fishery
assessments, since the conditions for its use are so common;
many fisheries are heavily exploited, the annual catches for
a year class can generally be determined, and the natural
mortality rate is known within a fairly small range and is
low compared with the fishing mortality rate.
class (or cohort): Fish in a stock born in the same
year. For example, the 2005 year class of cod includes all
cod born in 2005, which would be age 1 in 2006. Occasionally,
a stock produces a very small or very large year class which
can be pivotal in determining stock abundance in later years).
Yield per
recruit: The expected lifetime yield for a fish of
a specific age (e.g., per age 2 individual). For a given exploitation
pattern, rate of growth, and natural mortality, an expected
equilibrium value of Y/R can be calculated for each level
of F.
For further
Anon. 1998a. Improving Fish Stock Assessments. Committee on
Fish Stock Assessment Methods. Ocean Studies Board. National
Research Council. National Academy Press, Washington, D.C.,
177 p.
1998b. Review of Northeast Fishery Stock Assessments. Committee
to Review Northeast Fishery Stock Assessments. Ocean Studies
Board. National Research Council. National Academy Press,
Washington, D.C., 128 p.
A., S. Cadrin, J. Hoenig, C. Moore, S. Murawski and E. Pikitch.
1998. Evaluation of existing overfishing definitions and recommendations
for new overfishing definitions to comply with the Sustainable
Fisheries Act. Final Report of the Overfishing Definition
Review Panel to the New England Fishery Management Council.
179 p.
W.L. and P.M. Mace. 1999. A review of biological reference
points in the context of the precautionary approach, p. 34-45.
In: Restrepo, V.R. ed. Proceedings of the Fifth National NMFS
Stock Assessment Workshop. NOAA [National Oceanic and Atmospheric
Administration] Tech. Memo. NMFS-F/SPO-40. 161 p.
W.L., M.P. Sissenwine, and W.J. Overholtz. 1989. Analysis
of spawning stock biomass per recruit: an example for Georges
Bank haddock. N. Am. J. Fish. Mgmt. 9: 383 391.
J.A., ed. 1988. Fish population dynamics. John Wiley &
Sons, Inc., New York. 422 p.
R. and C.J. Walters. 1992. Quantitative fisheries stock Assessment:
choice, dynamics and uncertainty. London: Chapman and Hall.
570 p.
L., J. Burnett, and R.K. Mayo. 1993. Maturation of 19 species
of finfish off the northeast coast of the United States, 1985-
1990. NOAA [National Oceanic and Atmospheric Administration]
Tech. Rept. NMFS 113. 66 p.
T. J. and R.B. Deriso. 1999. Quantitative fish dynamics. Oxford
University Press, Inc., New York. 542 p.
V.R., G.G. Thompson, P.M. Mace, W.L. Gabriel, L.L.Low, A.D.
MacCall, R.D.Methot, J.E. Powers, B.L. Taylor, P.R. Wade,
and J.F. Witzig. 1998. Technical guidance on the use of precautionary
approaches to implementing National Standard 1 of the Magnuson-Stevens
Fishery Conservation and Management Act. NOAA [National Oceanic
and Atmospheric Administration] Tech. Memo. NMFS-F/SPO-31.
54 p.
V. R., P. M. Mace, and F. Serchuk. 1999. The precautionary
approach: a new paradigm or business as usual? P 61-70. In:
NMFS. 1999. Our living oceans. Report on the status of U.S.
living marine resources, 1999. U.S. Dep. Commer., NOAA Tech.
Memo. NMFS-F/SPO-41, 301 p.
Rosenberg, A., convener.
1994. Scientific review of definitions of overfishing in U.S.
fishery management plans. NOAA [National Oceanic and Atmospheric
Administration] Tech. Memo. NMFS F/SPO 17. 205 p.
Back to Top
Return to Status of Fishery Resources off the Northeastern US


text:
Press Release
Caltrans Releases Long-Range Transportation Plan Update
CTP 2040 sets course toward economically sound, sustainable future
Date: June 28, 2016
District: Headquarters
Contact: Tamie McGowen
Phone: (916) 657-5060
SACRAMENTO – Caltrans is pleased to present the California Transportation Plan (CTP) 2040, the State's new long-range integrated approach toward transportation planning that is multimodal, sustainable and environmentally responsible. The plan presents a set of supporting goals, policies and recommendations to chart a long-term vision to help guide transportation decisions and investments in the 21st century that meet our future multimodal mobility needs and reduce greenhouse gas emissions.
"The California Transportation Plan 2040 sets the correct course for the state's transportation future. With a growing population that requires an integrated, effective transportation system, the Plan will improve transit options while fulfilling economic and environmental goals."
The CTP 2040 takes a "whole system" approach toward the state's transportation system that integrates statewide long-range modal plans and programs with the latest technology and tools to articulate the State's broad vision for a single, seamless transportation system that complements regional transportation plans, sustainable communities strategies and land-use visions for greater mobility choices.
Preparation of the CTP 2040 included an extensive outreach campaign through an open and collaborative planning process with input and guidance from transportation partners representing various governmental agencies, tribal governments, and advocacy groups who participated on the CTP's Policy Advisory and Technical Advisory Committees. The plan also gathered input from a wide range of stakeholders, including the public, elected and appointed officials, and community-based organizations across the state.
Achieving the goals and polices of the CTP 2040 and transforming the transportation system from where California is now to where it needs to be in 2040 will take significant effort among transportation partners and stakeholders, as well as broad public support. The CTP provides recommendations for how California can move toward its greenhouse gas reduction targets and achieve the vision for a fully integrated, multimodal, and sustainable transportation system that enhances California's economy and livability.
The CTP 2040 is available at http://www.dot.ca.gov/hq/tpp/californiatransportationplan2040/2040.html.
Statewide Alerts and Other Information
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You can also call
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text:
Child Custody Order Not Being Followed
Amanda Szpakowski My name is Amanda Szpakowski. I am the Family Law legal assistant here at the Bornmann Law Group. I specialize in anything family lawrelated custody, visitation, father's rights, anything family law. Is what we could put in place called Emergency Temporary Orders. And basically what that is, is if there's a situation where a parent is not being able to see the minor child, or the minor child is in a dangerous situation that could compromise his safety, we could ask for an Emergency Temporary Orders hearing. This could be with or without the other party's notice, depending on the seriousness of the matter.


text:
Tag Archives: Professionals
Where to work? Julius Meinl
The first time I went to Julius Meinl was about three years ago. It has been a while, but like a fine wine this place continues to get better. Not much has changed, at least anything I can remember. The service … Continue reading
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Featured Songs - Click to Get Lyrics
- Yankee Doodle Boy
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- Alouette
- The Muffin Man
- Harrigan
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- Ta-Ra-Ra-Boom-Dee-A
- I'm A Big Boy Now
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- Jump-Jump, Turn Around, Start Again
- Don't You Just Love To Waltz?
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- The Yellow Rose Of Texas
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- Old MacDonald Had A Farm
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- I Wanna Be A Fireman
- Them Bones
- Mr. Policeman
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Song Previews
Yankee Doodle Boy [Song MP3]
Adventures in Biggleland [Song MP3]
East Side, West Side [Song MP3]
Alouette [Song MP3]
The Muffin Man [Song MP3]
Harrigan [Song MP3]
Let's Be Silly [Song MP3]
Ta-Ta-Ra Boom-Dee-A [Song MP3]
I'm a Big Boy Now [Song MP3]
Simon Says [Song MP3]
Jump-Jump, Turn Around, Start Again [Song MP3]
Don't You Just Love to Waltz? [Song MP3]
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text:
Latest buy's.
main () The Garage
Scale Modeling Sponsors
This came in the mail yesterday from all the way in the Ukraine.
It is a 1/24 scale replica of wheels of wheels made by MTechnica, a company that I design wheels for. USCP has a pretty large selection of transkits and resin wheels.
Quality on the wheels seem pretty crisp and clean as well.
49 Mercury blues.
Nice one James.
We should have a Cop car group build?


text:
WITHOUT A TRACE: ISU Creates Dissolving Technology
An Iowa State University professor has developed electronics that are able to store and send sensitive data, but be destroyed down to nothing if compromised.
The small circuit might not seem like much but this small technology could change the world in a big way.," says ISU Assistant Professor of Mechanical Engineering Reza Montazami.
Montazami has created a circuit board, capable of collecting and transmitting data that will dissolve once it's done its job.
The technology can be used in everything from medical devices that travel inside the body to the military and intelligence operations.
"If a soldier on the front line is wounded or killed and you want to protect your electronics and the data that`s on the electronics, you want to prevent them from being recovered by the enemy you can have them dissolve in the environment," says Montazami.
Montazami says the polymer based product is degradable and environmentally friendly.
By adding water the circuit board starts to dissolve, destroying all sensitive data that was on it.
Eventually, that will also include the specially made casing surrounding the data chip.
"You want to leave zero trace, no trace," says Montazami.
Montazami says he's working on the technology being able to dissolve from a trigger, meaning you could remotely destroy the data from anywhere.
It's technology that's not being researched anywhere else in the state and technology that Montazami says has limitless potential.
"It has its own challenges but it`s very interesting and I very much enjoy it," says Montazami.
Montazami says he's still early in his research but eventually he hopes this technology can be used in cell phones, credit cards, passports and even driver's licenses.
So if you lost any of these items you could remotely dissolve them rather than worrying about them falling into the wrong hands.


text:
Product Details
ShopResponse time: A few hrs.Response rate: 60%
MaterialUnique featuresCustomizable, Exclusive to PinkoiQuantityDown to the last 10
This handmade scarlet red formal clutch bag is ideal as wedding purse or formal purse. It would make a great Christmas gift for her and a show-stopping accessory to complete your party outfit. (For larger quantities, color variations and customization options, for matching bridesmaid purses, for instance, please contact me.)
The little red lace purse is carefully handmade from glossy ribbon yarn in the most opulent shade of scarlet red. The zippered lining is sewn from double textile in matching colors. The purse has an easily removable crochet wristlet complete with a stunning Swarovski Elements crystal button.
The designs and patterns for all my crochet purses and clutch bags are my own originals.
Measurements of the handbag:
- length: 23 cm (9.1 inches)
- maximum height: 12 cm (4.7 inches)
- crochet wristlet: 24 cm (9.4 inches)
Care instructions: hand-wash in cool water, iron on low temperature.
- - -
* Like the design of the small crochet wristlet bag, but not sure about scarlet red? If you have specific color preferences, please do not hesitate to contact me. I love taking custom orders and brainstorm with you to find the perfect solution!
* * For available color variations and designs, please browse my store for more options.
* * * Please consider that although I am doing my best to capture the right colors of my items, the actual shades may vary slightly due to different monitor settings.
Manufacturing Details
Handmade in Estonia
- Int'l shipping
Ship from: Estonia Ship to: 1st item 2nd item Taiwan FREE S/H Other countries/regions FREE S/H
The shipping fee to United States is counted under "Other countries/regions".
- PaymentCredit/debit card payment, PayPal, Alipay
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